Diameter-Transformed Fluidized Bed: Fundamentals and Practice [1st ed.] 9783030475826, 9783030475833

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Particle Technology Series

Youhao Xu · Bona Lu · Mingyuan He  Yujie Tian · Wei Wang

Diameter-Transformed Fluidized Bed Fundamentals and Practice

Particle Technology Series Volume 27

Series editor José Manuel Valverde Millán, University of Sevilla, Spain

Many materials exist in the form of a disperse system, for example powders, pastes, slurries, emulsions and aerosols, with size ranging from granular all the way down to the nanoscale. The study of such systems necessarily underlies many technologies/ products and it can be regarded as a separate subject concerned with the manufacture, characterization and manipulation of such systems. The series does not aspire to define and confine the subject without duplication, but rather to provide a good home for any book which has a contribution to make to the record of both the theory and applications of the subject. We hope that engineers and scientists who concern themselves with disperse systems will use these books and that those who become expert will contribute further to the series. The Springer Particle Technology Series is a continuation of the Kluwer Particle Technology Series, and the successor to the Chapman & Hall Powder Technology Series.

More information about this series at http://www.springer.com/series/6433

Youhao Xu • Bona Lu • Mingyuan He Yujie Tian • Wei Wang

Diameter-Transformed Fluidized Bed Fundamentals and Practice

Youhao Xu Sinopec Research Institute of Petroleum Beijing, China

Bona Lu Institute of Process Engineering Chinese Academy of Sciences Beijing, China

Mingyuan He Sinopec Research Institute of Petroleum Beijing, China

University of Chinese Academy of Sciences Beijing, China

Wei Wang Institute of Process Engineering Chinese Academy of Sciences Beijing, China

Yujie Tian Institute of Process Engineering Chinese Academy of Sciences Beijing, China

University of Chinese Academy of Sciences Beijing, China

University of Chinese Academy of Sciences Beijing, China

ISSN 1567-827X Particle Technology Series ISBN 978-3-030-47582-6 ISBN 978-3-030-47583-3 https://doi.org/10.1007/978-3-030-47583-3

(eBook)

© Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Foreword

About 90% of energy, environmental and chemical production processes are accompanied by catalytic reactions. As the challenge of resources and environment becomes increasingly severe, the demand for diverse chemical products keeps growing simultaneously. This has become an important innovation direction for industrial catalytic technology to realize efficient utilization of resources through directional transformation of chemical raw materials. To a great extent, the high efficiency produced by catalysts is achieved through the development of catalytic processes, whereas the core of catalytic processes is the design and optimization of catalytic reactors. The development and design of reactors and the synthesis of highperformance catalyst are always in complementary. Dr. Youhao Xu, the first author of this book, received his master’s degree from the UNILAB Research Center of Chemical Reaction Engineering of East China University of Science and Technology, where he engaged in catalytic reaction engineering research under the supervision of Prof. Lian Zhang and me. After graduation, Dr. Xu joined SINOPEC Research Institute of Petroleum Processing (RIPP) and received his doctorate in 2006. Since then, he has been committed to the research and development of fluidized bed reactors and processes, and has made massive achievements in both fundamental research and industrial application. Prof. Mingyuan He, a friend of mine and also an author of this book, has made great contributions to catalytic materials and reactions. The other three authors, Dr. Bona Lu, Dr. Yujie Tian and Prof. Wei Wang, are young researchers of Prof. Jinghai Li’s team at the Institute of Process Engineering (IPE), Chinese Academy of Sciences (CAS), and also the University of Chinese Academy of Sciences (UCAS). Prof. Li proposed the EMMS (the Energy-Minimization Multi-Scale) model, which has shown its unique capability in reasonably predicting the global flow structure and flow regime transitions in gas-solid fluidization. Prof. Wang, Dr. Lu and Dr. Tian developed the EMMS model and successfully applied it to simulation of a series of DTFBs. These authors constitute a perfect team for writing this book. After the invention of DTFB reactor, Dr. Xu and his team continued to develop a number of oil refining and chemical techniques based on the platform of DTFB v

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reactor, which have been widely used in industry and have generated great economic benefits. The industrial test was conducted in the heavy oil processing industry, which has been systematically investigated and is expected to be widely used in other chemical technology fields. The FCC process in China was pioneered by Enze Min, Junwu Chen, Baochen Wu and others, and we all witnessed with pleasure the big progress carried through in the past decades. Dr. Xu has made great contributions in this field with teaching and technical innovations, and he has been well recognized as an excellent expert by receiving a number of national prizes and awards on developing FCC. This book systematically summarized the invention, fundamental research, industrial practice and application of DTFB reactors from a perspective of catalytic reaction engineering. It will definitely make a big impact on the technological progress of oil refining and chemical industry and further promote the research in the field of complex gas-solid catalytic reactions. In view of the academic value of this book and the fact that the DTFB reactor has become a successful case of process innovation in China, I am very glad to write a foreword to this book. East China University of Science and Technology Beijing, China December 25, 2019

Weikang Yuan

Preface

The invention of diameter-transformed fluidized bed (DTFB) reactor, which refers to a fluidized bed characterized by the coexistence of multiple flow regimes and reaction zones, achieved by transforming the bed into several sections of different diameters, can be traced back to May 1998, when China was carrying out the clean gasoline program for vehicles. In 1999, GB 17930-1999 Automotive Unleaded Gasoline Quality Standard was promulgated, requiring the olefin volumetric content of automotive gasoline to be reduced to less than 35%. At that time, the olefin volumetric content of FCC gasoline was 40% ~ 65% and fluid catalytic cracking (FCC) process was facing a severe challenge of upgrading gasoline quality. Based on experimental results and the analysis of hydrocarbon chemical reactions, we proposed the concepts of cracking and conversion reaction zones and obtained desired results in lab experiments. On April 9, 1999, we applied for two Chinese patents, “Riser reactor for fluidized catalytic conversion” and “Catalytic conversion process for producing iso-butane and iso-paraffin enriched gasoline.” The two patents, which were applied from aspects of both processes and reactors, were considered based on the possibility that the multiple reaction zones formed in a fluidized bed reactor can be applied to some other catalytic reaction systems. That may shed light on solving the scientific problem that a single-zone, fluidized bed is difficult to handle. Therefore, in the reactor patent, apart from protecting the rights of unique structures of the reactor, we extended the protection to more applications in different reactors. Prof. Mingyuan He was the chief engineer of Research Institute of Petroleum Processing (RIPP), SINOPEC at that time. With the deepening understanding during his research, he became more and more convinced about the idea that the transformation of fluidized bed diameter can be used to construct multiple reaction zones to achieve high selectivity in complex catalytic reaction systems. In 2000, when Prof. He was the chief scientist for the project of “973 programme” of the Ministry of Science and Technology of China, entitled “Green chemistry of petroleum refining and synthesis of basic organic chemicals” (G200004800, 2000.10-2005.9), he included the research on this topic as the primary one. With the help of “973 vii

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programme”, the scientific research team systematically studied the parallel/series chemical reactions of hydrocarbons on catalysts and also obtained some valuable results under the guidance of Prof. He. In the following two “973” projects, the research team continued to carry out research on molecular level characterization and reaction kinetics, thus constructing a synergistic model of hydrocarbon catalytic reaction, diffusion, thermodynamics, and fluid dynamics, and pioneered a new approach to achieve orientational transformation of complex gas-solid catalytic reactions. Around 2000, while studying the complex catalytic reactions of hydrocarbons, RIPP research team worked closely with the team led by Prof. Jinghai Li, at the Institute of Process Engineering (IPE) of Chinese Academy of Sciences (CAS) and also the University of Chinese Academy of Sciences (UCAS). The gas-solid flow state in DTFB was simulated and experimentally studied at IPE. The characteristics of gas-solid flows were thoroughly investigated. The occurrence and conditions of the “choking” phenomenon were revealed as well. On this basis, the design team led by Mr. Xiren Hao, a National Design Master, determined the implementation plan of industrial reactor scaling-up. The production management team led by Mr. Hui Xu, who was the chief engineer of the refinery of SINOPEC Gaoqiao branch, evaluated that the risk of replacing the iso-diameter riser with a DTFB was controllable. At that time, Mr. Xianghong Cao, deputy general manager of SINOPEC, made the final decision about the direct, one-step scale-up, from the laboratory scale to large-scale industrial device, which was then found quite successful in industrial application. In the first industrial test, although a stable operation of DTFB reactor was achieved, the dense-phase fluidization section was difficult to form at the bottom of the second reaction zone. The design team led by Mr. Hao explored and adopted a number of measures according to the modeling results of the “choking” provided by IPE. Eventually, a stable, dense-phase fluidization section free from the “choking” was formed at the bottom of the second reaction zone of the industrial DTFB. Since 2007, the project development team of SINOPEC, including SINOPEC Engineering Incorporation (SEI), has continued to work with the modeling team of IPE and participated jointly in two National Science and Technology Support Programs of Ministry of Science and Technology (MOST), China. Through the continuous engineering practice, a more suitable distributor was developed, which successfully solved a series of problems such as the desirable flow distribution of gas and solids and a stable transition between flow regimes in the two reaction zones in a large DTFB. It was applied to the DTFB with a maximum diameter of 5.5 meters in the largest domestic 4.8 million tons/year FCC unit. It enables to form a stable fluidized bed at the bottom of the second reaction zone, avoids dangerous choking instability of gas-solid flows, and reduces the wear of catalyst by gas-solid flows, thus guaranteeing a long-cycle operation of DTFB. The project development team has been working at the forefront of research, design, and operation of catalytic processes for more than ten years. During this period, we have cooperated with Jinghai Li’s team in order to make DTFB to be used as a general reactor for complex gas-solid catalytic reactions. A number of new FCC processes have been developed, which have been widely used and have generated

Preface

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great economic and social benefits. For example, when the residue FCC process was developed and transformed from an iso-diameter riser to a DTFB, the increase of technical indicators was basically the same as that when the VGO FCC process was developed from amorphous silica-aluminum catalyst to molecular sieve catalyst. The latter uses the catalyst with molecular sieve as the active component to improve the reaction rate and selectivity, while the former applies the DTFB to further improve the utilization rate of molecular sieve so as to improve the reaction rate and selectivity. The technical invention aspects of these two techniques are different, but the increase rate of technical indicators is basically the same and both of them achieved significant progress. The former technique has more outstanding progress in liquid yield and gasoline octane number and requires less catalyst activity. Thus, the consumption of molecular sieve and rare earth was reduced. At present, the DTFB reactor has been widely used in residue FCC unit and has also been selected as the reactor for more than 80% of the processing capacity of SINOPEC FCC units. Acknowledgement should be given to both domestic and foreign colleagues/ counterparts in the field of chemical industry, who encourage us with positive comments on the development of DTFB reactors and the corresponding processes. Prof. Qin Xin, from Dalian Institute of Chemical Physics (DICP) of CAS, recognized DTFB-based FCC processes for maximizing iso-paraffin (MIP) as a major technological breakthrough in China’s oil refining in a paper entitled “China’s catalytic progress: theoretical and technological innovation.” MIP process was recognized as China’s independent innovation technology in the book preface of New Progress in China’s Refining Technology edited by Mr. Jiming Wang, where on Page 6, the MIP process was described as a major technology breakthrough to improve the efficiency level of oil refining industry, and a special introduction to MIP process was also included. Prof. Joachim Werther from TUHH introduced DTFB reactor in the special issue for the 100th anniversary of Ullmann Encyclopedia. Dual diameter riser (DTFB) was highly praised by the Handbook of Petroleum Processing (Edition 2, Springer, 2015), which was edited by experts from three major oil companies in the world, i.e., Steven A. Treese (Philips), Peter R. Pujado (UOP), and David S. J. Jones (Fluor). It has been recognized as one of the major innovations in the development of FCC technology in the past 70 years. The techniques of MIP and catalytic cracking process for producing clean gasoline (CGP) has been recommended in the “Hydrocarbon Processing’s 2011 Refining Processes Handbook” and introduced in the cover article. In 2016, State Intellectual Property Office and World Intellectual Property Organization granted “Riser reactor for fluidized catalytic conversion (ZL99105903.4, the master patent of DTFB reactor)” a Gold Medal of Chinese invention patents. In 2003, State Intellectual Property Office granted “Catalytic conversion process for producing iso-butane and iso-paraffin riched gasoline (ZL99105904.2, MIP process patent)” an Excellent Award of Chinese invention patent. It is expected that, based on DTFB reactors, more efficient processes in petroleum refining, petrochemical industry, and other chemical fields can be newly developed. It provides more suitable catalytic reaction engineering technology for complex gas-solid catalytic reactions and promotes the construction and development of petroleum refining and chemical engineering.

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During more than 20 years of research and development of this project, we have received much guidance and help from pioneering researchers in this area in China, to mention a few of them, Junwu Chen, Xianghong Cao, Dadong Li, Xieqing Wang, Xingtian Shu, Qiye Yang, Houliang Dai, Zaiku Xie, Zhixiong Guo, Renfeng Zhao, Yaohuan Chen, Zhe Yang, and others. Here, I would like to express my heartfelt thanks to all of them. The SINOPEC Science and Technology Department and the petroleum refining division have also provided massive help during the project establishment and implementation. Sincere thanks are given to Prof. Weikang Yuan for his time to write a foreword to this book. At the same time, I would like to thank all colleagues who participated in the research, design, and production management of this project. Many thanks to SINOPEC, PetroChina, CNOOC, Yanchang Group, China National Chemical Corporation, and private oil refiners who have applied DTFB reactors. Finally, my special thanks go to Prof. Jinghai Li, who cooperated with us all the time, for his selfless guidance and help. In order to promote the application of DTFB reactors in the development of new chemical technologies in the future, RIPP and IPE have again teamed up. The research achievements of the DTFB reactor in the past 20 years were systematically summarized and compiled. Youhao Xu and Mingyuan He wrote Chaps. 1, 5, 6, 7 and 8. Chapter 2, which is an addendum compared to this book of Chinese edition, targeting more fundamental understanding of flow regimes in fluidized beds, was written by Yujie Tian and Wei Wang. Bona Lu wrote Chap. 3, in which the experimental contents were summarized based on the research report of gas-solid flows in a cold-model DTFB, originally prepared by Bingyu Chen, Linpei Xia, Shiqiu Gao, and Xianghui Wang, and the simulation contents were summarized based on the doctoral thesis of Dr. Congli Cheng. Chap. 4 was written by Bona Lu and Wei Wang. Shouye Cui provided some materials for Chap. 6, Sect. 6.3 and Chap. 8, Sect. 8.3. In the process of writing this book, I have received meticulous guidance from Prof. Jinghai Li and Prof. Zaiku Xie, and here I would like to express my heartfelt thanks. Mr. Zhijian Da, President of RIPP, provided a lot of support and help for the publication of this book. Zuo Yanfen, Sun Xin, Xia Yuetong, Xie Wanni, and other colleagues translated Chaps. 1, 5, 6, 7 and 8 of this book of Chinese edition. Bona Lu revised Chaps.1, 5, 6, 7 and 8 of this book, and many students including Zhuo Yang, Chunhua Zhang, Caixia Han, Fei Xu, Chengzhe Du, Xing Zhao, Honglin Duan and Boyu Jia helped produce figures. Hereby I would like to express my sincere thanks to them. Due to the limitation of our knowledge and experience, there could be some improper points in the book. We are glad to receive comments and corrections from readers. Beijing, China December 17, 2019

Youhao Xu

About the Book

This book systematically summarizes the invention, theoretical research, industrial practice and application of diameter-transformed fluidized bed (DTFB) reactor from the perspective of catalytic reaction engineering. Here, DTFB refers to a fluidized bed characterized by the coexistence of multiple flow regimes and reaction zones, achieved by transforming the bed into several sections of different diameters. The book presents detailed explanation about how the concept of DTFB was innovated, and the major demands underlying such innovation, which has been driven further from the in-depth understanding of practice. Based on the conception formation, experimental development, theoretical simulation and large-scale implementation of DTFB, as well as its application in petroleum refining and chemical processes development, a novel catalytic reaction platform based on DTFB has been constructed. The research and cooperative development over DTFB provides a typical example of how the process development and innovation occur in China. This book is unique in that it provides a historical perspective on the development of a novel fluidized bed reactor and related new technologies, addressing both the success stories and the operational problems encountered in developing a variety of processes based on a DTFB reactor as well as providing abundant experimental and industrial operation data. It is an academic monograph with high theoretical level and practical value. It will promote the application of DTFB reactor in the development of new chemical processes in future. This book is intended for professionals engaged in the teaching, research, design and production of complex gas-solid catalytic reactions.

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Contents

1

2

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Catalysis Science and Technology . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Catalytic Reaction Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Complex Gas-Solid Catalytic Reactions . . . . . . . . . . . . . . . . . . . . 1.3.1 Gas-Solid Catalytic Reaction . . . . . . . . . . . . . . . . . . . . . . 1.3.2 Kinetics of Complex Reaction Systems . . . . . . . . . . . . . . . 1.3.3 Analysis of Complex Reaction Systems . . . . . . . . . . . . . . . 1.4 Design and Optimization of Complex Gas-Solid Catalytic Reactor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4.1 Type of Catalytic Reactors . . . . . . . . . . . . . . . . . . . . . . . . 1.4.2 Reactor Design Method . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4.3 Design and Optimization of Reactor in Complex Catalytic Reaction System . . . . . . . . . . . . . . . . . . . . . . . . 1.5 Structure of DTFB Reactor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5.1 Complex Catalytic Reactions . . . . . . . . . . . . . . . . . . . . . . 1.5.2 The Reactor Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 1 5 7 7 8 12

Fundamentals of Reactor Design and Scale-Up . . . . . . . . . . . . . . . . 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Flow Regimes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Regime Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Material Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.3 Geometric Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.4 The Choking Phenomenon . . . . . . . . . . . . . . . . . . . . . . . 2.3 Methods for the Design and Scale-Up of DTFBs . . . . . . . . . . . . 2.3.1 Analytical Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 Experimental Approach . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.3 Numerical Approach . . . . . . . . . . . . . . . . . . . . . . . . . . .

49 49 50 51 54 56 58 60 61 62 64

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16 16 18 20 35 35 38 45

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2.4 EMMS-Based Multiscale CFD Simulation . . . . . . . . . . . . . . . . . . 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

65 66 66

3

Cold Model Experiment and Reactor Modeling . . . . . . . . . . . . . . . . 71 3.1 Experimental . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3.1.1 Setup I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 3.1.2 Setup II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 3.1.3 Experimental Conditions . . . . . . . . . . . . . . . . . . . . . . . . . 76 3.2 Measurement Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 3.2.1 Pressure Drop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 3.2.2 Local Solids Concentration and Velocity . . . . . . . . . . . . . . 78 3.2.3 Solids Circulation Rate . . . . . . . . . . . . . . . . . . . . . . . . . . 80 3.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 3.3.1 Effect of Primary Solids Flux . . . . . . . . . . . . . . . . . . . . . . 81 3.3.2 Effect of Supplementary Solids Feed Rate . . . . . . . . . . . . . 84 3.3.3 Effect of Gas Velocity . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 3.3.4 Radial Distribution of Solids Velocity . . . . . . . . . . . . . . . . 87 3.3.5 Radial Distribution of Solids Concentration . . . . . . . . . . . . 89 3.4 Theoretical Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 3.4.1 Industrial DTFB Settings and Conditions . . . . . . . . . . . . . . 91 3.4.2 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 3.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

4

Multiscale CFD Simulation for DTFB Scale-Up . . . . . . . . . . . . . . . . 4.1 Simulation Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.1 Basic Governing Equations . . . . . . . . . . . . . . . . . . . . . . . 4.1.2 Solid Phase Stress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.3 Gas–Solid Drag Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Model Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Geometry and Simulation Setting . . . . . . . . . . . . . . . . . . . 4.2.2 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Simulation of Industrial DTFB Reactors . . . . . . . . . . . . . . . . . . . . 4.3.1 Operating and Simulation Parameters . . . . . . . . . . . . . . . . 4.3.2 Industrial DTFB Reactor 1 . . . . . . . . . . . . . . . . . . . . . . . . 4.3.3 Industrial DTFB Reactor 2 . . . . . . . . . . . . . . . . . . . . . . . . 4.3.4 Choking Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Reactive Simulation of a 1.2-Mt/a Industrial DTFB Reactor . . . . . 4.4.1 Geometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.2 Mathematical Equations . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.3 Simulation Settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Conclusion and Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

103 103 105 106 107 114 114 117 123 123 124 130 150 152 152 154 158 162 168 170

Contents

5

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Engineering Aspects and Application of DTFB . . . . . . . . . . . . . . . . 5.1 DTFB Structure and Internals . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.1 DTFB Structure and Dimension . . . . . . . . . . . . . . . . . . . 5.1.2 Steady-State Fluidization Distributor . . . . . . . . . . . . . . . . 5.1.3 Pre-Lifting Section of Low Pressure Drop . . . . . . . . . . . . 5.2 Ancillary Engineering Technology . . . . . . . . . . . . . . . . . . . . . . . 5.2.1 Double-Cycle Catalyst Transportation Technology . . . . . . 5.2.2 Cool and Hot Catalyst Pre-Lifting Mixer . . . . . . . . . . . . . 5.2.3 Other Engineering Techniques . . . . . . . . . . . . . . . . . . . . 5.3 Proprietary Catalyst . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.1 Catalytic Active Component . . . . . . . . . . . . . . . . . . . . . . 5.3.2 Coke Migration on Catalyst . . . . . . . . . . . . . . . . . . . . . . 5.3.3 Case Study of Proprietary Catalyst Development . . . . . . . 5.4 Technology Platform of DTFB Reactor . . . . . . . . . . . . . . . . . . . 5.4.1 DTFB Reactor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.2 Application in Petroleum Refining . . . . . . . . . . . . . . . . . 5.5 Application Analysis of DTFB Reactor . . . . . . . . . . . . . . . . . . . 5.5.1 Comparison with Y-Zeolite in Application . . . . . . . . . . . 5.5.2 Comparison with Equal-Diameter Fluidized Bed Reactor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5.3 Comparison with Equal-Diameter Riser Plus Dense-Phase Fluidized Bed Reactor . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6 Commercial Application and Economic Analysis of DTFB Reactor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6.1 Commercial Application . . . . . . . . . . . . . . . . . . . . . . . . 5.6.2 Economic Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6.3 Technology Licensing . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7 Social Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7.1 Progress in Petroleum Refining . . . . . . . . . . . . . . . . . . . . 5.7.2 Efficient on Utilization of Heavy Petroleum and Diversifying Chemical RAW Materials Sources . . . . . . . . 5.7.3 Development of Key Technologies for Motor Gasoline Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . .

173 173 173 176 187 189 189 194 197 198 198 198 203 205 205 206 206 206

Series of MIP Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 MIP Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.1 Mechanism Analysis on the Cracking Reaction and Hydrogen Transfer Reaction . . . . . . . . . . . . . . . . . . . 6.2.2 Experiment Studies on MIP Process . . . . . . . . . . . . . . . . 6.2.3 DTFB Reactor Experiments and Analysis . . . . . . . . . . . . 6.2.4 Comparison of the Pilot Plant Results Between MIP and FCC Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.5 Reaction-Regeneration System Design of MIP Process . . .

. 233 . 233 . 234

. 217 . 218 . . . . . .

220 220 221 223 224 224

. 225 . 226 . 231

. 236 . 245 . 251 . 254 . 257

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Contents

6.2.6 MIP Industrial Trials and Commercial Application . . . . . . . 6.2.7 Technical Features of MIP Process . . . . . . . . . . . . . . . . . . 6.3 CGP Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.1 Reaction Mechanism Analysis and Process Features . . . . . . 6.3.2 Pilot Plant Study on CGP Process . . . . . . . . . . . . . . . . . . . 6.3.3 Coupled Units for Clean Gasoline Components Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.4 Engineering Design Principles of Reaction-Regeneration Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.5 Industrial Running Test of CGP Process . . . . . . . . . . . . . . 6.3.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 LTG Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.1 Reaction Mechanism and Process Features . . . . . . . . . . . . 6.4.2 Bench Scale and Pilot Plant Experiments . . . . . . . . . . . . . . 6.5 DCR Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5.1 DCR Process Features . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5.2 Pilot Plant Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5.3 Engineer Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5.4 Commercial Performance Test . . . . . . . . . . . . . . . . . . . . . 6.5.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6 Fine Catalytic Cracking Process . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6.1 Reaction Pathway of Decalin and Product Analysis . . . . . . 6.6.2 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6.3 Experimental Results and Analysis . . . . . . . . . . . . . . . . . . 6.6.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

260 263 266 267 271

278 279 288 289 289 291 305 306 308 312 314 317 318 320 326 329 334 335

7

Effective Processing Technology of Heavy Oil . . . . . . . . . . . . . . . . . . 7.1 Heavy Oil Processing Technology . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Effective Utilization of Carbon and Hydrogen in the Heavy Oil . . . 7.2.1 Effect of Heavy Oil Processing Technology . . . . . . . . . . . . 7.2.2 Three Processing Routes . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 IHCC Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.1 Results and the Best Conversion Range . . . . . . . . . . . . . . . 7.3.2 Theoretical Basis of IHCC Process . . . . . . . . . . . . . . . . . . 7.3.3 Different Types of Reactors . . . . . . . . . . . . . . . . . . . . . . . 7.4 Commercial Trial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5 Summary and Prospect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

337 337 339 339 342 349 350 352 360 361 366 370

8

Applications in Chemical Industry and Other Fields . . . . . . . . . . . . . 8.1 Moderate Catalytic Cracking Process . . . . . . . . . . . . . . . . . . . . . . 8.1.1 Overview of Catalytic Cracking Process . . . . . . . . . . . . . . 8.1.2 Reaction Chemistry in MCC Process . . . . . . . . . . . . . . . . . 8.1.3 Pilot Plant Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

373 373 373 374 379

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xvii

8.1.4

Product Composition and Characteristics of MCC Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1.5 Integration of MCC and HVT Process . . . . . . . . . . . . . . . . 8.2 Production of Light Olefins from Methanol . . . . . . . . . . . . . . . . . 8.2.1 Experiment Unit and Method . . . . . . . . . . . . . . . . . . . . . . 8.2.2 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.3 Development Conception of Methanol to Light Olefin Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

380 388 393 394 395 405 407 408

Chapter 1

Introduction

Abstract This Chapter introduces the fundamentals of catalytic reaction engineering and complex gas-solid catalytic reactions as well as how the various reactors including fixed bed, moving bed and fluidized bed reactors being adapted to the complex heterogeneous reactions. It is found that it is fairly difficult to compromise the reaction conversion and the selectivity to the desired product employing the fluidized bed with a single reaction zone. A diameter-transformed fluidized bed (DTFB) reactor is then invented, in order to maximize the target reactions and inhibit/stop the undesired reactions by creating multiple reaction zones with different suitable reaction conditions in an engineering feasible way.

1.1

Catalysis Science and Technology

The catalysis science focuses on searching for the catalytic element principle, and the catalytic technology is the specific application of the principle of catalysis. Catalysis science is the scientific study of how and why a catalyst activates the molecules to be participated in a reaction and the properties and behaviors of these activated molecules. The presence of catalyst can greatly change the reaction rate, but it cannot change the thermodynamic equilibrium state of chemical reactions. For example, the synthesis of NH3 from N2 and H2 is thermally advantageous, but the reaction rate is very low without the presence of catalyst. Once a catalyst is added, the reaction rate of ammonia synthesis is significantly increased. There is another example, i.e., the reaction of hydrogen and oxygen to water, which is thermally advantageous. However, the reaction is too slow to be perceptible. When a catalyst is involved, it is then activated very quickly. Catalytic reactions and catalytic processes occur widely in nature. For example, plants use the light to synthesize carbon dioxide and water into organic compounds due to the catalytic action of chlorophyll. The catalyst can accelerate the chemical reaction, because after the catalyst being added, the reaction takes place along a pathway with low activation energy required. The importance of catalytic principle is reflected in the wide application of catalytic technology. Catalytic technology plays a very important role in the progress of human civilization and the development of world economy. Catalyst can help © Springer Nature Switzerland AG 2020 Y. Xu et al., Diameter-Transformed Fluidized Bed, Particle Technology Series 27, https://doi.org/10.1007/978-3-030-47583-3_1

1

2

1 Introduction

transform raw materials into chemical products and fuels with high added value in an efficient, green and economic way, so it is widely used in energy, chemical industry, food, medicine, electronics and other fields. There is no doubt that every major breakthrough in catalytic technology has greatly changed the way of human production and life. In 1746, nitrous oxide produced by saltpeter was actually a kind of gaseous catalyst, which was the beginning of industrial scale production using catalytic technology. In 1875, the first set of contact method device for producing fuming sulfuric acid via platinum containing catalyst for the first time, which was the very first use of solid industrial catalyst in catalytic technology. In 1906, Ostward used Pt/Rh alloy mesh as catalyst to develop the ammonia contact oxidation process for the production of nitric acid. Ostward won the 1909 Nobel Prize in chemistry for his work on the fundamental principles of catalysis, chemical equilibrium, and reaction rates. The synthetic ammonia industry has greatly enhanced the production of nitrogen fertilizer, which has improved food production and solved the problem of feeding billions of people. Therefore, industrial ammonia synthesis technology is considered to be the greatest chemical invention in the twentieth century and a pioneer in heterogeneous catalytic reactions. Because the invention of synthetic ammonia technology is of great significance, Nobel Prize in chemistry has been awarded three times to the outstanding researchers in this field. Fritz Haber won the 1918 Nobel Prize in chemistry for his work on synthetic ammonia. Bosch won the 1931 Nobel Prize in chemistry for his invention and development of high pressure catalytic reaction ammonia synthesis. Gerhard Ertl was awarded the 2007 Nobel Prize in chemistry for his work on solid surface chemistry. Coal liquefaction technology was developed in 1913, and the coal direct liquefaction industry is known as Bergius-Pier process. Bergius studied the hydroliquefaction of coal under high temperature and pressure, using an iron containing catalyst to generate liquid fuel. Bergius won the 1931 Nobel Prize in chemistry for his invention and development of high pressure chemical technology. In 1923, F-T synthesis technology was developed. In the same year, methanol production from syngas appeared. In 1930, ethylene epoxidation technology was established. After the 1930s, the oil industry developed rapidly. Alkylation technology has been developed in 1932 while in 1936, catalytic cracking technology was developed. In 1939, the catalytic reforming technology was developed, followed by hydrotreating and hydrocracking technologies. In 1950, Ziegler and Natta developed the olefin polymerization technology. They won the 1963 Nobel Prize in chemistry for their pioneering research in the chemical properties and technologies of polymers. In 1959, ammoxidation of propylene to acrylonitrile was developed, and in 1964, double decomposition of olefin was developed. Y. Chauvin, R. Schrock and R. Grubbs won the 2005 Nobel Prize in chemistry for developing the method of double decomposition in organic synthesis. In 1964, G. Wilkinson has developed a kind of RhCl(PPh3)3 catalyst, which successfully achieved the catalytic hydrogenation of olefin in alkane solution. It initiated a new era of homogeneous complex catalytic reaction. G. Wilkinson and E. Fisher won the 1973 Nobel Prize in chemistry for their pioneering work on the chemical properties of metal-organic compounds. In the field of asymmetric homogeneous catalysis, Knowles, Noyori and Sharpless have been awarded the Nobel Prize in chemistry in 2001 for their work on

1.1 Catalysis Science and Technology

3

chiral hydrogenation/oxidation reactions. In 1979, methanol was used to produce olefin. In 1989, three-way catalyst came out [1]. The development process of industrial catalytic technology in the past 200 years is like a big tree. The opening of branches and spreading of leaves is the epochmaking catalytic technology mentioned above. The root is the catalyst and catalytic material, and the main trunk is the reactor. The relationship between catalyst, reactor and process is shown in Fig. 1.1. The high efficiency of catalyst depends on the development of catalytic processes. The core of catalytic processes is the design and optimization of catalytic reactor.

Fig. 1.1 The relationship between catalyst, reactor and process

4

1 Introduction

Catalytic technology is widely used in petroleum refining, the production of basic chemicals (such as ammonia, methanol and sulfuric acid), fine and special chemicals, and pharmaceutics. It also plays an identically important role in the treatment of environmental pollutants, such as reduction of NOx and treatment of VOC. In the production of food and feed, the use of enzymes is essential in biological catalytic processes [2]. The oil refining industry mainly produces oil products, especially liquid transportation fuels. It is the basis of the development of the transportation industry, especially the automobile industry and the aviation industry. With the rapid development of national economy, the car ownership has been greatly increased, and the demand for transportation fuel has been rising sharply. The petrochemical industry produces three major synthetic products: plastics, fibers and resins, which are not only the basis of our daily life, but also the basis of downstream product industries such as coatings, textiles, building and decoration materials, and household appliances. In addition, the basic petrochemical and petroleum refining industries need to use large quantities and different types of oil refining catalysts and petrochemical catalyst. Other important basic chemical industry in corresponding catalytic processes, such as the production of three acids (sulfuric acid, nitric acid and hydrochloric acid) and fertilizers (particularly nitrogen ammonia synthesis industry), are highly dependent on solid catalyst and catalytic processes. Catalytic reactions are also widely involved in the field of environmental industry. Among them, it should be pointed out that automobile exhaust emissions have become the largest source of urban air pollutants. The air pollution produced by cars is a very public-concerned problem, in particular with the great increase of car ownership. It was reported that the number of cars in the world has increased from 400 million in the 1940s to 700 million in the early twenty-first century. It is now estimated to have more than 1 billion cars. Cars burn a lot of fuel and the exhaust from incomplete combustion contains many pollutants. This will seriously pollute the air if without being properly treated. Even if every car is fitted with a tailpipe purifier that uses a three-way catalyst for converting pollutants (i.e. carbon monoxide, hydrocarbons and nitrogen oxides), carbon dioxide emission is still huge. The automobile exhaust purifier is a catalytic reactor. The annual production and consumption of this reactor has far exceeded that of conventional petroleum refining catalysts. The environmental treatment problem differs from the general chemical industry, in which the concentration of pollutants is usually low, but the amount of treatment required is very large. Thus, the catalysts and reactors should meet some special requirement, e.g., the catalysts should not affect the output power and operation of automobile engines (very low pressure drop and large space velocity are required). At the same time, it is able to deal with the variability of the gas treated (including temperature and pollutant concentration), so the automotive exhaust gas purifier often uses structural catalyst and structural reactor. With the development of modern civilization, the emission of pollutants is increasing, and environmental problem becomes increasingly serious. At the same time, the arrival of the information age makes environmental problems more attractive to research. In order to solve the problem of environmental pollution more effectively, the concept of “green chemistry” was put forward in the 1990s, that is,

1.2 Catalytic Reaction Engineering

5

the concept of “sustainable development of chemistry”. The key to the twelve principles of green chemistry are atomic economy and catalytic technology. Catalytic technology is the key technology to achieve the goal of green chemistry, and it is also an essential and extremely important tool to achieve the social and economic goals. “Low-carbon economy” is the further deepening and materialization of green economy and “sustainable development”. Catalysis is also one of the indispensable tools and key technologies to achieve the goal of “low carbon economy”. By and large, about 90% of the energy, environmental and chemical production processes are related to catalytic reactions. Every breakthrough in the field of catalysis has greatly changed the way of human production and life. As resource and environmental challenges become more severe, the demand for diversity of chemical products is increasing. It is an important direction of chemical engineering and industrial catalytic technology innovation to achieve efficient utilization of resources through orientational transformation of chemical raw materials.

1.2

Catalytic Reaction Engineering

The research field of catalytic mechanism focuses on catalysts, involving catalyst preparation, active phase, activity, active site, conversion frequency, kinetics and potential poisons that may harm the catalyst, etc. The research field of chemical engineering, especially catalytic reaction engineering, is how to make the reactants effectively contact with the active sites of selected catalysts, how to provide or remove the heat of reactions, how reactors can be scaled up and how to ensure that the activity and selectivity of catalysts in large-scale equipment approximate to the ones obtained in the laboratory scale. The main research content of chemical reaction engineering is the so-called “three transfer and one reaction”. Here the “three transfer” refer to the momentum, mass, and heat transfer (collectively referred to as “transport phenomena” because of their similarity in mathematics) while “one reaction” refers to chemical reactions and chemical reactors [2]. Catalytic reactions are very important, not only in their wide existence in nature, but also in their wide applications. For example, large-scale energy industries like oil refining are developed on catalytic reactions. The petroleum refining industry is mainly concerned with hydrocarbon catalytic reactions. Based on the reaction mechanism of carbocation, this kind of catalytic reaction studies how hydrocarbons transform from reactants to products at the active center of acidic solid catalysts. These include the adsorption and activation modes of hydrocarbons, all steps of the elementary reactions of activated adsorbents (carbocation) converted into reaction products through surface reactions, and the desorption process of reaction products, etc. In general, catalytic reaction engineering is a part of chemical reaction engineering. However, in addition to the same general rules obeyed, it also has its own particularity—it relates to gas-solid two-phase catalytic reactions or gas-solid-liquid three-phase catalytic reactions. Similar to chemical reaction engineering, catalytic reaction engineering is based on material balance, reaction rate equation,

6

1 Introduction

stoichiometry of reactions, energy or heat balance. However, diffusion (in boundary layer and solid catalyst particles) and contact (hydrodynamics or hydraulics or pressure drop) both have their particular importance for catalytic reaction engineering. The design of catalytic reactors is based on these rules and their interactions. Catalytic reaction engineering includes three parts: catalytic reaction kinetics, transfer in multiphase catalytic processes and catalytic reactors. Among them, catalytic reactions and catalytic reactors are the core research fields to catalytic reaction engineering. Heterogeneous catalytic reactions normally occur on the surface of solid catalysts, and the reactants or products must be transferred between the fluid and the catalyst surface. Similarly, the heat required or released in reactions needs to be transferred between the fluid and the solid surface of the catalyst as well. There are two different levels of problems involved: the catalyst surface and catalyst particles. As for the problems of catalytic reaction engineering, a large number of catalyst particles are needed to obtain enough products. How these particles are stacked to form the catalyst bed in the reactor to achieve the desired output is a different problem from the catalytic reaction on a single catalyst particle. They are at different levels. Although the catalytic reaction engineering solves the problem of the higher level, it is closely connected with the problem of the lower level and cannot be separated. Therefore, these two levels of problems need to be studied and solved jointly in catalytic reaction engineering. The surface of catalyst (outer surface, inner surface of channel) is the site of catalytic reactions, and the reaction rate needs to be described by catalytic reaction kinetics. The problems of reaction transfer on a single catalyst particle and the catalytic reactor engineering need to be solved by catalytic reaction engineering. The main factors affecting the catalytic reaction process include concentration of reactant, reaction temperature, surface properties and structure properties of catalyst, reaction heat, and transfer process (including fluid properties such as viscosity and molecular properties), as well as the interaction between the transfers and the catalytic reaction, such as the coking, poisoning, sintering, loss, multi-steady state, oscillation and temperature runaway. As a methodology, catalytic reaction engineering is used to quantitatively describe the interactions between transport phenomena and catalytic reaction dynamics in reactors of different sizes. The methodology is used to establish quantitative mathematical models for different reactor performance measurements, such as reaction rate, conversion rate and selectivity, and develop quantitative relationships between reactor performance and operating conditions. At the same time, it can be employed to select the proper reactor and process, scale up process and correlate industrial device data accurately to optimize operating conditions in production. By determining the basic laws of catalytic processes, especially the mass, energy, momentum transfer and catalytic reaction kinetics in a reactor, and the quantitative relationship between their interactions, the optimal catalytic reactor and the corresponding process can be designed to meet the specific requirements of the catalyst. In essence, the catalytic reaction engineering can improve production efficiency, save energy consumption and reduce waste emission, so as to achieve the

1.3 Complex Gas-Solid Catalytic Reactions

7

highest economic benefit with the minimum energy consumption, i.e. minimizing the consumption of reaction material and energy while maximizing the output. The petroleum refining industry embodies this characteristic of catalytic reaction engineering, because even minor advances in catalytic reaction engineering can bring huge economic benefits to the oil refining industry with a large production capacity. For example, 1 percentage increase in oil product yield could increase the income by tens of billions of dollars or even more.

1.3 1.3.1

Complex Gas-Solid Catalytic Reactions Gas-Solid Catalytic Reaction

The rate of gas-solid two-phase catalytic reaction on solid catalyst is usually affected by diffusion, adsorption, surface reaction and desorption rates. The slowest step is called the rate-control step. As shown in Fig. 1.2, the gas-solid two-phase catalytic reaction process is divided into 7 steps: Step 1: The diffusion of reactant from the bulk fluid to the external surface of the catalyst particle is called external diffusion. The rate depends on the hydrodynamic characteristics of the system. Step 2: The reactant diffusion from the external surface of the catalyst particle to the immediate vicinity of the internal catalytic surface is called the internal diffusion. The rate depends on the porosity of the catalyst, the size and shape of the pores, and its surface characteristics.

Fig. 1.2 The main steps of gas-solid catalytic reaction process

8

1 Introduction

Step 3: The adsorption rate of reactants on the internal surface of catalyst particles depends on the interaction between reactants and catalyst surface. Step 4: The adsorbed reactant is undergoing the catalytic reaction on its surface and converts the intermediate transition state into the adsorbed product. Step 5: The desorption of the products from the internal surface of the catalyst, analogous to Step 3. Step 6: The product diffuses from the interior of the catalyst particle to the pore mouth at the external surface, analogous to Step 2. Step 7: Mass transfer of the products from the external catalyst surface to the bulk fluid, analogous to Step 1. Among them, Step 3 to Step 5 are the three elementary steps of catalyst surface chemical reaction: adsorption, surface reaction and desorption. The slowest elemental step is called the rate-control step, and its rate is almost equal to the total reaction rate. In the elementary step of surface chemical reaction, several unstable intermediate transitional species can be formed. These unstable intermediate species react quickly. Their concentrations are generally very low, and it can be assumed that the concentrations of these species are constant. In other words, their rate of formation is the same as their rate of consumption, which is so-called the quasi-steady state approximation. The steady-state hypothesis of the unstable species and the hypothesis of the rate-control step are very useful for obtaining the kinetic equation from the reaction mechanism. The concentration of the molecular species contained in the equation can be easily determined by using analytical methods. These two assumptions have very good generality and can be extended to the adsorption and diffusion steps.

1.3.2

Kinetics of Complex Reaction Systems

The catalytic reactions in industrial processes are normally complex, involving a variety of parallel reactions and series reactions, with a variety of desired products coexisting with numerous unwanted side products. Studies on the kinetics of such complex catalytic reactions are concerned with not only the conversion, but also the selectivity of intermediate desired products. Sometimes, the intermediates are side products of other reaction pathways at different conditions. In order to obtain the kinetics of complex reactions, one needs to rely on advanced analytical instruments and equipment to analyze all the reactants and products, and then obtain the variation curves of mass or concentrations of all the species with reaction time (contact time). Based on these data, reaction networks can be qualitatively derived. Related kinetic parameters are quantitatively determined by proper algorithm, and the reaction kinetics model is then verified. Of course, the agreement between the kinetics model and the experimental data does not mean that the reaction kinetics model is the only accurate mechanism model [3].

1.3 Complex Gas-Solid Catalytic Reactions

1.3.2.1

9

Parallel Complex Catalytic Reactions

Consider the multiple parallel catalytic reactions like

The reaction rate can be expressed by 0

RA ¼ ðk 1 þ k2 þ k3 þ . . .ÞCαA

ð1:1Þ

γ Q ¼ k1 CαA

0

ð1:2Þ

0

ð1:3Þ

γ S ¼ k2 C αA For the first order reaction, the rate law is 

dCA ¼ k1 CA þ k2 CA dt dCQ ¼ k1 CA dt dC s ¼ k2 CA dt

ð1:4Þ ð1:5Þ ð1:6Þ

Carrying out the integration of Eqs.1.4 and 1.5 gives

CQ  C Q0

C A ¼ C A0 eðk1 þk2 Þt h i k1 ¼ C A0 1  eðk1 þk2 Þt k1 þ k2

ð1:7Þ ð1:8Þ

Figure 1.3 shows all the possible results. The relative concentration of products can be obtained by comparing the rate equations: 

dC Q k 1 ¼ dC S k 2

ð1:9Þ

The above ratio implicitly includes time and output. After integration, we can get: C Q  C Q0 k1 ¼ C s  C s0 k2

ð1:10Þ

10

1 Introduction

Fig. 1.3 Concentration of parallel first-order reaction versus time curve [3]

1.3.2.2

Complex Series Catalytic Reactions

Consider the multiple series catalytic reactions like 1

2

A!Q!S The reaction rate can be expressed by 0

RA ¼ k1 CαA

ð1:11Þ 0

0

RQ ¼ k1 C αA  k2 CqQ 0

RS ¼ k2 CqQ

ð1:12Þ ð1:13Þ

For the first order reaction, carrying out the integration of Eq. 1.11 to Eq. 1.12 can get 

dC A ¼ k1 CA dt

ð1:14Þ

dC Q ¼ k1 CA  k2 CQ dt

ð1:15Þ

C A ¼ CA0 ek1 t

ð1:16Þ

and

1.3 Complex Gas-Solid Catalytic Reactions

11

Fig. 1.4 The relation of concentration to time for the first-order serial reaction with various k2/k1 ratios [3]

C Q ¼ C Q0 ek2 t þ

 k1 C A0  k1 t e  ek2 t , k1 6¼ k2 k 2  k1

ð1:17aÞ

C Q ¼ k1 CA0 ek1 t t, k1 ¼ k2

ð1:17bÞ

CS ¼ CA0 þ C Q0 þ C S0  C A  C Q

ð1:18Þ

Figure 1.4 shows the above results. If the experimental data for CA and CQ are given as a function of time, then the values of k1 and k2 can be found out through comparing the calculated curves presented in Fig. 1.4 and experimental data. The numerical optimization method can be used to quickly yield many possible solutions for k1 and k2 which are subsequently compared with the experimental data. By differentiating the equation with respect to CQ and letting it equal to 0, the maximum value on the Q curve can be obtained. The results are as follows: k1 tm ¼

    C Q0 1 k k 1þ 2 ln 2 1  k1 C A0 k1 ðk2 =k1 Þ  1

ð1:19Þ

In addition, the selectivity is obtained by comparing the rate equations. dCQ k2 CQ ¼ 1 þ dCA k1 CA The solution is:

ð1:20Þ

12

1 Introduction

C Q  CQ0 CQ0 ð1  xA Þk  1 1  xA 1  ð1  xA Þk1 ¼ þ xA C A0  C A CA0 k1 xA

ð1:21Þ

where, 

 CA k xA ¼ 1  ; k¼ 2 C A0 k1

1.3.3

ð1:22Þ

Analysis of Complex Reaction Systems

The basic types of complex reactions include series reactions, parallel reactions and their combinations. Parallel reactions are also called competing reactions, where reactants are consumed by two and more different reaction pathways to generate different products.

1.3.3.1

Maximization of the Desired Product in Parallel Reactions

Consider the parallel reaction like A⟶DðkD Þ A⟶UðkU Þ A desired product is D, and undesired product is U, so there exists a competition. Minimizing the formation of U and maximizing the formation of D are wanted, because the greater the amount of undesired products are formed, the greater amount of reactants are wasted and the greater is the cost of separating the undesired product U from the desired product D. Normally, a highly efficient reactor scheme could be achieved through the proper choice of operating conditions and the reactor selection based on systematic research and accurate modeling. The rate of the above competing reaction can be defined as follows: r D ¼ kD C αA1

ð1:23Þ

kU C αA2

ð1:24Þ

rU ¼ The consumption rate of A is

r A ¼ r D þ r U

ð1:25Þ

1.3 Complex Gas-Solid Catalytic Reactions

13

r A ¼ k D C αA1 þ kU C αA2

ð1:26Þ

The ratio of the two reactions is SDU ¼

r D k D α1 α2 ¼ C rU kU A

ð1:27Þ

For the reaction of higher orders, maximizing the formation of S could be also achieved: 1. If α1 > α2, the order of the reaction to the desired product is greater than the reaction order of the unwanted product, let α be a positive number, α ¼ α1α2, then: SDU ¼

rD kD α ¼ C rU kU A

ð1:28Þ

To make this ratio as large as possible, the reaction should be carried out in a manner that will keep the concentration of reactant A as high as possible. For the gas-phase reaction, do not use the inert gas and keep A at a high concentration at high pressures. For the liquid-phase reactions, the use of diluents should be kept to a minimum. Batch or plug flow reactors are preferred to use in such cases, because the concentration of reactant A at these reactors can start at a high value and decrease progressively during the course of the reaction. However, in an ideal continuous stirred tank reactor (CSTR), the concentration of reactant is always at its lowest value so that the CSTR should not be selected for those cases. 2. If α1 < α2, the order of reaction to the desired product is smaller than the reaction order of the undesired product, let α be a positive number, α ¼ α2α1. Then, SDU ¼

rD k ¼ D r U kU C αA

ð1:29Þ

To make this ratio as large as possible, the concentration of reactant A should be as low as possible. Low concentration of A can be achieved by addition of inert gas or diluent to the feed. A CSTR is better to use because it could keep the concentration of A at a low level. A recycle reactor could be used as well, because the reactants are diluted with the products. As the activation energy is unknown in both cases, it is not clear whether the high or low temperatures is favorable to the reaction. The sensitivity of the rate selectivity parameter to temperature can be determined from the ratio of the rate constants:

14

1 Introduction

 kD AD E  EU ¼ exp  D kU AU RT

ð1:30Þ

Where A is the frequency factor and E the activation energy. When ED > EU, the rate constant kD of the desired reaction increases faster with increasing the temperature than does the rate constant kU of the unwanted side reaction. Therefore, in order to obtain the maximum SDU, the reaction system should be operated at as high as possible temperature; When ED > EU, the rate constant kD of the desired reaction increases slower with increasing the temperature than does the rate constant kU of the side reaction. Thus, in order to maximize SDU, the system should be run at as low as possible temperature. But the temperature cannot be regulated so low that the sufficient conversion of the desired reaction cannot be achieved.

1.3.3.2

Maximizing the Desired Product in Multiple Series Reactions

It has been pointed out that the undesired products can be minimized by regulating operating conditions such as reactant concentration and by selecting an appropriate reactor. For multiple series reactions, the most important variable is reaction time, i.e. space time for a continuous flow reactor and real time for a batch reactor. To illustrate the importance of the factor time, consider the consecutive reaction is k1

k2

considered: A ! B ! C , where B is the desired product. If the first reaction is slow and the second is fast, B is extremely difficult to obtain. If the first reaction is fast and the second is slow, it is relatively easier to obtain a large yield of B. However, if the reaction is allowed to proceed in the reactor for a very long time, the desired product B could be converted to unwanted product C consequently. Therefore, the calculation of reaction time is more important for the series reactions than for the other types of reactions. The rate law for product B in a packed bed reactor (PBR) can be expressed by v0

dC B ¼ k1 CA  k2 CB dW

ð1:31Þ

Let τ0 ¼ W/ν0 ¼ ρcV/ν0 ¼ ρcτ, where ρc is the bulk density of the catalyst. The expansion of Eq. (1.31) with substituting for CA and then rearranging, we can get dC B þ k 2 C B ¼ k1 CA0 exp ðk1 τ0 Þ dτ0

ð1:32Þ

0

ðk 2 τ Þ Where d½CB exp ¼ k1 CA0 exp ½τ0 ðk2  k 1 Þ. dτ0 Employing the initial conditions, τ0 ¼ 0 and CB ¼ 0, one can obtain

CB ¼

k1 CA0 ½ exp ðk 1 τ0 Þ  exp ðk2 τ0 Þ , k1 6¼ k 2 ðk 2  k 1 Þ

ð1:33Þ

1.3 Complex Gas-Solid Catalytic Reactions

15

As the reactions proceed, the concentration of A decreases and concentration of B increases, while the concentration of B undergoes an increase initially, followed by a decrease. As the concentration of product B reaches the maximum at a point along the reactor length, we can differentiate Eq. 1.33 to find the optimum reactor length.

 dCB k1 C A0 k1 τ0 k2 τ0 ¼ 0 ¼ k e þ k e 1 2 dτ0 k2  k1 τ0opt ¼

1 k ln 1 k2  k1 k2

ð1:34Þ ð1:35Þ

The conversion rate of A (k1 6¼ k2), X¼

C A0  C A ¼ 1  exp ðk1 τ0 Þ C A0

ð1:36Þ

Then,   k1 =ðk1 k2 Þ k X opt ¼ 1  expðk 1 τ0opt Þ ¼ 1  exp  ln 1 k2  k1 =ðk1 k2 Þ k1 ¼1 k2

ð1:37Þ

Here yield is defined as the ratio of the amount of product B to the amount of feed A. The relationship function between the yield and conversion rate is shown in Fig. 1.5. The yield of product B can be expressed as CB/CA0. More method for tracking the progress of series reactions can be found elsewhere [4].

Fig. 1.5 Product yield – conversion curve [5]

16

1.4 1.4.1

1 Introduction

Design and Optimization of Complex Gas-Solid Catalytic Reactor Type of Catalytic Reactors

In general, catalytic reactors are specially designed on basis of catalysts and specific catalytic reactions, rather than catalysts and catalytic reactions are required to adapt the catalytic reactors. For example, the research and development of ammonia synthesis catalysts has spawned the development and improvement of fixed bed reactors with different heat transfer devices. The development of molecular sieve catalytic cracking catalyst boosted the emergence of riser reactor. Raney nickel catalyst drove the applications of slurry bed reactors. The third-generation reforming catalyst promotes the development of the moving-bed reactor. Therefore, it is necessary to deeply understand the characteristics of catalytic reactions and catalysts for the selection and design of catalytic reactors. After more than 200-year development, various types of reactors have been developed. They can be adapted to different types of catalytic reactions. Reactors can be classified on basis of involved phases, states of fluid flow, temperature distribution, motion of catalysts, reactor capacity or type of the dominant transfer. One typical classification of reactors is based on the motion of catalysts, giving e.g., fixed bed, moving bed, fluidized bed and slurry bed reactors. Their features are listed as follows [6]: 1. Fixed bed: catalyst particles are at rest or almost motionless and the surrounding reactant fluid flows through the void space among catalyst particles. The fluid can be continuous phase or discontinuous phase, such as gas, liquid or the mixture of gas and liquid. Accordingly, the related reactors can be called gas-solid, liquidsolid, gas-liquid-solid (such as trickled bed, submerged bed) fixed bed reactor. The general structure of a fixed bed reactor is shown in Fig. 1.6a. 2. Moving bed: the solid catalyst particles or particle reactants are continuously fed from the top to the reactor. The solid materials move downwards slowly and are discharged continuously out of the reactor from the bottom. The fluid flow upwards or downwards through the entire bed and the catalytic reactions then take place when the fluid contacts with solid materials. The structures of movingbed reactors are schematically drawn in Fig. 1.6b. 3. Fluidized bed: In a fluidized bed, particles are agitated by a fluid or external force field to manifest a fluid-like behavior. With the variation of operating conditions and material properties, the fluid and particles in a fluidized bed can be homogeneously or heterogeneously dispersed, as distinguished by Wilhelm and Kwauk [7] in terms of “particulate” and “aggregative” fluidization. Fluidized bed reactors offer many unique advantages such as large interfacial surface area between gas and particles, high gas-solid contact efficiency, excellent heat transfer, uniform

1.4 Design and Optimization of Complex Gas-Solid Catalytic Reactor

17

Fig. 1.6a The structure of fixed bed reactor and the flow of reactants

Fig. 1.6b The structure of moving-bed reactors and the flow of reactants

temperature and the ability to handle a large quantity of particulate materials of a wide range of physical properties. Figure 1.6c shows the typical structure of fluidized bed reactors. Fixed beds and fluidized beds are the most commonly used reactors for gas-solid catalytic reactions. In a tubular fixed bed reactor, the fluid reactants are continuously consumed as they flow down the length of the reactor. In modeling a tubular reactor,

18

1 Introduction Regenerated flue gas oil-gas

reactor Dilute phase region

spent catalyst

steam

feedstock

Dense phase region

regenerated catalyst

air

Fig. 1.6c The structure of fluidized bed reactors and the flow of reactants

the fluid is usually considered as in plug flow. That means the concentration or temperature varies continuously in the axial direction through the reactor, and almost no backmixing in the axial direction and no variation of concentration or temperature in the radial direction. The fluidized bed was originally developed for fluid catalytic cracking (FCC) to solve the problems of fast coking and deactivation of and circulation of catalysts. It has been developed into a relatively mature reactor technology and plays an irreplaceable role in many industrial processes, such as pulverized coal gasification, methanol-to-olefins process, hydrocarbon catalytic cracking process.

1.4.2

Reactor Design Method

Although the method of step-by-step reactor scale-up is reliable, it is very timeconsuming and costly. With the development of computation technology and the accumulation of abundant data, the method of reactor scale-up has gradually transformed. In addition, the expected method of reactor design completely dependent on the knowledge of catalytic reactions is still not available. Therefore, the reactor design can only adopt a compromised method, that is, a combination of the reactor modeling and experimental verification.

1.4 Design and Optimization of Complex Gas-Solid Catalytic Reactor

19

The first step in reactor design is to obtain enough data for a particular catalyst and related reactions. In particular, a suitable and reliable rate equation for the catalytic reactions should be established. This should be based on experimental data and can be obtained from one of the following methods: 1. Obtained from experiments over the laboratory reactor which is suitable for the study of catalytic reaction kinetics. The experiments aim to obtain the intrinsic chemical kinetic data, i.e. a series of concentration data VS time or contact time under the conditions free from the influence of external mass transfer limitation. Then the relation of rate and concentration data can be obtained by numerical differential method, and finally the appropriate rate equation is established by optimization method such as least square method. 2. Obtained from experiments over micro-scale and pilot-scale reactors. A great deal of experimental data can be collected by varying operating parameters such as the composition, temperature and pressure. These data are inevitably affected by the external mass transfer. Such influence should be separated from the chemical kinetic data on the particle scale, or, the effects of external mass transfer should be quantified. 3. Obtained and optimized from abundant data in different industrial catalytic reactors with varying operating conditions. Such rate equations can be used directly. The second step is to calculate reactant and product distribution in different types of catalytic reactors using the catalytic reaction rate equation and mass and energy balance equations. The calculation can help determine the mass or volume of catalysts needed to obtain the desired quantity of products and the heat removal or addition, thus providing a basis for the selection of reactor type, reactor size and catalyst inventory. The third step is involved with mechanical and civil engineering. In summary, the design of catalytic reactor includes the following main contents: (1) The reactor type and operation form (such as catalyst inventory, heat-exchange type, WHSV) are selected and determined, based on the calculations of different types of reactors using the combination of chemical reaction rate equation and material and energy balance equations; (2) The thermal stability and safety of the designed reactor are ascertained according to the nature of catalytic reaction, material and energy balances; (3) Selection of suitable internals, materials made for reactors and mechanical properties of reactor for satisfying the requirements of reactions and operating conditions. Although the complete design of a catalytic reactor must include the mechanical and architectural design, the selection of the structural materials, wall thickness and internals should ensure that the reactor can be operated safely over a wide range of operating conditions and resist the corrosion of reactants. The mechanical design of reactor is undertaken by mechanical engineers.

20

1 Introduction

1.4.3

Design and Optimization of Reactor in Complex Catalytic Reaction System

1.4.3.1

Fixed Bed Reactor and Moving-Bed Reactor

Industrial catalytic reaction is usually very complex and its reaction network is a combination of many cascade and parallel reaction steps. Each reaction step has its own thermodynamic/kinetic characteristics. The regulation of specific reaction pathways for maximizing the desired reactions and, at the same time, minimization of the undesired side reactions, could be achieved through creating different reaction environments for specific reaction pathways, and realizing reasonable cooperation of different cascade reaction steps. However, a single reactor or a single reaction zone is difficult to provide a suitable reaction environment for a specific reaction pathway in a complex catalytic reaction network, and it is also hard to effectively utilize the catalyst. For complex catalytic reactions with low coking rate and heat effects, the fixed bed or moving bed reactors are connected in series/parallel to regulate some specific reaction steps. For examples, four to five fixed bed reactors are used together in hydrotreating process of residual oil [8]; three fixed bed reactors in series are employed in the semi-regenerative reforming process; and four moving bed reactors in series/parallel are utilized in the continuous reforming process [9]. The hydrotreating process of residual oil mainly includes hydrodesulfurization, denitrification and demetallization as well as the conversion of carbon residue precursor and hydrocracking reactions. These reactions have the following characteristics: 1. Hydrodesulfurization (HDS) reaction The various types of hydrolytic sulfide reactions are exothermic, and the total reaction heat is about 2300 kJ per volumetric consumption of H2 consumption (Nm3). Hydrodesulfurization reaction is the main reaction in the hydrogenation process of residual oil and contributes the most heat in the total reactions. 2. Hydrogenation demetallization (HDM) reaction Nickel and vanadium in residuals are mostly found in resin and asphaltene. Therefore, the hydrodemetalization reaction of residual oil is often closely related to the asphaltene pyrolysis. The nickel and vanadium are deposited on the catalyst in the form of metal sulfide, respectively represented by Ni3S2 and V3S4. Vanadium is more easily removed than nickel under the identical reaction conditions, because the vanadium in porphyrins is bound strongly to oxygen atoms which has a strong bond to the surface of the catalyst, making it easier to remove vanadium. 3. Hydrodenitrification (HDN) reaction About 70–90% of nitrogen of crude oil exists in residue, and about 80% of nitrogen in residue is found in resin and asphaltene. It is reported that most nitrogen in resin and asphaltene exists in the form of ring structure (heterocyclic rings of five-

1.4 Design and Optimization of Complex Gas-Solid Catalytic Reactor

21

membered cyclopyrrole or six-membered cyclopyridines). The nitrogen compounds in the feedstock are hydrogenated to generate NH3 and hydrocarbons. NH3 is then removed from the product and hydrocarbons remain in the product. Generally, the hydrogenation and denitrification of heterocyclic nitride starts from the saturation of aromatic and heterocyclic hydrogenation. Then one of the C-N bonds in the ring is broken (i.e., hydrolyzed), and finally the intermediate amines or anilines are formed and C-N is hydrolyzed. Nitrogen is removed as the form of NH3. Therefore, the use of catalyst with good aromatic hydrogenation saturation and high hydrogen partial pressure is favorable to the hydrogenation denitrification reaction. The hydrogenation denitrification reaction is also exothermic, and the reaction heat is about 2720 kJ per volumetric consumption of H2 (Nm3). However, the removal rate of nitrogen is only between 50% and 60% due to the low nitrogen content in the crude oil, thus it does not contribute much to the total reaction heat. 4. Hydrogenation deactivation reaction (HDCR) Hydrogenation is also an important reaction in the hydrogenation process of residue oil. The reduction rate of residual carbon is an important index. Different from impurities such as S, N and metals, the amount of residual oil carbon represents the coke generation tendency of the components with high boiling point such as polycyclic aromatic hydrocarbons, colloid and asphaltene. 5. Hydrocracking reaction Hydrocracking reaction is to convert the fractions in crude oil with the boiling point of over 538  C to the light fractions with the boiling point of below 538  C. The degree of conversion depends on the production scheme of residue hydrotreating technology. For the general residual oil hydrotreating process, the conversion degree (named light conversion rate) is less than 50%. Hydrocracking reaction plays an important role in generation of light oil products. The residue hydrotreating process is based on the characteristics of desulfurization, denitrification, metal removal and carbon residue conversion. The reaction system can be divided into three stages. The first stage is used for hydrogenation and demetallization, and the operating temperature is usually 20–30  C higher than the second stage. The second stage is the transition stage (HDM/HDS), and the third stage is the deep hydrodesulfurization and refining. The process flow scheme is shown in Fig. 1.7. All the protective reactors and main reactors of the reaction system employ the fixed bed reactors with an equal diameter. This is to facilitate the loading and unloading of catalysts and simplify the layout of the internal components in the reactor. Catalytic reforming mainly involves cycloalkane dehydrogenation and alkane dehydrogenation reactions. When the number of carbon atoms is constant, the tighter the molecular structure is, the higher the octane number will be. Therefore, the reforming process aims to convert straight-chain hydrocarbons into branched isomers, cycloalkanes and aromatics. The reaction pathway is [2]:

22

1 Introduction

Fig. 1.7 Process flow scheme and reactor layout of residual oil hydrotreating process [10]

Linear hydrocarbon ! ðk 1 Þ Naphthenic ! ðk 2 Þ Aromatics The rate constant, k1, in the first step is smaller than that, k2, in the second step, and both steps are strongly endothermic. And the allowable operating temperature range is very small: side reactions will occur at more than 530  C, and almost no reaction will happen when the temperature is below 430  C. Therefore, multiple fixed bed or moving bed reactors can be used for intermediate heating to meet the actual needs of naphtha reforming catalytic reaction. After naphtha feedstock entering the first reactor, the fast reactions, such as the dehydrogenation of 6-naphthene, are carried out first. These endothermic reactions cause the reactor temperature to drop sharply. The bottom of the reactor is at a lower temperature, which affects the reaction rate and prevents the catalyst from fully functioning. Therefore, the volume of the first reactor should not be too large and the catalyst should not be over-loaded. At the same time, a larger furnace should be set up after the first reactor to reheat the reaction vapor to the desired temperature. After being heated, the reaction vapor enters a larger second reactor, and the pentacycloalkane undergoes dehydrogenation and isomerization reactions. Meanwhile, the temperature will also drop, but the decline range will be narrowed. Next, when the reaction vapor enters the third and fourth reactors, the reactions which easily occur are almost completed. Slower reactions, such as the cyclization and dehydrogenation of alkanes, require larger space. At the same time, endothermic dehydrogenation reaction decreases, exothermic hydrocracking reaction increases gradually, and the reactor temperature drop is less significant. Therefore, the furnace load decreases gradually while the reactor volume increases in each reforming reaction from front to back. In addition to the heat load of the first reformer (feed furnace) which relates to the heat load of the feed heat exchanger, the heat load of the

1.4 Design and Optimization of Complex Gas-Solid Catalytic Reactor

23

Fig. 1.8 Reactor layout of semi-regenerative catalytic reforming process

last three reformers (middle furnace) is determined by the reaction heat of each reaction. The loading ratio of the catalyst from the front to the back of the reactor is generally 15%, 25% and 60% while the four reactors are generally 10%, 15%, 25% and 50%, respectively. The catalytic reforming process is operated at the following conditions: reaction pressure is 0.35–1.50 MPa, reaction temperature 480–530  C, hydrogen molar ratio 2–8 and volume velocity is between 1 and 3 h1. The adiabatic reactor is used in this process with a great deal of heat being absorbed during the reaction. In order to maintain sufficient reaction temperature, 3 or 4 reactors are usually used together and the feedstock is heated in the furnace before entering each reactor. The number of reactors for catalytic reforming reaction is closely related to feed composition and reaction requirements such as the octane number and reaction heat. The increase of the number of reactors results in small variation in the temperature in each reactor and thus is favorable to the catalytic reforming reaction. However, in the other hand, the increase of reactors requires bigger investment, possibly being unreasonable from the economic point of view. In practice, if the octane number (RON) and reaction heat are required to be below 98 and 1000 kJ/kg, respectively, arrangement of three reactors could be a good scheme, whereas four reactors are preferred. Semiregenerative catalytic reforming process generally adopts three fixed bed reactors in series, as shown in Fig. 1.8, but the continuous reforming process prefers to use four moving bed reactors in series, as shown in Fig. 1.9. Figure 1.10 presents the fluid flow in the reactor of catalytic reforming process. The reactants flow radially inward through the catalysts encased in a metal mesh. The catalysts move slowly down the length of the reactor in a discontinuous rather than continuous manner. Since the reaction is endothermic, the equilibrium conversion rate increases with temperature. The balance between temperature and conversion should be paid attention in design.

24

1 Introduction

Fig. 1.9 Reactor layout for continuous reforming process

Fig. 1.10 Schematic diagram of fluid flow in a moving bed reactor with intersegment heating

1.4.3.2

Fluidized Bed

Gas-solid fluidized bed reactors are widely used in a variety of chemical and physical processing applications, such as fluid catalytic cracking (FCC), coal/biomass pyrolysis and gasification, olefin polymerization, ore calcination and granulation. These numerous applications of fluidized-bed technology can be classified into four

1.4 Design and Optimization of Complex Gas-Solid Catalytic Reactor

25

categories based on the types of reactions involved [11]: (1) Gas catalytic reaction, where both reactants and products are in gas phase, but the reaction takes place over the surface of catalyst particles. FCC process and recently commercialized MTO (methanol to olefins) process belong to this category; (2) Gas-solid reaction, where both gas and solids are the reactants and products, which contains either only gas phase or a combination of both gas and solids. Coal combustion and gasification are the typical examples; (3) Gas-phase reaction with solids as heat carriers where solids provide the heat for the reaction or carry away the heat produced by the reactions, and both reactants and products are in gas phase; (4) Physical process with no chemical reactions, such as fluidized-bed drying. The gas-solid fluidized bed reactor can be operated in different flow regimes according to the specific application. For a specified solids inventory, a range of flow regimes could be realized with increase of gas velocity encompassing homogeneous expansion, bubbling fluidization, turbulent fluidization, slugging (if bed diameter is comparable to bubble size), fast fluidization, dense suspension upflow and dilute pneumatic conveying. Each fluidization regime has characteristic flow structures, such as gas pockets or voids which are frequently referred to as bubbles in bubbling fluidization, or particle swarms and streamers which are commonly called clusters in fast fluidization. Accordingly, the fluidized bed reactors could be generally classified into bubbling fluidized bed, turbulent fluidized bed, fast fluidized bed or riser, and others. Although different types of fluidized beds show evident difference in hydrodynamics, they generally offer a number of advantages over alternative designs, such as large interfacial surface area between gas and particles, fast heat transfer, relatively even temperature distribution and the ability to handle a large quantity of particulate materials of a wide range of physical properties. This is why a wide of industrial applications employ the fluidization technology [12, 13]. However, in order to satisfy the more stringent environmental provision and diversified requirements, the research on the fluidized bed reactor and reaction intensification technology is undergoing continuous development. For example, in order to keep the advantages of fluidization while reduce the solid backmixing for achieving ideal residence time distribution and creating favorable chemical and physical environment, various complex fluidized bed reactors emerge such as multi-layer fluidized bed, multi-chamber fluidized bed, and a combination of several fluidized beds or multi-fluidized beds [14]. Multi-layer fluidized bed consists of a number of fluidized beds connected in series along the axial direction, and the beds are separated by sieve plates. Particles enter the reactor from the upper fluidized bed and move down to the lower fluidized bed through overflow pipes or sieve plates, while gases enter the reactor from the bottom and exit from the top (See Fig. 1.11). The remarkable advantage of the multilayer fluidized bed is that it can establish the desired temperature and concentration gradient in the axial direction, effectively inhibit the growth of bubbles and improve the mass and heat transfer [15]. Compared with single-layer fluidized bed, multi-layer fluidized bed not only maintains the inherent advantages of fluidized bed, but also decreases the backmixing of solid particles through controlling the growth of bubbles, thus resulting in improvement of the residence time distribution and

26

1 Introduction

Fig. 1.11 Schematic diagram of multi-layer fluidized bed structure

intensification of the desired chemical reaction and physical processing. Therefore, multilayer fluidized bed has been developed rapidly and received wide application [14]. Multilayer fluidized bed has not only been used in physical processing of gas phase and solid phase such as drying and adsorption, but also in chemical reaction processes such as catalytic cracking to produce alkene, naphthalene oxidation to produce phthalic anhydride and roasting [16]. Multi-chamber fluidized bed is composed of several fluidized beds connected in series along the radial direction. The bed section is generally rectangular, and the fluidized bed is divided into multiple chambers through baffles. Particles are fed to

1.4 Design and Optimization of Complex Gas-Solid Catalytic Reactor

27

Fig. 1.12 Schematic diagram of multi-chamber fluidized bed structure

the reactor from one end and discharged from the other end. The gas enters the reactor from the bottom and exits from the top. Gas and particle flows form a crossflow pattern, as shown in Fig. 1.12. The main feature of multi-chamber fluidized bed is compact arrangement, being favorable to reduce backmixing of particles and establish the temperature and concentration gradient in the radial direction. Multichamber fluidized bed is analogous to multi-layer fluidized bed, as they are both separated into several zones based on the physical structure. The main difference is that a multi-chamber fluidized bed establishes multiple zones laterally, while a multilayer fluidized bed separates multiple zones axially. A typical application of multichamber fluidized bed is a horizontal multi-chamber, continuous fluidized bed dryer, where a rectangular gas distributor is installed and the region below the distributor is divided into several gas distribution chambers for achieving even gas distribution. The residence time of feedstock is controlled by the height of the outlet weir. Multi-fluidized bed is a combined reactor system consisting of two or more single fluidized beds in series or parallel. In this system, gas and solid particles move between different fluidized beds, achieving particle flows in series and gas flow in parallel flow or other forms of flow [17]. In addition, the gas can be separately fed to each fluidized bed to create different reaction conditions such as reaction temperature, pressure and gas composition. Thus, different types of catalytic reactions can be achieved. Fluidized catalytic cracking (FCC) was the first process to adopt the multi-reactor fluidized bed reactor. FCC reactor employs a column riser operated in the dilute transport while the regenerator in bubbling fluidized bed, turbulent bed, fast bed or

28

1 Introduction

Fig. 1.13 Process flow scheme of FCC regeneration system [18, 19]

their combination. The oil vapor undergoes catalytic cracking reactions in the riser, and the catalyst particles continuously circulate between the reactor and the regenerator. The process flow scheme of the device is shown in Fig. 1.13 [18, 19]. There are also many application examples of a combination of multiple fluidized bed reactors in the field of biomass gasification [12]. For instance, as shown in Fig. 1.14, double fluidized bed gasifier process has the first and the second fluidized bed reactors (Reactor I and Reactor II). In Reactor I, the biomass pyrolysis occurs and the carbon particles produced are fed into Reactor II for combustion. The combustion makes the temperature of materials in Reactor II increase, and the high-temperature materials return to Reactor I through the dipleg, providing the heat source for the reactions in Reactor I. In this gasification process, the combustion furnace employs the bubbling fluidized bed for fully coke burning and high carbon conversion, while the pyrolysis bed employs the turbulent or fast fluidized bed. The circulation of heat carrier particles between two beds realizes the heat balance of the whole system. The chemical looping combustion (CLC) process can be deployed for direct combustion of the fuel through the combination of two fluidized bed reactors for achieving automatic separation and purification of CO2 without the use of the energy-intensive, cryogenic process or membrane technology and free from the generation of NOX [20–22]. Figure 1.15 [23] describes the fuel gas and solid flow between the two fluidized bed reactors. In a fuel bubbling fluidized reactor, the solid

1.4 Design and Optimization of Complex Gas-Solid Catalytic Reactor

29

Fig. 1.14 Process flow scheme of double fluidized bed gasifier

Fig. 1.15 Process flow scheme of chemical looping combustion in double fluidized bed combination [23]. (1-riser; 2-hopper; 3-bubbling bed)

(metal oxide) brings the oxygen to the hydrocarbon fuel gas to produce CO2 and H2O, and the metal oxides are reduced to low-valent metal oxides or metal monomers, which can be sequentially regenerated in the air reactor (riser) and a great deal of heat is accordingly released. In this process, the air does not react directly with the

30

1 Introduction

fuel gas, so that no NOx is formed and the risk of explosion caused by direct mixing of fuel gas and oxygen is avoided. The olefin polymerization process also adopts the scheme of a combination of reactors, which can be a combination of two bubbling fluidized beds, or a fluidized bed and a ring tube, or a fluidized bed and a stirred tank, or others. For example, the ethylene polymerization process takes the form of a fluidized bed reactor with four reaction zones. Two of the reaction zones are bubbling fluidized beds and the other two are fast fluidized beds. The velocity of polymer particles increases significantly after they move from the first bubbling fluidized bed to the fast fluidized bed. The particles are separated by cyclone and subsequently return to the second and the first bubbling fluidized beds through diplegs in succession [24]. Multi-layer fluidized bed, multi-chamber fluidized bed, and multi-fluidized bed reactors could establish temperature and/or concentration gradients within the bed, which is helpful to create multiple zones and/or different process states for effectively meeting the requirements of some special chemical processes. However, the following common disadvantages are found in all these reactors: 1. Each fluidized bed holds a relatively dense fluidization region and freeboard region. However, the presence of multiple freeboard regions wastes the reactor volume and thus results in the low utilization rate of the equipment. 2. Building a reactor with such a relatively complex structure costs much higher, compared to a reactor with simple structure at the same production scale. On the other hand, more complex the structure is, more difficult the operation and the maintenance are, thus restricting its further application. 3. Only suitable for the system with totally different types of reactions, such as the combination of gasification and oxidation, reaction and regeneration. It is difficult to achieve the temperature and/or concentration difference for satisfying different reaction pathways in a whole complex gas-solid catalytic reaction. In some cases, complex chemical process systems, especially the complex gas-solid catalytic reaction systems, require a single fluidized bed reactor possessing different flow states. The coexistence of multiple flow patterns could help achieve temperature gradient and concentration gradient in a single reactor for meeting different requirements of multiple main reactions in a complex gas-solid catalytic reaction process. Thus, such reactor design improves the utilization rate of fluidized bed equipment and reduce equipment investment, compared with the multi-layer fluidized bed, multi-chamber fluidized bed, and multi-fluidized bed. However, systematic research on this type of reactor with multiple temperature zones and/or multiple flow states [24] is rarely reported. Therefore, how to effectively realize the concentration and temperature gradient in a single fluidized bed reactor is of great significance to industrial application and theoretical modeling, and is expected to become an important idea in the future development of fluidized bed reactors. The flow structure in a gas-solid fluidized bed significantly affects the heat transfer, mass transfer and chemical reactions therein. Thus, the key in the design and scale-up of fluidized bed reactor is to accurately understand the flow structure and its underlying mechanism. The flow patterns and flow regime transition are

1.4 Design and Optimization of Complex Gas-Solid Catalytic Reactor

31

Fig. 1.16 Three mechanisms of particle transfer: suspension, collision and friction

closely related to the nature of particles and fluidized media as well as reactor configuration. For examples, the slugging normally occurs at a reactor with small diameter; fluidization of Geldart A particles could undergo homogeneous fluidization when the gas velocity, Ug, just exceeds the minimum fluidization velocity, Umf, while for Geldart B particles, the flow state directly evolves into the bubbling fluidization without experience of the homogeneous fluidization. Those different flow patterns may be accompanied with big difference in the particle movement, transfer mechanism and gas-solid coupling mechanism. As shown in Fig. 1.16, when the particle concentration is very low, the mean free path of particles could be larger than the characteristic length of flow field, thus few collisions between particles take place. In such a case, the flow dominates the particle movement and the particles are suspended relatively uniformly in the fluid. When the particle concentration increases, the mean free path of particles is reduced and collisions between particles ensue. The movement of particles are controlled by the instantaneous collisions between particles and the drag force exerted by the surrounding fluid during the collision interval. The compromise of the particle-related forces (including gravity, particle impact and etc.) and the drag force by the fluid results in the formation of dynamic cluster structures. With further increase of the particle concentration, collisions occur much easily and the suspension process is reduced greatly, leading to formation of more evident heterogeneous structures. When particles are increased to the closely packing state, both the instantaneous collision between particles and the suspension process are gradually weakened. The long-duration contact gradually replaces the instantaneous collision and the particle-particle friction starts to play a dominant role. Hence, the non-equilibrium transfer between particles is mainly realized through three mechanisms: the kinetic/suspension transport dominated by

32

1 Introduction

the drag force, the collisional transport induced by instantaneous contacts and the frictional transport in a closely packing state [14]. The suspension, collision and friction transfer, respectively, play a dominant role in different particle concentration. From a macroscopic perspective, fluidization can be considered as a system where the continuous fluid and discrete particles interact with each other. From a microscopic perspective, the continuous fluid is composed of a huge number of discrete molecules, so the fluidization can be considered as a system where discrete molecules and discrete solid particles interact with each other. The interaction between the fluid and particles transforms from a stress integrated and averaged over the fluid-particle interface, to a force summed over all the collisions and frictions between molecules and particles. As the number of fluid molecules is far above the order of 1023, tracking the motion of each molecules and solid particles is unfeasible for present computational capability. The macroscopic continuous fluid may be discretized into a certain number of “pseudo-particles”, each representing a group of molecules with the analogous hydrodynamic characteristics, thus greatly reducing the computational cost. However, too few pseudoparticles may lead to the much loss of movement information of individual molecules and too many pseudo-particles increase the calculation burden. Therefore, determination of the appropriate number of pseudo-particles becomes a difficult issue for such coarse-grained simulations. For an industrial-scale fluidized bed reactor, the diameter could be in the order of several meters or over 10 meters while the size of catalyst particle is only about tens of microns and the particle density is hundreds of times the gas density. Due to the complexity of flow structures in gas-solid fluidized bed reactors over such a big gap of scales, it is presently still difficult to effectively describe and control the hydrodynamics and chemical processes. It is almost impossible to arrange multiple fluidized beds in series/parallel to accommodate complex catalytic reactions like the scheme of combination of arrangement of multiple fixed beds or moving beds in series/parallel for satisfying some catalytic reactions with low coke generation and reaction heat. There are three major problems as follows: 1. The transition state is hard to continue Taking catalytic cracking reactions as an example, macromolecular alkane, as the reactant, is protonized at the acidic position of catalyst B to produce non-classical carbonium ions. This carbonium ion is broken in transition state. For example, there are three pathways of 3-methylpentane (3 – MP) breaking on acid catalyst [25], i.e., Pathway 1: non-classical carbonium breaks into methane and a classical carbenium; Pathway 2: non-classical carbonium breaks into ethane and a classical carbenium; Pathway 3: non-classical carbonium breaks into hydrogen and a classical carbenium. Macromolecular alkane forms non-classical carbonium on the catalyst surface as transition state, and then converts into classical carbenium. The conversion process is accompanied with the formation of small alkane molecules and hydrogen as by-products. Therefore, price needs to be paid by large alkane molecules to initially form the transition states on the catalyst surface. This means that the transition state of alkane on catalyst surface should be reduced as much as possible. It is better that

1.4 Design and Optimization of Complex Gas-Solid Catalytic Reactor

33

Fig. 1.17 Three fluidized bed reactors arranged in series

the small carbenium is able to directly convert the large molecule alkane into carbenium through the hydride ion transfer. In the presence of solid acid catalyst, the carbenium Rþ 2 will grab the hydride ion from alkane molecules to trigger the transfer of hydride ion. When Rþ 2 transferring into a new alkane, the large molecule alkane molecule will generate a new Rþ 1 , so that the whole catalytic cracking reaction continues. The equation of the reaction is:  þ  R1 H þ Rþ 2 Z ⟶R1 Z þ R2 H

Through the above reaction path, alkane molecules generate the classical carbenium directly, without producing hydrogen and small alkane molecules. That is to say, the intermediate transition state formed on the surface of the catalyst should not be forcibly terminated during the reaction. However, simply combining multiple fluidized bed reactors in series/parallel can only force the reaction depth of the classical carbenium to be terminated. This carbocation will be triggered in the next reactor, which results in unnecessary by-products. 2. Complexity for particle transport and difficulty for a long-time operation The transport of catalyst particles from one dense fluidized bed to another requires an equipment such as the catalyst hopper, pipeline and slide valve. If multiple fluidized bed reactors are connected in series/in parallel, multiple sets of catalyst hoppers, pipelines, and slide valves need to match with, leading to complex transport of catalyst particles. The flow sheet of such an arrangement is shown in Fig. 1.17. The transportation of catalyst is carried out in parallel, from a single regenerator to three reactors. On the contrary, the transportation of gas reactants is conducted in series, flowing from reactor 1, reactor 2 to the reactor 3. These three reactors may have different temperatures and catalyst densities for meeting the requirements of process parameters for the complex catalytic reactions. However,

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1 Introduction

if the catalyst transportation of one reactor is not quite smooth, it will be hard to continue the later catalyst transportation in other reactors and meanwhile increase the difficulty and instability in operation of the units. For a fluidized bed with high gas velocity, the particles tend to form clusters which a range from several particles to an entire reactor section. If multiple fluidized bed reactors of high gas velocity are simply connected in series/parallel, the catalyst buffer tanks must be placed between two reactors. The catalyst transport should be switched between the high-velocity state and low-velocity state, which makes the process more difficult to control. 3. High pressure drop and operation cost In order to keep catalysts in a fluidized state, the fluidized bed must be operated with certain pressure drop. The pressure drop of a riser reactor is about between 50 and 70 kPa and of a dense fluidized bed reactor is about 80 kPa. If three fluidized beds are connected in series, the total pressure drop is up to 0.2 MPa. Accordingly, additional power should be provided, resulting in a significant increase in operation cost. The flow structure of a fluidized bed is so complex that simple series/parallel combinations are almost impossible to meet the demands of complex catalytic reactions. Therefore, an approach to regulate complex catalytic reactions in a single fluidized bed reactor with variable diameter is proposed. The change of bed diameter helps to realize the co-existence of multiple temperature zones and/or multiple flow patterns in one reactor. A single fluidized bed with multiple temperature zones and/or multiple flow patterns breaks the limitation of relatively uniform distribution of temperature or concentration in a conventional fluidized bed. This novel fluidized bed reactor has not been studied systematically in open publications. The single fluidized bed reactor possessing multiple temperature zones and/or multiple flow states has many advantages over the simple combination of multiple reactors, such as high equipment utilization rate, easier operation and revamp, thus it is expected to further improve the selectivity and quality of desired products in such as catalytic cracking, coal gasification, drying and granulation processes. Therefore, we aim to establish a universal reactor platform for complex catalytic reactions with creating multiple operation patterns in a single fluidized bed. To this end, analyzing the common problems in different complex gas-solid catalytic reactions and understanding the hydrodynamic behavior, stability and interaction between gas-solid phase and chemical reaction process in this novel fluidized bed reactor is of great importance to the design, operation optimization and scale-up of this reactor platform.

1.5 Structure of DTFB Reactor

1.5

35

Structure of DTFB Reactor

1.5.1

Complex Catalytic Reactions

The study on the reaction of heavy hydrocarbon on the solid acid catalyst indicated that there are evident differences in reaction rates, diffusion rates, thermodynamics and kinetics between hydrocarbon cascade/parallel reactions. The highly selective catalytic reactions are difficult to achieve in a fluidized bed with a single reaction zone, facing a conflict between conversion rate and selectivity.

1.5.1.1

Monomolecular and Bimolecular Reactions

The reaction of hydrocarbons on the surface of solid acid catalyst follows the reaction mechanism of carbocation, which can be divided into initial stage, propagation stage and termination stage. In the initial stage, alkane molecules are adsorbed on the catalyst to form the intermediate transition state of non-classical carbonium ions, which are broken into classical carbenium ions and small molecules of alkane and hydrogen. Then the propagation stage takes place. The types of reactions are involved in the propagation stage [26–29], as shown in Fig. 1.18 [26]. It can be seen from Fig. 1.18 that the carbenium ions can undergo isomerization and β-scission reactions according to the monomolecular mechanism. If following the bimolecular mechanism, disproportionation and hydrogen transfer reaction can take place. Hydrocarbon cracking reaction is endothermic while the light olefins formation through bimolecular hydrogen transfer and isomerization reaction are

Fig. 1.18 Chain reaction network catalyzed by acid based on carbocation [26]

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1 Introduction

Table 1.1 Effect of reaction time on monomolecular and bimolecular reactions Reaction type Reaction time, s Hydrogen transfer index (volume ratio) ∑C-4 alkane/∑C-4 olefin iso-butane/iso-butene Gasoline composition (volume fraction), % Olefin Aromatic

Monomolecular 1 0.49 1.21 58.0 11.4

Bimolecular 6 0.98 2.89 33.1 12.7

exothermic. The former reaction prefers higher reaction temperature while the latter prefers a lower reaction temperature. How to determine the reaction parameters favorable for both reactions is a tough task. In addition, there are several ways for conversion of carbenium ions. How to achieve monomolecular or bimolecular oriented conversion? Sample analysis was conducted at different locations of a riser fluidized reactor. Table 1.1 lists the related results. Within 1 s, monomolecular cracking reaction plays the dominant role, then the bimolecular reaction ensues mostly. Experimental studies demonstrated that monomolecular and bimolecular reactions can be an oriented conversion through introducing several different reaction zones [30].

1.5.1.2

Reaction, Adsorption and Diffusion

In pursuit of desired conversion and selectivity, the size of hydrocarbon molecules in VGO and the catalyst pores should match each other. The diameter of macromolecular of residual oil is about 1.5–15 nm, while the diameter of pores in molecular sieve is about 0.74 nm, even the diameter of the supercage is only 1.2 nm. According to the theory of configurational diffusion, the diameter of the molecular sieve channel should be 6–10 times the diameter of the feedstock molecular, which could eliminate the effect of configurational diffusion. In addition, the resin and asphaltene in the residue are first absorbed on the catalyst surface, which block or decrease the catalyst channel, thus making the diffusion of reactant macromolecular to the supercage in the molecular sieve become difficult. As a result, the diffusion affects the reaction seriously, and the desired selectivity of the desired product and conversion cannot be achieved simultaneously. The polycyclic aromatic hydrocarbons (PAHs) and other macromolecules in the residue are adsorbed on the catalyst surface and their side chains on PAHs are cracked. Then the coke could be formed due to the condensation reaction of PAHs, particularly on the REY zeolite catalyst with high acid density or under the condition of low reaction temperature and high catalyst activity, more easily occurs the formation of coke. In order to make more side chains on PAHs cracking and avoid coke formation due to the condensation reaction simultaneously, it is expected to develop the USY zeolite catalysts with low acid density or new reactor systems to reduce the surface adsorption capacity of catalysts and make the

1.5 Structure of DTFB Reactor

37

Table 1.2 Changes in feedstock composition after 1 s reaction Composition Alkane Cycloparaffin Monocyclic aromatic Polycyclic aromatic Resins

Feedstock (%) 19.5 36.6 10.4 9.9 23.6

Heavy oil after 1 s reaction (%) 30.3 41.1 11.6 12.2 4.8

macromolecules repeatedly expose to the catalyst surface. Even if PAHs and other macromolecules in residue lie flat on the catalyst surface, the adsorption of PAHs nuclei on the catalyst surface is still not strong enough. Or, although the PAHs nuclei has been adsorbed on the catalyst surface, the desorption can easily take place, then the PAHs could then stand on the catalyst surface, and the side chains are further broken. C5 ~ C24 (gasoline and diesel distillate) molecules are difficult to diffuse out of micropores of the molecular sieve, and are prone to decompose into coke and dry gas by the “excessive cracking” before escape. Developing new reactor systems to provide a more suitable reaction environment will make full use of molecular sieve supercage structure, letting C5 ~ C24 molecules react in molecular sieve supercage and avoiding the “excessive cracking”. The composition changes of residue oil feedstock after 1 s reaction on catalyst are shown in Table 1.2. The resin content in the residue decreases significantly after 1 s reaction. This indicates that the resin is first adsorbed on the catalyst surface, which blocks the catalyst channel. And the transfer resistance of macromolecular reactants to the zeolite supercage increases, resulting in a decrease in the utilization rate of the zeolite supercage. The cracking of reactants and the selectivity to desired products are thus greatly affected, leading to a pronounced conflict between the conversion rate and product selectivity. How to achieve the effective conversion of saturated hydrocarbon, monocyclic aromatic hydrocarbon and polycyclic aromatic hydrocarbon in residue oil after 1 s reaction, especially the effective conversion of monocyclic aromatic hydrocarbons and polycyclic aromatic hydrocarbons, without developing the new catalysts? We resort to develop a new highly efficient reactor system where the the side chains of saturated hydrocarbons, monocyclic aromatic hydrocarbons and polycyclic aromatic hydrocarbons can be broken on the catalyst surface to form small molecular products such as gasoline and LPG, and the condensation reactions of the aromatic hydrocarbons, especially polycyclic aromatic hydrocarbons can be simultaneously avoided to generate coke. Therefore, we saw that the new fluidized reactor should have two primary reaction zones. The residue oil was pre-cracked in the first reaction zone to separate the saturated hydrocarbon, monocyclic aromatic hydrocarbon and polycyclic aromatic hydrocarbon from the feedstock. A more suitable reaction environment is created in the second reaction zone for achieving a highly effective conversion of saturated hydrocarbons, monocyclic aromatic hydrocarbons and polycyclic aromatic hydrocarbons. Introduction of multiple reaction zones for respectively optimizing the adsorption and reaction in a

38

1 Introduction

single reactor may be the only way to resolve the conflict between conversion and selectivity of hydrocarbon reaction [30].

1.5.1.3

Maximizing Intermediate Products

The kinetic difference is found between different hydrocarbon molecules with different sizes and types. When the cracking reaction of hydrocarbon macromolecular and small molecular occur on the surface of catalyst, the reaction rate of the former is obviously higher than that of the latter. When hydrocarbon macromolecular are decomposed into small olefins, the kinetic difference exists in the cracking reaction between olefins and alkanes [30], as shown in Fig. 1.19. Light olefins can be obtained through catalytic cracking of hydrocarbons or methanol conversion. However, light olefins are intermediate products, which are prone to undergo secondary reactions such as hydrogen transfer and polymerization, thus reducing the selectivity to the desired products. This problem is particularly severe in the production of low carbon olefins in the fluidized reactor with only primary reaction zone. From the perspective of kinetics, the reaction process could be regulated accurately. The reaction temperature and reaction time can be regulated to be optimum for the production of light olefins with simultaneously avoiding or decreasing the consecutive conversion of light olefins to propylene conversion, in order to increase the yield of light olefins. Based on the experimental evidence, the last 0.2 s is very important for the conversion of methanol to olefin. One fluidized bed reactor is difficult to accurately create favorable reaction conditions for both methanol-to-olefins reaction and olefin conversion.

1.5.2

The Reactor Structure

To resolve forgoing problems, the complex catalytic reaction control technology with the diameter transformed fluidized bed (DTFB) as the reactor platform was proposed at 1999 and has been developed into a successful technology and applied in a variety of chemical processes.

Fig. 1.19 Differences of catalytic cracking reactions of alkane and olefin in kinetics

1.5 Structure of DTFB Reactor

39

Fig. 1.20 The gas-solid flow state with the variation of fluidized bed diameter

The variation of fluidized bed diameter can significantly change the gas-solid flow state and form multiple different particle concentration fields or basins in the same reactor (See Fig. 1.20). Different particle concentration fields can match with different types of reactions so as to accurately regulate the depth and direction of the desired reaction pathway in the complex catalytic reaction. The fluid with high velocity flows from the outlet of a reaction zone to the bottom of the next reaction zone in the form of a jet flow. The development of the jet flow is limited to the reactor space, which is called the restricted jet flow. The restricted jet flow is affected by the bed geometry and boundary conditions, showing different characteristics compared to the fully developed jet flow, such as the shortened core region, wall attachment, reflux flow, circulating flow and continuous reduction in pressure along the reactor length [14]. The fluid with high velocity jetting into the infinite space from the nozzle can develop freely, called the free jet flow. The free jet flow undergoes three stages from generation to disappearance, i.e., initial stage, transition stage and developed stage, as shown in Fig. 1.21. At the initial stage, the jet flow just leaves the nozzle, and its

40

1 Introduction

Fig. 1.21 The diagram of the development of free jet flow

velocity is quite uniform. As it flows down along the reactor, it is gradually mixed with the immediate layer of surrounding fluid and becomes wider and wider. The velocity in the center is kept as the same as the velocity from the nozzle. The velocity in the peripheral mixing zone gradually decreases to zero along the radial direction. At the transition stage, the velocity in the jet axis decreases, less than the initial flow velocity from the nozzle, and all the jet flow region belongs to the mixing zone. At the developed region, the radial profiles of mean axial flow velocity on different cross sections show the similar bell-shaped distribution. When the velocity decreases to zero, the jet flow disappears. From generation to disappearance of the jet flow, two stages need to focus on, i.e., the initial stage and the developed stage. These two stages show completely different flow characteristics, the former keeps the same momentum, temperature and composition of the gas as those at the nozzle, namely the potential flow, and the latter shows the bell-shaped radial velocity profiles on different cross sections. Generally speaking, a jet fluidized bed is formed by injection of a high-velocity flow stream into a limited space. In a jet fluidized bed, the jet flow region coexists with the surrounding annular fluidized region. When the voidage in the annular region is larger and the jet flow velocity in the center is very high, the flow resistance of the gas in the center to the annular region is small so that the gas in the jet flow could readily disperse in the annular region and the jet flow disappears rapidly. During the collapsing course of the jet flow, some bubbles are produced and rise upward through the bed, making the bed fully fluidized. The typical jet flow appears conical-shaped with an ellipsoid top. The height from the nozzle mouth to the jet top is defined as the jet depth Lmax, as shown in Fig. 1.22 [31]. Once the jet rises to the jet depth, the ellipsoid top of the jet flow is elongated. A regular bubble is then formed at the end and separated from the jet. The jet starts to collapse. The jet flow collapses in three stages with the variation of bubbles, as illustrated in Fig. 1.23 [32]. The initial bubble with the torch-like shape and shrunk neck, corresponds to the minimum jet depth Lmin, followed by the bubble-merged section with a series of shrunk necks corresponding to the maximum jet depth Lmax. The first

1.5 Structure of DTFB Reactor

41

Fig. 1.22 Vertical jets and their initial bubbles [31]

bubble just separated from the main body of the jet flow, before losing its original momentum to enter the bed layer, corresponds to the deepest jet section, Lb. The length Lb is the maximum depth above which the internals are required to install for avoiding the erosion by the jet flow. The high-velocity jet flow divides the bed into several dense areas. The strong and frequent collisions between the entrapped particles in the jet flow and the particles in the surrounding region result in rapid dissipation of the jet flow, thus the jet injection angle in the fluidized bed is larger than the single-phase jet angle. If the DTFB structure as shown in Fig. 1.20 is adopted as the reactor. The outlet velocity of the lowest reaction zone is about 20 m/s. The gas stream out of the first reaction zone is subsequently sprayed into the secondary reaction zone and divides

42

1 Introduction

Fig. 1.23 Typical jet structure [32]

the solid layer into several dense regions. This kind of fluidized state is unstable and the catalyst density inside the bed is in constant change, so it is difficult to provide a suitable place for complex catalytic reactions. A suitable distributor must be placed between the first and secondary reaction zones to properly distribute the fluid flow and eliminate sharp fluctuation of the catalyst density in the bed induced by the formation of a strong jet flow. The distributor is thus the key for DTFB for being a general reactor platform. Therefore, designing a suitable distributor, which can reduce or even eliminate the influence of the outlet jet in the first reaction zone on the stability of the fluidized bed in the second reaction zone, is one of the technical challenges in the development of DTFB reactor platform. Based on the preliminary structure of DTFB shown in Fig. 1.20, the DTFB reactor with considering the interference of the jet flow on the flow structure of the fluidized bed was invented [33–35]. This new reactor can be composed of the first reaction region, the second reaction region and the third reaction region with a fluid distributor mounted between the first and the second reaction zones. The bottom of the second reaction zone should form a stable catalyst bed of a certain density.

1.5 Structure of DTFB Reactor

43

Fig. 1.24 The structure scheme of DTFB reactor

Normally the first and third reaction zones belong to dilute transport beds with high velocity, while the second reaction zone is operated at fast fluidization. The schematic diagram of the structure of the new DTFB reactor is shown in Fig. 1.24. In a gas-solid fluidization system, the choking usually refers to an instability phenomenon that the concentration of catalyst particles, and hence the pressure drop, in the bed abruptly increases with the change of operating conditions (e.g., the solid flux). It is very important to predict the choking phenomenon in the design of gas-solid fluidized bed system and the stability of operation. As pointed out by Li and Kwauk [36], when the movement of particles controls the fluid flow, the state is called the particle-dominating (PD). As the fluid velocity increases, the fluid gradually loses its control by particles and starts to subject to each other, corresponding to the flow state as particle-fluid compromising (PFC). As the gas velocity further increases, the fluid flow dominates over particles and particles start to follow the bulk

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1 Introduction

Fig. 1.25 The choking phenomenon of Ug-Gs-I phase diagram [37]

fluid flow. The whole gas-solid system shows relatively uniform flow structures, corresponding to the fluid-dominating (FD) state. In Ug-Gs-I (superficial gas velocity-solids flux-solids inventory) phase diagram shown in Fig. 1.25 [37], choking occurs over a plateau section, on which the increase in solids inventory cannot change the solids flux (as the solids flux has reached the saturation carrying capacity, Gs ¼ K), but increases the height of the dense bottom section of axially S-shaped distribution. In short, if a fluidized bed is operated at non-choking states, the axial voidage distribution is relatively uniform and the stable state is FD or PD. However, if operated at the critical condition with choking (PFC/FD), the flow state could turn into a full-dense upflow (PD) or the dilute transport (FD) abruptly even if the operating conditions is slightly adjusted [38, 39]. As the catalyst inventory in the second reaction zone is relatively high, the choking is readily to occur. Therefore, in the second reaction zone, sufficient catalyst inventory is required for meeting the requirement of WHSV for catalytic reaction, and the choking phenomenon that affects the operation instability should be avoided simultaneously. So, whether the second reaction zone has enough space or suitable geometry to regulate the solid concentration and its distribution, is another major technical challenge in the development of DTFB reactor platform. In all, two important innovative ideas have been formed during the past two decades research: (1) Multiple reaction zones in a single fluidized bed was realized by varying the fluidized bed diameter; (2) The oriented conversion of complex catalytic reaction was achieved in different reaction zones in a single fluidized bed. Based on the technological platform of DTFB reactor, a series of engineering technologies, proprietary equipment and proprietary catalysts have been correspondingly developed, realizing the instantaneous oriented conversion and control of the transition state. As shown in Fig. 1.26, non-classical carbonium ions are generated firstly when the alkane molecules initially contact with the catalyst, and decomposed into the classical carbenium ions. The classical carbenium ions continue to undergo the β-scission reaction in the first reaction zone to form smaller carbenium ions. As

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Fig. 1.26 Schematic diagram of different hydrocarbon reaction paths in DTFB reactor

the reaction proceeds, the transition carbenium ions adsorbed on the surface of the catalyst enter the second reaction zone with movement of the catalysts. Whether carbenium ions in the second reaction zone will undergo β-scission, isomerization, hydrogen transfer or other types of reactions, primarily depends on the temperature and catalyst density in the second reaction zone apart from the catalyst performance factors. In other words, the direction and depth of the reaction can be controlled by adjusting the temperature and catalyst density in the second reaction zone. Of course, if necessary, the temperature and catalyst density in the third reaction zone can even be adjusted for satisfying the requirements of process parameters of a more complex gas-solid catalytic reaction.

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14. Kwauk, M.: In: Li, H.Z. (ed.) Fluidization Handbook. Chemical Industry Press, Beijing (2008). (in Chinese) 15. Kannan, C.S., Rao, S.S., Varma, Y.B.G.: A study of stable range of operation in multistage fluidised beds. Powder Technol. 78(3), 203–211 (1994) 16. Gascón, J., Téllez, C., Herguido, J., Menéndez, M.: Fluidized bed reactors with two-zones for maleic anhydride production: different configurations and effect of scale. Ind. Eng. Chem. Res. 44(24), 8945–8951 (2005) 17. Covezzi, M., Mei, G.: The multizone circulating reactor technology. Chem. Eng. Sci. 56(13), 4059–4067 (2001) 18. Gupta, A., Rao, D.S.: Model for the performance of a fluid catalytic cracking (FCC) riser reactor: effect of feed atomization. Chem. Eng. Sci. 56(15), 4489–4503 (2001) 19. Gupta, A., Rao, D.S.: Effect of feed atomization on FCC performance: simulation of entire unit. Chem. Eng. Sci. 58(20), 4567–4579 (2003) 20. Adanez, J., Abad, A., Garcia-Labiano, F., Gayan, P., de Diego, L.F.: Progress in chemicallooping combustion and reforming technologies. Prog. Energy Combust. Sci. 38(2), 215–282 (2012) 21. Adánez, J., Gayán, P., Celaya, J., de Diego, L.F., García-Labiano, F., Abad, A.: Chemical looping combustion in a 10 kWth prototype using a CuO/Al2O3 oxygen carrier: effect of operating conditions on methane combustion. Ind. Eng. Chem. Fundam. 45(17), 6075–6080 (2006) 22. Kronberger, B., Johansson, E., Löffler, G., Mattisson, T., Lyngfelt, A., Hofbauer, H.: A two-compartment fluidized bed reactor for CO2 capture by chemical-looping combustion. Chem. Eng. Technol. 27(12), 1318–1326 (2004) 23. Lyngfelt, A., Leckner, B., Mattisson, T.: A fluidized-bed combustion process with inherent CO2 separation; application of chemical-looping combustion. Chem. Eng. Sci. 56(10), 3101–3113 (2001) 24. Zhou Y.F.: Realization control and stability analysis of multiple temperature zones in the liquidcontaining gas-solid fluidized bed reactor. Doctoral thesis, Zhejiang University, Hangzhou, China (2014) 25. Marcilly, C.: Acido-Basic Catalysis: Application to Refining and Petrochemistry, vol. 2. Editions Technip, Paris (2006) 26. He, M.Y.: The development of catalytic cracking catalysts: acidic property related catalytic performance. Catal. Today. 73(1–2), 49–55 (2002) 27. He, M.Y.: Green Chemistry in Petroleum Refining and Synthesis of Basic Organic Chemicals. China Petrochemical Press, Beijing (2006). (in Chinese) 28. Xu, Y.H., Cui, S.Y.: A novel fluid catalytic cracking process for maximizing isoparaffins: from fundamentals to commercialization. Front. Chem. Sci. Eng. 12(1), 9–23 (2018) 29. Xu Y.H., Zhang J.S., Yang Y.N., Long J., Wang X.Q., Li Z.T., Zhang R.C.: Catalytic conversion process for producing isobutane and isoparaffin-enriched gasoline. USA, 2002, US 6,495,028 Bl 30. Xu, Y.H.: Chemistry and Process of Catalytic Cracking. Science Press, Beijing (2013). (in Chinese) 31. Merry, J.M.D.: Penetration of vertical jets into fluidized beds. AICHE J. 21, 507–510 (1975) 32. Knowlton, T.M., Hirsan, I.: The effect of pressure on jet penetration in semi-cylindrical gas-fluidized beds. In: Grace, J.R., Matsen, J.M. (eds.) Fluidization. Springer, Boston (1980) 33. Xu Y.H., Yu B.D., Zhang Z.G.: A riser reactor for fluidized catalytic conversion. China, 1999, ZL99105903.4 34. Xu Y.H., Yu B.D., Zhang Z.G., Long J., Jiang F.K.: Riser reactor for fluidized catalytic conversion. USA, 2010, US 7,678,342 Bl 35. Werther, J., Hartge, E.-U., Heinrich, S.: Fluidized-bed reactors – status and some development perspectives. Chem. Ing. Tech. 86, 2022–2038 (2014) 36. Li, J., Kwauk, M.: Paticle-Fluid Two-Phase Flow: The Energy-Minimization Multi-scale Method. Metallurgical Industry Press, Beijing (1994)

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Chapter 2

Fundamentals of Reactor Design and Scale-Up

Abstract Diameter-transformed fluidized beds (DTFBs) possess unique advantages in terms of their ability to control complex catalytic reactions. The design and scaleup of DTFBs are challenging due to the intrinsic multiscale nature of gas-solid fluidization. In this chapter, we first review the fundamental understanding of gas– solid flow regimes, which is relevant to both transport and reaction characteristics. Then, design and scale-up methods including analytical, experimental, and numerical approaches are introduced. Finally, we summarize the process of applying multiscale computation fluid dynamics simulations to the development of DTFBs.

2.1

Introduction

Diameter-transformed fluidized beds (DTFBs) are able to separate reactions into several different zones to realize efficient and selective conversion through complex catalytic reactions. Compared to traditional reactors, such as multilayer and multichamber fluidized beds, DTFBs allow multiple flow regimes to coexist in a single reactor with continuous control of reactions. Thus, DTFBs have been widely used for processes with complex catalytic reactions; e.g., fluid catalytic cracking (FCC), reaction of FCC residue, and conversion of methanol to olefins. The design of a DTFB should always meet the requirements of kinetic reactions and common rules of transport, including both hydrodynamics and mass and heat transfer. One principal challenge in the design of DTFBs is the prediction of the flow regimes in each reaction zone, and their changes in the transitional regions. Each reaction zone functions to meet the design in only a specified flow regime, because each flow regime has distinct characteristics in terms of solids concentration and mixing, efficiency of gas–solid contact, and distribution of particle residence time, and thereby the reaction behavior. However, accurate prediction of the flow regime is notoriously difficult, because it depends on multiple variables, including operating conditions, material properties, and bed geometry [1, 2]. Indeed, it is hard to unambiguously identify flow regimes, especially in a high-velocity fluidized bed. Researchers have delineated various flow regimes with different criteria and terminologies. A series of regime maps have been proposed based on different © Springer Nature Switzerland AG 2020 Y. Xu et al., Diameter-Transformed Fluidized Bed, Particle Technology Series 27, https://doi.org/10.1007/978-3-030-47583-3_2

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2 Fundamentals of Reactor Design and Scale-Up

coordinates and empirical flow regime boundaries; however, they only apply to specific particle and/or bed geometries. Further attention should be paid to the scaleup of DTFBs, because the flow regime may change during the scale-up process from laboratory to pilot to commercial scale. Thus, the practical development of DTFBs calls for reliable approaches that can predict flow regimes over different scales along with the characteristics of internal flow fields in as much detail as possible. There is not yet a universal approach for the design, scale-up, and optimization of fluidized beds. In past decades, the design of fluidized beds has heavily relied on empirical and semi-empirical correlations. These correlations are usually extracted from experiments with specific settings of the physical properties of fluid and particles and reactor geometry. Thus, they are difficult to extrapolate to a wide range of conditions. Fluidization engineers are hesitant to develop novel fluidized bed reactors, due to the lack of available correlations for new designs. A common approach for scale-up is to apply a scaling law [3], in which a set of dimensionless parameters are considered to be constant at different scales. However, this traditional approach has also been questioned because of the lack of degrees of freedom for designing scaled models, as well as incompleteness of scaling sets [4]. Computational fluid dynamics (CFD) simulation is expected to expand the horizons of process technology development [5]. However, it seems that the problems encountered by traditional methods are not circumvented when using CFD methods. There are two main CFD approaches used to investigate the multiscale behavior of fluidized beds. One is known as the filtered model [6], which extracts steady-state statistical information for coarse-grid modeling from fine-grid transient simulations. The other is the energy-minimization multiscale (EMMS) model [7], which is composed of a set of conservation equations and a stability condition, whose extremum determines the steady state of the system. Both of these approaches have been used to tackle multiscale problems in gas–solid fluidization systems. This chapter reviews the current understanding of the flow regimes in gas–solid fluidized beds. Then, methods for the design and scale-up of fluidized beds are introduced, with a focus on newly emerged numerical methods. Finally, the use of the EMMS-based CFD method in the design, scale-up, and optimization of fluidized beds is described.

2.2

Flow Regimes

The flow regime of a gas–solid fluidized bed depends on operating conditions, material properties, and geometric factors. In this section, we first focus on the relationship between regime maps and operating conditions. Then, different material properties are considered to increase the completeness of regime maps. Finally, we consider the influence of geometric factors on flow regimes.

2.2 Flow Regimes

2.2.1

51

Regime Identification

Researchers have delineated various flow regimes in gas–solid fluidized beds. In general, a gas–solid fluidized bed will experience several flow regimes including delayed bubbling, bubbling, slugging, turbulent, fast, and pneumatic transport regimes with increasing superficial gas velocity [8]. A schematic description of flow regimes [8] is shown in Fig. 2.1. The delayed bubbling regime, also called the homogeneous expansion regime, is normally encountered in systems with Geldart A particles [9] in a narrow range of superficial gas velocities just beyond the minimum fluidization velocity (Umf). The bubbling and turbulent regimes are normally classified as conventional fluidized beds or low-velocity fluidization. Slug flow occurs when the bed height-to-diameter ratio is comparatively high; for example, >2.0. Conventional fluidized beds have been used in coal gasification, catalytic cracking, and Fischer–Tropsch synthesis. The fast fluidization and pneumatic transport regimes are classified as high-velocity fluidization. Fast beds are widely applied in FCC, alumina calcination, combustion and gasification, and chemical looping, whereas the pneumatic transport regime is normally applied in physical processes such as solids conveying.

Fig. 2.1 Schematic depictions of flow regimes in gas–solid fluidized beds [8]. (Reprinted by permission of John Wiley and Sons)

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2 Fundamentals of Reactor Design and Scale-Up

Each flow regime mentioned above is characterized by distinctive features and can be distinguished using certain regime boundaries. The transition from a fixed bed to initial fluidization is delineated by Umf, at which the pressure drop of the bed is initially sufficient to support the weight of particles. The variation of pressure drop across the bed with superficial gas velocity levels off at Umf after gradually increasing in the fixed bed. Umf can be estimated from a correlation modified from the Ergun equation [10]. In the delayed-bubbling regime, particles are homogeneously distributed. In the delayed-bubbling regime, one can estimate the pressure drop using the equation developed by Wen and Yu [11], and the bed voidage can be determined using the relation reported by Richadson and Zaki [12]. The onset of the bubbling regime is delineated by the minimum bubbling velocity (Umb), at which bubbles first appear and form near the gas distributor and gradually coalesce with each other, resulting in larger bubbles with the increase of bed height [13]. In a fluidization system with Geldart A particles, successive bubble coalescence and splitting may reach an equilibrium when the bed is high enough. The bubble size can be estimated using the correlation described by Horio and Nonaka [14]. The efficiency of gas– solid contact in the bubbling regime is comparatively low because of the considerable gas bypassing. In a narrow and/or sufficiently deep fluidized bed, bubbles can coalesce and form a slug. The slug flow regime is characterized by growing bubbles, the size of which is comparable to the bed diameter. The superficial gas velocity indicating the onset of the slugging regime strongly depends on the bed diameter. The transition from the bubbling regime to the turbulent regime is gradual and can be delineated by two characteristic velocities, Uc and Uk [15]. Uc is defined as the superficial gas velocity at which the pressure fluctuation peaks, whereas Uk is the superficial gas velocity at which the pressure fluctuation, having decayed from the peak value, begins to level off. The fluidization behavior between Uc and Uk is characterized by the apparent breakdown of large bubbles into small dispersed voids [15]. When Uk is reached, dispersed voids gradually interconnect with each other and form a dilute phase, while the emulsion phase breaks down into distinct clusters and streamers of particles. For fine particles, Uk is normally larger than the terminal velocity of individual particles (ut) by about one order of magnitude [15]. However, the terminal velocity of clusters remains higher than the superficial gas velocity because of the strong clustering behavior. As a result, most fine particles can be maintained in the bed. However, there is also some entrainment of solids in the turbulent regime with fine particles, because a small fraction of particles can escape from clusters near the top of the bed. In contrast, there is no carryover in turbulent fluidized beds with coarse and/or denser particles, because the terminal velocity of these particles is normally higher than the superficial gas velocity in the range of the turbulent regime. Compared to the case for bubbling fluidized beds, turbulent fluidized beds provide better gas–solid contact and less gas bypassing. However, turbulent fluidized beds exhibit higher solid reflux and wider solid residence time distribution compared with those of circulating fluidized beds (CFBs). A turbulent fluidized bed is preferable for Fischer–Tropsch synthesis and FCC regeneration, where solid reflux is not a critical concern.

2.2 Flow Regimes

53

The transition from turbulent fluidization to fast fluidization is delineated by the transport velocity (Utr) at which considerable solids are entrained from the top of the bed upon further increase of the superficial gas velocity [15]. Yerushalmi and Cankurt [15] explained the sharp increase of particle carryover at Utr by surmising that “when the transport velocity is reached, the terminal velocities of a large proportion of the clusters are smaller than the velocity of the gas.” Given the considerable solid entrainment in the fast fluidization regime, continuous operation requires continuous solids feeding at the bottom of the bed. Beyond Utr, the solid concentration of beds depends on not only the superficial gas velocity but also the solid flow rate. The fast fluidization regime is characterized by high superficial slip velocity because of the presence of clusters. The radial core–annular structure and S-shaped axial distribution of solid concentration are considered typical characteristics of the fast fluidization regime. Larger clusters tend to form near the bed walls rather than at the bed center, whereas the gas velocity is comparatively low near the bed wall. As a result, large clusters cannot be sustained by the gas near the bed wall, giving rise to substantial solid backmixing. The fast fluidization regime exhibits a shorter residence time and narrower residence time distribution compared to those of the turbulent regime. In addition, larger solid circulation allows continuous operation and quickly deactivated catalyst to be refreshed. Thus, the fast fluidization regime has been widely used in CFB combustion and FCC. Bi et al. [16] suggested that the upper boundary of the fast fluidization regime is marked by the type A choking velocity (Uca), as shown in Fig. 2.2a. In the words of Bi and Grace [17], Uca is defined as “the point where the uniform suspension collapses, causing particles to begin to accumulate at the bottom of the transport line with reducing the gas velocity”. The fast fluidization regime, which extends from Utr to Uca, is characterized by strong solids reflux near the wall and both radial and axial nonuniformity. With further increase of the superficial gas velocity, the “core–annular dilute phase flow” regime identified by Bi and Grace [17] is found in the range between Uca and Ump, which is sometimes called Upt and denotes the superficial gas velocity close to the minimum pressure gradient [18]. In contrast to the fast fluidization regime, the core–annular dilute phase flow regime exhibits little solid reflux and therefore lacks solid backmixing. The axial solids distribution is either uniform or shown as an exponential solid concentration profile. Beyond Ump lies the pneumatic transport regime, which is sometimes also called homogeneous dilute phase flow [17] or dilute phase conveying [18]. Bai et al. [18] claimed that in the pneumatic transport regime, “the frictional resistance contribution to the pressure drop becomes more and more significant and, finally, predominates, when the gas velocity rises above Upt”. Identifications of the regimes in gas–solid fluidized beds are far from reaching a consensus, particularly for CFBs. A wide variety of descriptive terminology has been used, reflecting the discrepancies in the definitions of flow regimes. Sun and Zhu [20] proposed a regime map that consists of six flow regimes, including bubbling, turbulent, circulating turbulent, low-density circulating fluidization, high-density circulating fluidization, and pneumatic transport regimes, as shown in

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2 Fundamentals of Reactor Design and Scale-Up

Fig. 2.2 Typical diagrams of gas–solid fluidization regimes for FCC particles described by (a) Bi et al. [19] (Reprinted by permission of Elsevier), (b) Sun and Zhu [20] (Reprinted by permission of John Wiley and Sons), and (c) Yerushalmi and Cankurt [15] (Reprinted by permission of Elsevier)

Fig. 2.2b. Sun and Zhu [20] argued that the so-called fast fluidization and core– annular dilute-phase flow regimes defined by Bi and Grace [17] cannot be considered as individual flow regimes. To better reflect industrial applications, Sun and Zhu [20] divided a CFB regime into high-density and low-density CFB regimes with an empirical boundary where solid volume fraction (εs) equals to 0.1. The relatively recently proposed circulating turbulent fluidized bed [21] was also included in the regime map to represent the intermediate regime between those of a conventional fluidized bed and CFB. In addition to the flow maps with a Ug
Us or (Gs) coordinate system, the classic work of Yerushalmi and Cankurt [15] depicted a flow regime map with a Uslip
εs coordinate system, as shown in Fig. 2.2c. The slip velocity can provide a more relevant measure of gas–solid interactions than the superficial gas velocity [15]. In addition, the bubbling and turbulent regimes that are compressed near the origin in a map with Ug
Us coordinates can be well presented by using a map with Uslip
εs coordinates. Beyond transport velocity, the fast fluidization regime depicted in Fig. 2.2c stretches with the variation of solid flux.

2.2.2

Material Properties

In addition to operating conditions, material properties of both solid and gas phases strongly influence the flow regime. Geldart [9] classified solid particles into four groups based on the density difference (ρs
ρg) and mean particle size (dp), as

2.2 Flow Regimes

55

Fig. 2.3 Geldart’s classification of powders [9]. (Reprinted by permission of Elsevier)

5

D Spoutable

rs–rg (g/cm3)

B Sand-like 1 0.5

0.1 10

A Aeratable

C Cohesive

50

100 – d p (µm)

500

1000

shown in Fig. 2.3. Each group represents a distinctive type of fluidization. It should be noted that this diagram is only valid for air-fluidized beds at atmospheric pressure and temperature. Geldart A particles are fine and can be aerated. Most cracking catalysts are Geldart A particles. A fluidization system with Geldart A particles shows an appreciable range between Umf and Umb. In bubbling fluidized beds with Geldart A particles, bubbles rise faster than interstitial gas, which results in fast bubbles, as defined by Davidson and Harrison [22]. In fluidization systems with Geldart B particles, bubbles are generated once Umf is reached. Thus, the homogeneous expansion regime is absent in a system with Geldart B particles. Sand is a typical example of Geldart B particles. Geldart C particles are cohesive and much finer than Geldart A particles. Fluidization systems with Geldart C particles tend to form channels rather than being normally fluidized. Geldart D particles are coarse and have a relatively high terminal velocity. Fluidization with Geldart D particles normally results in spouted beds, where the gas is brought in through a small central tube. Geldart D particles are frequently encountered in coating processes in the pharmaceutical industry. To depict a flow regime map with broader conditions of different material properties, Grace [8] modified the regime diagram of Reh [23] and proposed a two-dimensional (2D) operating diagram, as shown in Fig. 2.4. This map used a dimensionless plot of U (U  ¼ U g ðρ2g =μg gðρs
ρg ÞÞ) and dimensionless particle diameter (dp, where dp ¼ Ar3 ¼ dp ðρg ðρs
ρg Þg=μ2g Þ ) for a gas–solid suspension, which was devised based on a dimensional analysis of dominant factors. Compared to the aforementioned flow regime map in Fig. 2.2, this map can readily describe fluidization systems with a wide range of particles. On this map, Geldart’s classification involving Geldart C–A, A–B, and B–D boundaries was further extended to cover a wide range of gases other than air at ambient temperature and pressure. Regions for different types of reactors, including a conventional fluidized bed, circulating beds, transport reactors, dilute conveying, spouted beds, and moving packed beds are indicated on this map. The variation of the dimensionless minimum fluidization velocity (U mf ) and terminal velocity (ut ) with dp was determined from 1

1=3

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2 Fundamentals of Reactor Design and Scale-Up

Fig. 2.4 2D Operating diagram of fluidization [8]. (Reprinted by permission of John Wiley and Sons)

empirical correlations. Generally, ut increases with particle size and density. For Geldart A particles, a conventional fluidized bed can be operated at a gas velocity larger than ut by almost an order of magnitude because of the strong clustering effect. For Geldart D particles, the terminal velocity is so high that spouted beds are encountered under common operating conditions. It should be noted that the blanked regions on the map clearly indicate the areas undefined or with disputed hydrodynamic behavior.

2.2.3

Geometric Factors

Bed geometry has been found to influence the hydrodynamics of fluidized beds in the scale-up of reactors on the laboratory, pilot, and industrial scales. The behavior of

2.2 Flow Regimes

Group B Parameter

Fig. 2.5 Schematic illustration of the effects of bed diameter on the parameters of gas–solid fluidized beds [24]. (Reprinted by permission of Elsevier)

57

Group A

D1

D2 Diameter

gas–solid fluidized beds is complex because of the scale-dependence of parameters. As the bed diameter increases, the hydrodynamics of the bed may change; in some cases, the increase of bed diameter induces regime transitions, even if the operating conditions and particle properties remain the same. A schematic diagram of the influence of bed diameter on the dynamic parameters of the system is shown in Fig. 2.5 [24]. Multiple parameters of interest for scale-up including the bubble size and solid hold-up change with bed diameter. These parameters change rapidly at small bed diameter because of the wall effect, and tend to reach a constant value at larger bed diameter. The scaling parameter in a bed of Geldart A particles generally reaches a constant value at smaller bed diameter than that in the case of Geldart B particles. In bubbling beds, bubbles can grow larger in a bed with larger diameter. Larger bubbles allow more gas bypassing and thus lower the efficiency of gas–solid contact. Frye et al. [25] found that the reaction rate decreased by a factor of three when the bed diameter was increased from 0.0508 to 0.762 m. The experiment of Horio et al. [26] revealed that reaction yield decreased with increasing bed diameter. Bashiri et al. [27] investigated the hydrodynamics of gas–solid fluidized beds using the radioactive particle tracking technique and found that the solid diffusion and mixing increased with the bed diameter. Verma et al. [28] studied the bubble dynamics in five gas–solid fluidized beds with different diameters using CFD simulations. Their results showed that the bubble size and bubble rise velocity both increased with bed diameter. Efhaima and AI-Dahhan [29] investigated the effect of bed diameter on the hydrodynamics of gas–solid fluidized beds using the radioactive particle tracking technique. It was revealed that a larger bed diameter gave rise to higher axial solid velocity, bubble rise velocity, solid mixing, and solid diffusion. When it comes to CFBs, bed geometry also strongly affects their hydrodynamics. Yerushalmi and Avidan [30] observed a higher mean solid concentration in a bed column with larger diameter than that of a bed column with a smaller diameter at the same superficial gas velocity and solid flux. In addition, more clusters tend to form and cover the wall in a bed with larger diameter than is the case in a bed with smaller diameter, which leads to higher heat transfer from the bed to the wall in the former

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2 Fundamentals of Reactor Design and Scale-Up

system than in the latter. Zhang et al. [31] found that the layer thickness of downflowing particles at the wall of a CFB increased with bed diameter. Xu et al. [32] concluded that the influence of bed diameter on the bed density of CFBs is closely related to the particle type. Their experiments showed that the bed density decreased with increasing riser diameter for Geldart A particles, whereas the opposite trend was observed for Geldart B particles under specified operating conditions. The saturation carrying capacity was also found to increase with bed diameter for Geldart A particles, whereas it decreased with increasing bed diameter for Geldart B particles. Apart from bed diameter, the hydrodynamics of gas–solid fluidization is also strongly affected by some other geometric factors, such as the height-to-diameter ratio, variation of the cross-sectional area with height, inlet/outlet geometry, and inner baffles. For instance, in FCC processes, the inlet geometry influences the catalyst/oil mixing pattern. Feedstock nozzles with an inclined upward angle of 30 relative to the riser axis may cause nonuniform catalyst/oil distribution, severe backmixing, and even choking [33]. In a gas–solid fluidized dryer, spouted beds usually possess a diverging cone base with gas fed into the bed through an orifice [34]. This design can enhance solid motion and eliminate dead space in the bed bottom. Venkatesh et al. [35] found that a conical bed markedly improved the fluidity of Geldart C particles compared with that of the same particles in cylindrical beds. Wormsbecker et al. [36] compared the particle hydrodynamics in cylindrical and conical fluidized beds during the drying process. Their experiments illustrated that undesirable fluidization conditions such as channeling and defluidization sometimes obtained when using a cylindrical bed could be avoided by using a conical bed.

2.2.4

The Choking Phenomenon

Sharp flow regime transitions such as choking can cause problems such as equipment damage and thus should be avoided when manipulating gas–solid fluidized beds. The term “choking” was first proposed by Zenz [37] to describe the sudden increase of pressure drop in the vertical pneumatic transport of particles in pipes when the superficial gas velocity is decreased to a certain point at a constant solid flux. As the choking point is approached, the suspension and transport of particles cannot be further supported by the fluid, and thus the regime of dilute pneumatic transport collapses into the slug or turbulent flow regime. The solid flux at the choking point is termed the saturation carrying capacity of the fluid stream at the corresponding superficial gas velocity. Yerushalmi and Cankurt [15] evaluated choking by plotting the variation of the pressure drop in risers with solid flux, as shown in Fig. 2.6. When the superficial gas velocity was set at a constant value below Utr, the pressure drop in a riser initially gradually increased with the solid flux, following the line OA in Fig. 2.6. With further increase of solid flux, a sudden increase of pressure drop occurs at the saturation carrying capacity along line AA’, indicating classical choking behavior.

2.2 Flow Regimes

59

Fig. 2.6 Qualitative representation of choking [15]. (Reprinted by permission of Elsevier)

The bell-shaped area below Utr indicated by dotted lines shows the turbulent flow regime. When the superficial gas velocity is larger than Utr, the fluidized bed experiences a non-choking transition with increasing solid flux. The fast fluidization regime exists in the region beyond Utr. As a result, Utr demarcates the boundary between the turbulent and fast fluidization regimes. It should be noted that in the literature, different names have been used to denote the flow regimes in Fig. 2.6. For example, Li and Kwauk [7] and Lu et al. [38] identified the bell-shaped area in Fig. 2.6 as fast fluidization. Such a mismatch can be viewed as solely the use of different terminology, because the major flow characteristics in these areas are widely accepted and the same on different flow regime maps. Early studies on choking were conducted in pipes with small diameters, usually less than cm, using Geldart B or D particles. When it comes to choking in a CFB riser, which normally has a large diameter and relatively fine particles, the situation becomes more complicated, which has caused confusion and disagreement of the definition of choking [39]. To distinguish the classical definition of choking from that defined in the context of CFB risers, choking behavior that results in a transition to the slug or turbulent regime was classified as classical choking (type C) [16]. The incipient fast fluidization boundary encountered in risers with large diameter that is characterized by a gradual collapse of the particle suspension originating from the bottom of the riser was classified as accumulative choking (type A) [16]. The fast fluidization regime exists in the region between type A and type C choking, as shown in Fig. 2.7. This region becomes narrower with decreasing riser diameter and/or increasing particle size/density. When type C and type A choking coincide, the fast fluidization regime will no longer exist and the flow regime transforms directly from dilute phase transport to the slug or turbulent flow regime [39]. In DTFBs, superficial gas velocity decreases sharply when the fluid enters the second reaction zone. Choking occurs if the superficial gas velocity drops below Utr. Under these conditions, particles accumulate in the second reaction zone, which

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2 Fundamentals of Reactor Design and Scale-Up

Fig. 2.7 Regime map showing the boundaries of classical choking (type C) and accumulative choking (type A) [39]. (Reprinted by permission of American Chemical Society)

leads to unstable operation. It should be noted that the size of the choking zone in Fig. 2.7 is affected by the bed height of the fluidized bed (see Chap. 4) and the material properties of both the gas and solid phases. It is of great importance to predict choking behavior to aid the design and operation of DTFBs.

2.3

Methods for the Design and Scale-Up of DTFBs

Although DTFBs are ideal for industrial applications such as complex catalytic conversions, there are no universal techniques for the design and scale-up of fluidized beds. To date, fluidized bed design has relied heavily on empirical and semi-empirical correlations. The scale-up of fluidized beds normally uses a scaling law in which a set of dimensionless parameters are set to be constant at different scales. This traditional method provides general principles and parameters for design and scale-up but not detailed information about flow fields and reactions. The numerical method based on CFD has developed rapidly in recent decades and become a promising approach to compensate for the deficiencies of the traditional method. However, the numerical method also has limited accuracy and efficiency, and struggles to integrate hydrodynamics, heat and mass transfer, and reaction kinetics.

2.3 Methods for the Design and Scale-Up of DTFBs

2.3.1

61

Analytical Approach

The analytical approach based on phenomenological models and empirical correlations is still widely used for the design of gas–solid fluidized beds. Historically, there are two classes of models for modeling gas–solid fluidized beds. One is the ideal or simple one-parameter models, which include the ideal plug flow model, complete mixing or continuous stirred tank reactor model, dispersion model, and residence time distribution model. These models are oversimplified and hence inadequate to describe the flow behavior and reactions when heterogeneous structures are present in the bed. To account for the difference of contacting modes between the dense and dilute phases, two-phase models were proposed based on the assumption of two-phase theory [40]. These models distinguish gas–solid fluidized beds into two phases, a particle-rich dense phase and a gas-rich dilute phase. Mass balance equations for a given species in both dense and dilute phases are formulated that consider both mass transfer and reactions. These phenomenological models are normally based on a lumped, algebraic description of zero-dimensional space or a one-dimensional (1D) flow along the axial direction, or even a 2D axisymmetric cylindrical bed. Boundary conditions are required to solve 1D and 2D models. One model used describe fluidized beds is the bubble model proposed by Davidson and Harrison [22], which is based on the two-phase theory. This model reasonably describes the dynamic behavior of a single bubble rising in a fluidized bed and predicts the relation between the bubble size and rising velocity, as well as fast and slow bubble phenomena. Kunii and Levenspiel [41] proposed a bubbling bed model that considers an additional cloud-wake phase in addition to the bubble and emulsion phases. Edwards and Avidan [42] proposed the axial dispersed plug flow model for fully turbulent fluidization. Abba et al. [43] developed a generic fluidized bed reactor model that is applicable to multiple flow regimes ranging from minimum bubbling to fully fast fluidized beds. The two-phase model was used to describe the bottom dense region of the bed and an exponential decrease of solid concentration was assumed in the freeboard region. Kunii and Levenspiel [44] developed a flow and contacting model to describe CFBs, which can be used to estimate the contacting efficiency for turbulent, fast, and pneumatic transport regimes. Here we take a bubbling fluidized bed as an example [45]. Based on the two-phase model, it was assumed that the bubbling fluidized bed consisted of a particle-free bubble phase and a homogeneous emulsion phase. The gas bubble phase was subjected to ideal plug flow, whereas the emulsion phase showed complete mixing flow with respect to both gas and particle phases. The mass balance equation for species A in the bubble phase was thus given by Ub

dCbA
kab f b ðC dA
CbA Þ ¼ 0 dz

ð2:1Þ

where CbA and CdA denote the concentrations of species A in the bubble phase and emulsion phase, respectively, Ub is the bubble velocity, ab is the bubble surface

62

2 Fundamentals of Reactor Design and Scale-Up

concentration, and fb is the volume fraction of the bubble phase. The mass balance equation for species A in the emulsion phase was expressed as: Z

H

U d ðC Ain
CdA Þ þ

kab f b ðC bA
C dA Þdz
ð1
f b Þεds Hr A ¼ 0

ð2:2Þ

0

where CAin denotes the concentration of species A at the inlet boundary, H is the bed height, and rA the reaction rate per unit volume of catalyst. The boundary condition at the bed bottom was given by CbA ¼ CAin. Because complete mixing flow was assumed in the emulsion phase, CdA was independent of the bed height. The variation of CbA was determined from Eq. (2.1). By substituting the function of CbA into Eq. (2.2), the CdA was determined. Then, the mean concentration of species A at H was determined using the following mass balance equation between the bubble and emulsion phases: UCA ¼ U b C bA jz¼H þ U d C dA

ð2:3Þ

This simple 1D phenomenological model predicted the concentration distribution of species. In turbulent fluidized beds, the bottom dense region is normally assumed to consist of a dilute phase and a dense phase, where the dilute phase satisfies plug flow. The upper dilute region is described as a single dilute phase. Similar phenomenological equations with feasible boundary conditions can be formulated, as in the case of bubbling fluidized beds. When it comes to fast fluidized beds, many phenomenological models have used the cluster concept and the two-phase theory was added with an entrainment model. In addition, 2D dispersion models are also frequently used to describe the mass balance of species by considering the S-shaped axial distribution and the core–annular structure in the fast bed. By applying empirical correlations of axial and radial distributions of particles, these models can be solved. The design of fluidized beds still relies heavily on the analytical approach. Numerous correlations have been accumulated in the last half century. However, a model that is feasible for a certain reactor may not function well in another case. Furthermore, these models do not provide detailed information about the flow field and reactions, and therefore may not be applicable to reactors with complicated geometry.

2.3.2

Experimental Approach

The scale-up of fluidized beds is limited by the lack of understanding of the scaledependence of parameters of interest of fluidized beds. Most empirical correlations for hydrodynamics have been extracted from laboratory-scale fluidized beds at ambient temperature and pressure, and cannot be directly extended to larger scales.

2.3 Methods for the Design and Scale-Up of DTFBs

63

The lack of empirical correlations available for the design of commercial-scale fluidized beds, especially at elevated temperature and pressure, makes it still necessary to obtain design parameters using the experimental approach. The design of commercial reactors mainly relies on extensive scale-up processes [46]. Generally, one has to first conduct a screening procedure that involves selecting a proper fluidization regime and type of reactor based on reaction kinetics. Next, a laboratory-scale reactor and then a pilot-scale reactor are constructed to investigate the transport and reaction behavior at each of these scales. Finally, a full-scale reactor is constructed by using the data and experience collected from the cold flow model and pilot-scale unit. Researchers have expended much effort devising ways to aid the scale-up of commercial plants. A common approach is to determine a scaling law in terms of the similarities of the hydrodynamics and reactions between two fluidized beds; for example, a scaled cold reactor and a hot full-scale one. The scaled cold model can be used to mimic and test the hydrodynamics of the hot full-scale reactor, which allows parameters to be experimentally investigated using the smaller cold reactor and then extended to the larger hot reactor. Generally, a scaling law is described as a set of dimensionless parameters that should be kept constant at different scales. These relevant dimensionless parameters can be derived from dimensional analysis. For example, Glicksman [3] obtained a full set of dimensionless parameters by non-dimensionalizing the governing equations derived by Anderson and Jackson [47], the constitutive drag model proposed by Ergun [10], and the boundary condition. Horio et al. [26] obtained two scaling parameters based on a phenomenological model of bubbling beds. Here we describe the scaling law of Glicksman [3] as an example. To derive the scaling relationship, a set of general independent dimensionless parameters governing the dynamics of the fluidized bed were found by non-dimensionalizing the general equations of motion for fluidized beds. For simplicity, the fluid was assumed to be incompressible and the collisional force and viscous stress were neglected. The non-dimensional form of momentum balance equation for particles is given by  ð1
εÞ

 gd p βdp  ∂v    þ ðv  ∇ Þv ðu
v Þ ¼ 0 þ 2 ð1
εÞ
 ρs u0 ∂t u0

ð2:4Þ

where v ¼ v/u0, u ¼ u/u0, ∇ ¼ dp∇, and t  ¼ du0p t. The non-dimensional form of momentum balance equations for a fluid can by expressed as     βdp  ρf ∂u ρf gdp P     ε þ ðu  ∇ Þu ε þ ∇ ðu
v Þ ¼ 0 þ þ ρs u0 ρs ∂t  ρs u20 ρs u0

ð2:5Þ

The mass balance equation and boundary conditions were non-dimensionalized in the same way. From these non-dimensional equations, the independent non-dimensional   parameters were identified as

βd p ρs u0

,

gd p u0

,

L dp

,

D dp

,

ρf ρs

,

P0 ρs u20

. Glicksman [3] used the

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2 Fundamentals of Reactor Design and Scale-Up

Ergun drag correlation [10] for the drag coefficient (β). As a result, in the viscous limit and inertial limit, the governing non-dimensional parameters were simplified to gd gd ( u0p , ρ uμ0 dp , dLp , dDp , HD ) and ( u0p , ρρf , dLp , dDp , HD ), respectively. When two beds are s

s

designed to have equal independent non-dimensional parameters, the dependent non-dimensional variables, including fluid and particle velocity, pressure distribution, and voidage distribution, will also be identical. The scaling law approach has been applied to the scale-up of fluidized beds over the past decades. However, it has also been questioned for many reasons. One major criticism is the incompleteness of the scaling set with respect to the particle collision, particle friction, and wall effects [48]. Studies have also revealed that existing scaling laws may not apply to Geldart A particle systems [49], in which mesoscale clustering effects are substantial. Indeed, the currently available scaling laws are still based on the assumption of a homogeneous distribution rather than multiscale flow structures, which are known to be important in fluidized beds and other multiphase flow reactors. Scaling law models may result in evident discrepancies when a bed has obvious inlet and/or outlet effects and complex geometry. Moreover, particle properties in terms of size and density derived from scaling laws may not reflect those available for experimental implementation.

2.3.3

Numerical Approach

The numerical approach is becoming a useful tool to aid the design, scale-up, and optimization of fluidized bed reactors and is evolving with the increase of computational capacity. In the last half century, researchers have developed numerous multiphase flow models, including the particle-resolved direct numerical simulation model, discrete particle model, and two-fluid model (TFM), which describe the gas– solid flow at different scales [50]. Compared to analytical and experimental approaches, numerical simulations can not only provide rich information about the flow field, but also handle irregular bed geometries. It is common to use the TFM for the simulation of industrial-scale reactors because of its reasonable computational cost. The hydrodynamic equations of the TFM were derived by Anderson and Jackson [47] using an averaging process. Constitutive models are required for the unclosed terms in the TFM, including the viscous stress terms of both fluid and particle phases, the collisional stress of the particle phase, and the interaction drag force between gas and solid phases. Ding and Gidaspow [51] obtained a set of closure models for collisional and viscous stress terms by applying the kinetic theory of granular flow. Empirical drag models such as those developed by Wen and Yu [11] and Ergun [10] are often used to simulate gas– solid fluidized reactors. The efficiency and accuracy of the traditional TFM are sometimes poor, especially when simulating gas–solid systems with Geldart A particles. To achieve gridindependent results, the grid size should be as small as ten times the particle diameter

2.4 EMMS-Based Multiscale CFD Simulation

65

(or even smaller). Such a fine grid is not suitable for simulating large-scale reactors because of its high computational cost. In addition, when TFM simulations are integrated with homogeneous stress and drag correlations, predicted bed behavior, e.g., pressure drop, solid concentration distribution, and solid flux, becomes unreasonable. Yang et al. [52] found that their simulation using a homogeneous drag coefficient overestimated the solid flux by several orders of magnitude. In addition to hydrodynamics, the mass transfer coefficient correlations predicted for a CFB have differed by up to seven orders of magnitude [53, 54]. The failure of the traditional TFM to accurately model CFBs can be attributed to their multiscale structures over a wide range of scales prevailing at the sub-grid level, which are not resolved by the coarse-grid TFM coupled with homogeneous drag and stress models. Gas–solid fluidization is characterized by multiscale structures ranging from the scale of several particle diameters to the whole reactor. Microscale non-equilibrium processes including inelastic particle collisions, particle friction, and particle–fluid drag give rise to a variety of mesoscale structures in the form of bubbles and clusters, which affect the macroscale flow regime in a reactor [55]. These mesoscale structures strongly influence the hydrodynamics, mass and heat transfer, and chemical reactions in a reactor. To solve these problems, researchers have proposed many multiscale methods that consider the effects of sub-grid heterogeneous structures on the momentum, mass, and heat transfer in reactors. Over the past decades, a multiscale CFD method based on the EMMS model has been developed rapidly and received wide interest from the fluidization community.

2.4

EMMS-Based Multiscale CFD Simulation

The EMMS model was first proposed by Li and Kwauk [7]. This model describes the multiscale interactions in a gas–solid fluidization system with eight parameters and six eqs. A stability condition, namely the minimization of the energy to suspend and transport particles per unit mass of particles, is assumed to be satisfied when the fluidization system reaches its steady state. For given operating conditions and material properties, this model can be solved by optimizing the stability condition under the constraint of mass and force balance equations (further details of the EMMS model are described in Chap. 3). The EMMS model has been successfully used to predict the particle distributions and regime transitions in fluidized beds. By modifying the original EMMS model and extending it into the sub-grid level, the same group developed a series of EMMS-based heterogeneous drag models and multiscale CFD methods [56–59]. The EMMS drag models predicts that multiscale structures will cause a considerable drag reduction. The heterogeneous drag coefficient predicted by the EMMS drag model is lower than the homogeneous drag coefficient by up to three orders of magnitude. The TFM integrated with the EMMS drag model can reasonably predict particle concentration profiles, velocity profiles, and solid flux. The EMMS drag model has been validated in multiple flow regimes,

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2 Fundamentals of Reactor Design and Scale-Up

including bubbling, turbulent, fast, and pneumatic transport, and it enables accurate prediction of flow regime transitions; in particular, the choking transition in fluidized beds. Using the EMMS-based multiscale CFD method, Wang et al. [60] investigated choking in gas–solid fluidized beds. A set of fluidization systems with different solid flux were simulated at a given superficial gas velocity. The choking transition, depicted as an S-shaped area, was clearly predicted, which agreed well with the experimental findings. The simulation results also revealed that the choking area expanded with increasing bed height. Prediction of choking will help to avoid unstable operation during the scale-up of DTFBs [38] (see Chap. 4 for more details about the EMMS drag model and its applications). The EMMS-based multiscale CFD method has also been used to investigate the effects of different gas distributors and aid the design of the transitional regions in DTFBs. Chen et al. [61] investigated the effects of injection angle on the performance of FCC risers via CFD simulation. They showed that the feedstock with an upward injection angle of 30 , which is normally used in conventional designs, easily caused non-uniform gas–solid contact and undesirable backmixing in the feedstock injection zone. The CFD results also suggested that the catalyst distributions and gas–solid contact time could be improved by using a downward injection angle of 30 . The serious backmixing caused by the secondary flow could also be eliminated by using this design. By coupling with reaction kinetics, the EMMS-based multiscale CFD method has also been applied to the design and scale-up of methanol to olefins [62, 63], CFB boiler [64, 65], and maximizing isoparaffins [38] processes.

2.5

Summary

The development of new gas–solid fluidized bed reactors is a very complex and systematic endeavor. The scale-dependent, non-equilibrium nature of gas–solid flows give rise to complex dependencies of flow regime transitions and transfer and reaction phenomena. There is not yet a universal and mature method for the design, scale-up, and optimization of fluidized beds. Traditional approaches based on the assumption of homogeneous distributions normally fail to predict the complex behavior of fluidization. The multiscale CFD method, which considers sub-grid mesoscale structures, is a promising approach to tackle the challenge of CFB scaleup. Examples of this method are described in detail in the following chapters.

References 1. Wang, W., Chen, Y.: Mesoscale modeling: beyond local equilibrium assumption for multiphase flow. In: Advances in Chemical Engineering, pp. 193–277. Elsevier, San Diego (2015)

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2. Grace, J.: Hydrodynamics of fluidization. In: Michaelides, E., Crowe, C., Schwarzkopf, J. (eds.) Multiphase Flow Handbook, pp. 955–994. CRC Press, Boca Raton (2016) 3. Glicksman, L.R.: Scaling relationships for fluidized-beds. Chem. Eng. Sci. 39(9), 1373–1379 (1984) 4. Rudisuli, M., Schildhauer, T.J., Biollaz, S.M.A., van Ommen, J.R.: Scale-up of bubbling fluidized bed reactors – a review. Powder Technol. 217, 21–38 (2012) 5. Syamlal, M., Guenther, C., Cugini, A., Ge, W., Wang, W., Yang, N., Li, J.H.: Computational science: enabling technology development. Chem. Eng. Prog. 107(1), 23–29 (2011) 6. Igci, Y., Andrews, A.T., Sundaresan, S., Pannala, S., O’Brien, T.: Filtered two-fluid models for fluidized gas-particle suspensions. AICHE J. 54(6), 1431–1448 (2008) 7. Li, J., Kwauk, M.: Particle-Fluid Two-Phase Flow: The Energy-Minimization Multi-scale Method. Metallurgical Industry Press, Beijing (1994) 8. Grace, J.R.: Contacting modes and behavior classification of gas -solid and other two-phase suspensions. Can. J. Chem. Eng. 64(3), 353–363 (1986) 9. Geldart, D.: Types of gas fluidization. Powder Technol. 7(5), 285–292 (1973) 10. Ergun, S.: Fluid flow through packed columns. Chem. Eng. Prog. 48(2), 89–94 (1952) 11. Wen, C., Yu, Y.: Mechanics of fluidization. Chem. Eng. Prog. Symp. Ser. 62(62), 100–111 (1966) 12. Richardson, J., Zaki, W.: Sedimentation and fluidisation: part 1. Trans Inst. Chem. Eng. 32, 35–53 (1954) 13. Darton, R.C., Lanauze, R.D., Davidson, J.F., Harrison, D.: Bubble-growth due to coalescence in fluidized-beds. Trans. Inst. Chem. Eng. 55(4), 274–280 (1977) 14. Horio, M., Nonaka, A.: A generalized bubble diameter correlation for gas-solid fluidized-beds. AICHE J. 33(11), 1865–1872 (1987) 15. Yerushalmi, J., Cankurt, N.T.: Further-studies of the regimes of fluidization. Powder Technol. 24(2), 187–205 (1979) 16. Bi, H.T., Grace, J.R., Zhu, J.X.: Types of choking in vertical pneumatic systems. Int. J. Multiphase Flow. 19(6), 1077–1092 (1993) 17. Bi, H.T., Grace, J.R.: Flow regime diagrams for gas-solid fluidization and upward transport. Int. J. Multiphase Flow. 21(6), 1229–1236 (1995) 18. Bai, D., Jin, Y., Yu, Z.: Flow regimes in circulating fluidized beds. Chem. Eng. Technol. 16(5), 307–313 (1993) 19. Bi, H.T., Grace, J.R., Lim, K.S.: Transition from bubbling to turbulent fluidization. Ind. Eng. Chem. Res. 34(11), 4003–4008 (1995) 20. Sun, Z.N., Zhu, J.: A consolidated flow regime map of upward gas fluidization. AICHE J. 65(9), e16672 (2019) 21. Zhu, H.Y., Zhu, J.: Comparative study of flow structures in a circulating-turbulent fluidized bed. Chem. Eng. Sci. 63(11), 2920–2927 (2008) 22. Davidson, J.F., Harrison, D.: Fluidised Particles. Cambridge University Press, London (1963) 23. Reh, L.: Fluid dynamics of CFB combustor. In: Circulating Fluidized Bed Technology V. Science Press, Beijing (1997) 24. Knowlton, T.M., Karri, S.B.R., Issangya, A.: Scale-up of fluidized-bed hydrodynamics. Powder Technol. 150(2), 72–77 (2005) 25. Frye, C.G., Lake, W.C., Eckstrom, H.C.: Gas-solid contacting with ozone decomposition reaction. AICHE J. 4(4), 403–408 (1958) 26. Horio, M., Nonaka, A., Sawa, Y., Muchi, I.: A new similarity rule for fluidized-bed scale-up. AICHE J. 32(9), 1466–1482 (1986) 27. Bashiri, H., Mostoufi, N., Sotudeh-Gharebagh, R., Chaouki, J.: Effect of bed diameter on the hydrodynamics of gas-solid fluidized beds. Iran. J. Chem. Chem. Eng. 29(3), 27–36 (2010) 28. Verma, V., Padding, J.T., Deen, N.G., Kuipers, J.A.M.: Effect of bed size on hydrodynamics in 3-D gas-solid fluidized beds. AICHE J. 61(5), 1492–1506 (2015) 29. Efhaima, A., Al-Dahhan, M.H.: Bed diameter effect on the hydrodynamics of gas-solid fluidized beds via radioactive particle tracking (RPT) technique. Can. J. Chem. Eng. 95(4), 744–756 (2017)

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30. Yerushalmi, Y., Avidan, A.: High velocity fluidization. In: Davidson, J.F., Clift, R., Harrison, D. (eds.) Fluidization. Academic, New York (1985) 31. Zhang, W.N., Johnsson, F., Leckner, B.: Fluid-dynamic boundary-layers in Cfb boilers. Chem. Eng. Sci. 50(2), 201–210 (1995) 32. Xu, G.W., Nomura, K., Nakagawa, N., Kato, K.: Hydrodynamic dependence on riser diameter for different particles in circulating fluidized beds. Powder Technol. 113(1–2), 80–87 (2000) 33. Chen, S., Fan, Y.P., Yan, Z.H., Wang, W., Lu, C.X.: CFD simulation of gas-solid two-phase flow and mixing in a FCC riser with feedstock injection. Powder Technol. 287, 29–42 (2016) 34. Mathur, K.B., Epstein, N.: Spouted Beds. Academic, New York (1974) 35. Venkatesh, R.D., Chaouki, J., Klvana, D.: Fluidization of cryogels in a conical column. Powder Technol. 89(3), 179–186 (1996) 36. Wormsbecker, M., van Ommen, R., Nijenhuis, J., Tanfara, H., Pugsley, T.: The influence of vessel geometry on fluidized bed dryer hydrodynamics. Powder Technol. 194(1–2), 115–125 (2009) 37. Zenz, F.A.: Two-phase fluid-solid flow. Ind. Eng. Chem. 41(12), 2801–2806 (1949) 38. Lu, B., Wang, W., Li, J.H., Wang, X.H., Gao, S.Q., Lu, W.M., Xu, Y.H., Long, J.: Multi-scale CFD simulation of gas-solid flow in MIP reactors with a structure-dependent drag model. Chem. Eng. Sci. 62(18–20), 5487–5494 (2007) 39. Yang, W.C.: “Choking” revisited. Ind. Eng. Chem. Res. 43(18), 5496–5506 (2004) 40. Toomey, R.D., Johnstone, H.F.: Gaseous fluidization of solid particles. Chem. Eng. Prog. 48(5), 220–226 (1952) 41. Kunii, D., Levenspiel, O.: Fluidization Engineering. Wiley, New York (1969) 42. Edwards, M., Avidan, A.: Conversion model aids scale-up of mobil fluid-bed MTG process. Chem. Eng. Sci. 41(4), 829–835 (1986) 43. Abba, I.A., Grace, J.R., Bi, H.T., Thompson, M.L.: Spanning the flow regimes: generic fluidized-bed reactor model. AICHE J. 49(7), 1838–1848 (2003) 44. Kunii, D., Levenspiel, O.: Circulating fluidized-bed reactors. Chem. Eng. Sci. 52(15), 2471–2482 (1997) 45. Jiang, P., Wei, F., Fan, L.-S.: General approaches to reactor design. In: Yang, W.-C. (ed.) Handbook of Fluidization and Fluid-Particle Systems. Taylor & Francis Group LLC, New York (2003) 46. Kelkar, V.V., Ng, K.M.: Development of fluidized catalytic reactors: screening and scale-up. AICHE J. 48(7), 1498–1518 (2002) 47. Anderson, T.B., Jackson, R.: A fluid mechanical description of fluidized beds. Ind. Eng. Chem. Fundam. 6(4), 527–539 (1967) 48. Grace, J.R., Taghipour, F.: Verification and validation of CFD models and dynamic similarity for fluidized beds. Powder Technol. 139(2), 99–110 (2004) 49. Gallucci, K., Jand, N., Foscolo, P.U., Santini, M.: Cold model characterisation of a fluidised bed catalytic reactor by means of instantaneous pressure measurements. Chem. Eng. J. 87(1), 61–71 (2002) 50. van der Hoef, M.A., Annaland, M.V., Deen, N.G., Kuipers, J.A.M.: Numerical simulation of dense gas-solid fluidized beds: a multiscale modeling strategy. Annu. Rev. Fluid Mech. 40, 47–70 (2008) 51. Ding, J., Gidaspow, D.: A bubbling fluidization model using kinetic-theory of granular flow. AICHE J. 36(4), 523–538 (1990) 52. Yang, N., Wang, W., Ge, W., Li, J.: Choosing structure-dependent drag coefficient in modeling gas-solid two-phase flow. China Part. 1(1), 38–41 (2003) 53. Dong, W.G., Wang, W., Li, J.H.: A multiscale mass transfer model for gas-solid riser flows: part 1 – sub-grid model and simple tests. Chem. Eng. Sci. 63(10), 2798–2810 (2008) 54. Breault, R.W.: A review of gas-solid dispersion and mass transfer coefficient correlations in circulating fluidized beds. Powder Technol. 163(1–2), 9–17 (2006) 55. Sundaresan, S.: Instabilities in fluidized beds. Annu. Rev. Fluid Mech. 35, 63–88 (2003) 56. Wang, W., Li, J.: Simulation of gas-solid two-phase flow by a multi-scale CFD approach – extension of the EMMS model to the sub-grid level. Chem. Eng. Sci. 62(1–2), 208–231 (2007)

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Chapter 3

Cold Model Experiment and Reactor Modeling

Abstract To favor desired reactions, a diameter-transformed fluidized bed reactor (DTFB) was used to create multiple zones with different reaction conditions by introducing an enlarged reaction zone in the middle of a conventional fluidized catalytic cracking reactor. The flow states or temperatures in these zones were regulated by changing the diameter-expanding ratio and introducing additional solids feedstock. This chapter introduces cold model flow experiments on two experimental set-ups of the DTFB, which were conducted to investigate the effects of primary solids flow rate, supplementary solids flow rate, and gas velocity on the flow state. The results provided a first impression of the change in hydrodynamic features caused by increasing the bed diameter and were used for model validation in further numerical studies. Because bed diameter expansion is a feasible way to build multiple reaction zones from a practical point of view, understanding the regulation of flow states in multiple zones is of great importance to establish a general DTFB platform for complex gas–solid catalytic reactions.

3.1

Experimental

To understand the hydrodynamic behavior of the diameter-transformed fluidized bed reactor (DTFB), a series of experiments were conducted using two cold model reactors built at the Institute of Process Engineering (IPE), Chinese Academy of Sciences (CAS). Compared to a conventional fluid catalytic cracking (FCC) riser reactor with a uniform cross section, the new reactors were designed to have two reactor sections, where the first section was similar to a conventional FCC riser operating at high velocity and the second section had a larger diameter with lower gas velocity and higher solids concentration to favor production of cleaner gasoline. Understanding the hydrodynamic behavior, such as the variation of solids concentration with the solids inventory, gas velocity, primary solids flow rate, and secondary solids flow rate to the second reaction zone, is important to ensure suitable design and industrial operation of such novel FCC reactors. The enlarged second reaction zone is focused on in these experiments.

© Springer Nature Switzerland AG 2020 Y. Xu et al., Diameter-Transformed Fluidized Bed, Particle Technology Series 27, https://doi.org/10.1007/978-3-030-47583-3_3

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3.1.1

3 Cold Model Experiment and Reactor Modeling

Setup I

Figure 3.1 shows the first experimental apparatus of the DTFB (Setup I). The main body of the apparatus was made of plexiglass, consisting of a riser, downcomer, three cyclone separators, hopper, silo, and diplegs. The apparatus was 13.78 m high. The riser was a combination of a conventional riser (section I) and dense circulating fluidized bed (section II) to provide two different reaction zones. The lower section was 3.15 m high with an internal diameter (ID) of 0.140 m. The upper riser section was 8.25 m high with an ID of 0.284 m. The reaction zones were connected by a diffuser with a height of 0.12 m. There were 21 pressure taps mounted on the side wall of the riser at intervals of 0.5 m; their positions are summarized in Table 3.1. A butterfly valve (8) was mounted below the discharge outlet of the first cyclone separator inside the downcomer to measure the circulating solids flux. A small column was installed 3 m from the bottom of the downcomer to control the solids downstream. The downcomer was connected to the lower riser section and the upper riser section through slanted pipes. The butterfly valves labeled 10 and 11 were mounted on the slanted pipes to regulate the solids circulating rates from the downcomer to the lower and upper riser sections, respectively. Prior to start-up of experiments, catalyst particles were stored in the silo (7). Then, valve 9 in the conveying pipe connecting the silo and downcomer was opened to let the solids flow into the downcomer. A small amount of air stream was continuously pumped into the reactor from the bottom of the downcomer to maintain particles in a fluidized state. After opening valve 10, particles entered the first section of the riser and moved upwards concurrently with the gas stream. Particles moved upwards successively through section I of the riser, diffuser, section II of the riser, and finally arrived at the hopper, where most particles fell into the downcomer; other particles were entrained into the cyclone separators and then recirculated to the downcomer through the diplegs of the first cyclone and silo. The air stream mixed with ultrafine particles out of the third cyclone was finally released to the atmosphere after being separated via the bag filter. Full-loop circulation was realized in this setup. During experiments, the air velocity was regulated by the rotameter, and the air flow rate to the downcomer was maintained at an air velocity between 0.0288 and 0.0768 m/s to keep solids particles therein fluidized. A small amount of air stream was injected into the bottom of the first cyclone separator to ensure the flowability of particles.

3.1.2

Setup II

The second experimental apparatus (Setup II), as shown in Fig. 3.2, was constructed to obtain more measurements besides pressure data. Two risers with different configurations were compared in Setup II. The left riser (A) had a height of 10.2 m,

3.1 Experimental

Fig. 3.1 Schematic diagram of Setup I of the diameter-transformed fluidized bed reactor [1]

73

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3 Cold Model Experiment and Reactor Modeling

Table 3.1 Positions of the pressure measurement points (the position of the gas distributor is labeled “0”) in the diameter-transformed fluidized bed reactor [1] No. 1 2 3 4 5 6 7 8 9 10 11 12 13

Height (mm) 205 590 1070 1520 1975 2605 3055 3335 3795 4305 4805 5340 5800

No. 14 15 16 17 18 19 20 21 22 23 24 25 26

Height (m) 6300 6800 7340 8300 8800 9395 10,645 11,145 8940 8040 1785 1185 580

encompassing section I and II with a diffuser between them. Below the diffuser was section I with an ID of 45 mm and height of 3.94 m; above the conical diffuser was section II with an ID of 90 mm and height of 6.2 m. Compared to the first riser on the left, the second riser shown on the right of Fig. 3.2 has a different structure, in which the enlarged section II above the diffuser was shortened to a height of 2 m and connected to the upper thinner lifting tube with a height of 4.2 m and ID of 45 mm. The downcomer (B) was 10.5 m high with an ID of 120 mm The upper circulating dipleg and top downcomer (8.3 m above the base) were equipped with perforated-plate valves D1 and D2 covered by wire mesh to measuring the circulating solids fluxes Gs2 and Gs1, respectively. Twenty-five pressure taps were mounted along the circulating loop of the reactor and connected to 24 pressure transducers to collect pressure data. More details can be found elsewhere [2]. The measurement of pressure drops with operating conditions was similar to that in the first apparatus [2, 3]. Four measuring points for optical fiber probes were opened in the riser at elevations of 2.34, 4.30, 5.63 and 7.77 m, as shown in Fig. 3.2. Some of the measuring points were set near the wall, where the solids flux and particle velocity varied remarkably with position. The air stream entering the riser was provided by a blower (H) and the air flow rate was regulated by a control valve (G) and measured with a rotameter (F). Valves E1 and E2 for regulating the circulating solids flux from the downcomer to section I and section II, respectively (denoted as Gs1 and Gs2, respectively) were mounted on two slanted diplegs. In the riser, particles and air flowed upward concurrently to the top and then the particles were recirculated to the riser again after being separated from the cyclones. It should be noted that at an elevation of 5.25 m above the base inside the downcomer, an eccentric tube (C) with a height of 2.0 m and ID of 70 mm was installed to form a feeding bed to provide solids particles to section II. This bed operated in two

3.1 Experimental

75

Fig. 3.2 Schematic diagram of the second diameter-transformed fluidized bed reactor (Setup II)

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3 Cold Model Experiment and Reactor Modeling

different states, i.e., a moving bed state and a fluidized bed state. During experiments, most of the particles collected from the cyclones fell into the feeding bed and quickly filled up the bed; remaining particles together with the overflowing particles moved downward to the bottom of the downcomer to feed section I. In the above dual-loop fluidized bed apparatus, the circulating loop through section I is the primary loop and the other through section II is the secondary or supplementary loop. The introduction of the secondary loop can further increase the solids concentration in section II of the riser by increasing the supplementary solids feed rate. However, this design makes it difficult to control the pressure balance of the entire system. To achieve a good initial distribution of solids and gas flow in section II, a perforated plate distributor was installed above the diffuser. Because the opening ratio of the distributor is closely related to operation stability and solids distribution [2, 3], it was investigated in experiments. One distributor with an opening ratio of 14.82% contained 48 uniformly distributed orifices with an ID of 5 mm and the other distributor with an opening ratio of 8.33% contained 27 orifices with an ID of 5 mm.

3.1.3

Experimental Conditions

3.1.3.1

Setup I

Experiments using Setup I were performed at ambient pressure and temperature. Compressed air was used as the fluidization medium with a density of 1.205 kg/m3 and viscosity of 1.81
105 Pas at 20  C and ambient pressure. The solid particles were zeolite catalysts used in FCC processes at Sinopec Zhenhai Refining & Chemical Company. The particles were white, spherical, and possessed an incipient fluidization velocity of about 0.007 m/s and terminal velocity between 0.34 and 0.7 m/s. A series of density tests were conducted and related data are listed in Table 3.2. The particle size distribution is summarized in Table 3.3, from which we know that about 90% of particles were in the size range of 45–125 μm and the mean particle diameter was about 70.61 μm. Table 3.4 summarizes the operating conditions of the experiments conducted using Setup I.

Table 3.2 Physical properties of solid particles (unit: g/mL) Skeletal density 2.31

Particle density 1.727

Closely packed density 0.95

Loosely packed density 0.84

Settled bulk density 0.89

3.1 Experimental

77

Table 3.3 Particle size distribution [1] Particle diameter (μm) 0 ~ 45 45 ~ 56 56 ~ 80 80 ~ 100 100 ~ 125 125 ~ 175 >175

Mass fraction (%) 4.60 13.8 26.0 34.3 15.1 5.70 0.50

Table 3.4 Operating conditions for experiments using Setup I [1] Solids inventory (kg) 320

410

460

Superficial gas velocity in riser, m/s Section I Section II 5 1.22 12 2.92 15 3.65 12 2.92 15 3.65 16 3.91 12 2.92

Solids circulating rate, t/h Ws1 Ws2 0.15 ~ 1.46 0.61 3.77 ~ 7.00 0.61 ~ 0.91 1.17 ~ 5.13 – 6.55 ~ 15.23 0.18 ~ 11.95 18.08 1.29 17.49 ~ 20.08 2.84 ~ 4.57 14.32 0 ~ 5.81

Fig. 3.3 Particle size distribution of FCC catalysts used in Setup II [3]

3.1.3.2

Setup II

The physical properties of solid particles used in Setup II were similar to those used in Setup I. The solid particles had a mean diameter of 82 μm and density of 1450 kg/m3. The particle size distribution was measured by a Coulter-Ls230 particle size analyzer, as shown in Fig. 3.3. Compressed air with a density of 1.29 kg/m3 and viscosity of 1.81
105 Pas was used to fluidize the solid particles.

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The total solids inventory in Setup II was about 25 kg. The superficial gas velocity in section I of the riser was regulated from 4 to 14 m/s and the superficial gas velocity in section II of the riser was varied from 1.25 to 3.5 m/s. The primary solids flow rate (Ws1), which was fed to section I, was varied from 3.9 to 19 kg/min and the secondary solids flow rate (Ws2), which was fed to section II, was regulated from 0 to 2.9 kg/min.

3.2 3.2.1

Measurement Methods Pressure Drop

Manometers connected to pressure taps by plastic tubes were used to measure the pressure drops. Apparent cross-sectional average voidage was obtained by calculating the average pressure drops between two adjacent taps along the riser neglecting acceleration and friction effects. The related equations are written as follows: ρb ¼ εg ¼ 1 

ΔP gΔL

ΔP gΔLðρp  ρg Þ

ð3:1Þ ð3:2Þ

Here, ρb is the average bed density, ΔP is the pressure drop, εg is the apparent crosssectional average voidage, ρp is particle density, ρg is gas density, and ΔL is the distance between two pressure taps.

3.2.2

Local Solids Concentration and Velocity

An optical fiber system (Particle Velometer PV-4A, IPE, CAS) was mounted on Setup II to measure local particle velocity and voidage simultaneously in terms of their time series fluctuation. The optical fiber system consisted of an optical fiber probe, photomultiplier, and data acquisition unit. The optical fiber probe tip possessed an outer diameter of 3.8 mm and two bundles of fibers. Each bundle consisted of 8000 small optical fibers with a tip diameter of 15 μm to emit and receive light arranged in an alternating manner. The probe was mounted with its face perpendicular to the direction of flow and illuminated a measuring volume of particles. The light reflected by particles was captured by the light-receiving system and processed by the photomultiplier. The light intensity was converted into a voltage signal and then amplified and fed into a personal computer for data acquisition and storage.

3.2 Measurement Methods

79

Finally, the voltage signal was converted into solids volume fraction using a calibration relation based on the method developed by Zhang et al. [3], as follows: εg ¼ 1  0:0264W 1:4999 , R2 ¼ 0:9795

ð3:3Þ

Particle velocity was determined by cross-correlation analysis of signals [4]. Calibration of the solids velocity probes was performed to find the effective distance between the light-emitting and light-receiving fibers. Here, the electric signals from the two fibers with a real-time hardware processor and probe were precisely calibrated using a rotating disk device [5]. The reflected light intensity, which was correlated with the solids concentration within the irradiated volume, was integrated over time so that a quantitative measure of the local solids concentration was achieved with prior accurate calibration. To measure the solids concentration, the optical fiber probe was inserted into the column horizontally and moved across the column cross section. At each elevation (H ¼ 2.34, 4.30, 5.63, and 7.77 m), measurements were conducted at eleven radial positions (r/R ¼ 0, 0.158, 0.382, 0.497, 0.59, 0.67, 0.741, 0.806, 0.866, 0.922, and 0.974, where r is the distance from the center and R is the riser radius). These radial positions were selected by dividing the cross section of the column into ten concentric rings of equal size and determining the median diameter of each ring. The crosssectionally averaged value was obtained by averaging the data at the ten measurement points except the central point. To measure the solids velocities, the optical fiber probe was rotated so that the two bundles of fibers were arranged in the same direction as the upflow and then put into the riser through the hole. After placing the probe at the measurement points and prescribing the sampling frequency and time, the local instantaneous solids velocity, mean velocity of upflowing particles, mean velocity of downflowing particles, and overall mean velocity of solids were obtained through data processing. Because of the non-uniform distribution of solids concentration, the cross-sectionally averaged solids velocity was determined by: up ¼

X10 1

up ε s =

10 X

εs

ð3:4Þ

1

For different operating gas velocities, the frequency and time step of sampling were adjusted to ensure that the detailed dynamic nature of the flow could be fully captured. All measurements were repeated at least five times to obtain reasonable and reproducible data. The settings are listed in detail in Table 3.5. Table 3.5 Frequency and time step of sampling by the optical fiber probe Superficial gas velocity (m/s) 5 8 10,12 14

Sampling frequency (kHz) 31.25 62.5 125 500

Time step of sampling (ms) 1040 524.28 262.14 65.53

Sampling number 32,768 32,768 32,768 32,768

80

3 Cold Model Experiment and Reactor Modeling

Fig. 3.4 Relationship between Gst, Gs1, and Gs2 (kg/(m2s)), which are the overall solids flux, solids flux in section I, and solids flux in section II, respectively

3.2.3

Solids Circulation Rate

As shown in Fig. 3.2, a butterfly valve similar to a perforated plate was mounted on the upper downcomer of the second apparatus to measure the solids flow rate. When the apparatus was operated in a steady state, the valve D2 could be closed and then a volume of particles gradually accumulated on this valve. The solids flow rate was then determined by measuring the mass and height of particles accumulated during a certain period of time as well as the corresponding pressure drop. Using Eqs. (3.5), (3.6), (3.7), (3.8), (3.9), and (3.10), different solids circulation rates were calculated and their relationship is shown in Fig. 3.4. W s1 ¼ A2 

Δh ΔP2524  Δt gΔH 2524

ð3:5Þ

W st ¼ A2 

Δh ΔP2322  Δt gΔH 2322

ð3:6Þ

W s2 ¼ W st  W s1

ð3:7Þ

Gs1 ¼

W s1 AI

ð3:8Þ

Gst ¼

W st AII

ð3:9Þ

Gs2 ¼

W s2 AII

ð3:10Þ

3.3 Results and Discussion

81

where Wst, Ws1, and Ws2 (t/h) are the overall solids circulation rate, solids circulation rate through section I of the riser, and solids circulation rate through section II of the riser, respectively; Gst, Gs1, and Gs2 (kg/(m2s)) are the overall solids flux, solids flux in section I, and solids flux in section II, respectively; A2 is the cross-sectional area of the downcomer; AI is the cross-sectional area of the riser in section I; AII is the crosssectional area of the riser in section II; Δh is the height of particles collected on the valve; Δt is the time to form a pile of solid particles with a height of Δh above the valve; ΔP25  24 represents the pressure drop between measurement points 25 and 24; and ΔH25  24 denotes the distance between points 25 and 24.

3.3

Results and Discussion

The following symbols are introduced to aid discussion. Because the riser was operated at a relatively high gas velocity compared to that of the downcomer, we called it a fast bed and used F as the subscript to represent the riser. Therefore, QF denotes the volumetric gas flow rate to the riser, UF1 is the superficial gas velocity for section I of the riser, and UF2 is the superficial gas velocity for section II of the riser. The downcomer was operated at a lower gas velocity, so we used L as the subscript representing the downcomer. Here, QL and UL are the volumetric flow rate of gas and superficial gas velocity in the downcomer, respectively.

3.3.1

Effect of Primary Solids Flux

The influence of the primary solids flux Gs1 on the performance of Setup I was experimentally investigated. The operating gas velocity for section I of the riser was set at 5 m/s and the secondary solids feed was stopped (Gs2 ¼ 0) to mimic the startup state of the system before reaching a steady state. Then, the primary solids flux was gradually increased by gradually opening valve 10. The resulting variation of axial voidage profiles was collected and is depicted in Fig. 3.5. An increase of Gs1 from 2.8 to 46.7 kg/(m2s) markedly changed the solids holdup. In the riser in section I, the dilute transport state (εg  0.99) gradually shifted to fully dense transport (εg  0.91). Compared with that in section I, the solids concentration in section II had a much greater effect on Gs1 because of the lower gas velocity (UF2 ¼ 1.22 m/s). In the riser in section II, the voidage varied considerably in the axial direction, forming a dense bottom. In contrast, the voidage decreased greatly with increasing Gs1, especially in the diffuser (H ¼ 3.15–3.27 m), where the voidage decreased from 0.99 to 0.5. The height of the dense bottom in section II increased up to about 4.5 m when Gs1 was 46.7 kg/(m2s) and the bed height tended to oscillate drastically, leading to a big increase in the overall pressure drop of the riser. When Gs1 was greater than 26.4 kg/(m2s), the formation of a dense bottom was readily detected and the height of the dense bottom rose quickly with increasing Gs1.

82

3 Cold Model Experiment and Reactor Modeling

Fig. 3.5 Axial voidage profiles for Setup I with different primary solids circulation rates at UF1 ¼ 5 m/s (Gs2 ¼ 0) [1]

The gas velocity in an FCC riser may exceed 10 m/s. Thus, the effect of primary solids flux on the axial distribution of voidage at a higher gas velocity (UF1 ¼ 12 m/s, UF2 ¼ 2.92 m/s) was investigated. Figure 3.6 presents a series of axial profiles of solids concentration at Gs1 ranging from 68.1 to 355.9 kg/(m2s). An abrupt increase in solids concentration was observed at the bottom of section II (above H ¼ 3.27 m) when the primary solids flux Gs1 was about 68.1 kg/(m2s). The increase of Gs1 simultaneously changed the axial distribution of solids concentration in both section I and section II. The abrupt increase in solids concentration is caused by the expansion of bed diameter, and the highest solids concentration roughly appears in the diffuser. Above 4 m, it became difficult to accumulate particles when Gs1 was increased from 68.1 to 274.9 kg/(m2s). When Gs1 was increased to 355.9 kg/(m2s), a remarkable increase in solids concentration above 4 m was detected. Overall, the variation of the axial profile of solids concentration in both section I and section II with Gs1 was irregular and it was difficult to form a steady dense region in section II. Figure 3.7 shows the cross-sectionally averaged solids concentration at a height of 3 m with different Gs1. As Gs1 increases, the solids concentration at this position generally increased; however, some oscillations around the fitting line were detected. These oscillations were largely caused by the bed expansion above a height of 3 m, as shown in Fig. 3.1.

3.3 Results and Discussion

83

Fig. 3.6 Influence of the primary solids feed rate on axial profiles of voidage at UF1 ¼ 12 m/s (Gs2 ¼ 0) [1]

To examine the formation of a dense bed in section II, Fig. 3.8 shows the variation of cross-sectionally averaged solids concentration with the primary solids flux above a height of 3.5 m. At a height of 3.5 m, for almost the whole range of Gs1 from 68.1 to 355.9 kg/(m2s), the solids concentration reached a certain high value above 0.2. At a higher position, i.e., H ¼ 4 m, the solids concentration exceeding 0.2 only appeared at a larger Gs, e.g., 355.9 kg/(m2s), inferring that in the Setup I, it is difficult to form a certain height of dense bottom by only increasing the primary solids flux.

84

3 Cold Model Experiment and Reactor Modeling

Fig. 3.7 Variation of solids concentration at a height of 3 m with the primary solids flux at UF1 ¼ 12 m/s (Gs2 ¼ 0) [1]

Fig. 3.8 Variation of solids concentration with primary solids flux at a height of 3 m (UF1 ¼ 12 m/s, Gs2 ¼ 0) [1]

3.3.2

Effect of Supplementary Solids Feed Rate

When fixing the gas velocity and primary solids flux, i.e., UF1 ¼ 12 m/s (UF2 ¼ 2.92 m/s) and Gs1 ¼ 258.4 kg/(m2s), the variation of axial distribution of solids concentration with supplementary solids feed can be obtained, as shown in Fig. 3.9. The supplementary solids feed rate to section II strongly affected the formation of the dense bed in section II. As Gs2 increased up to 25.5 kg/(m2s), the mean solids concentration at heights between 4 and 6 m increased by 0.1. Meanwhile, the increase of Gs2 diluted the solids flow in the first section. Because the solids concentration was converted from the pressure data obtained experimentally, as described in Sect. 3.2, we could infer that the above phenomenon is largely related to the concentration measurement error caused by the drastic variation of solids

3.3 Results and Discussion

85

Fig. 3.9 Axial profiles of voidage at different secondary solids fluxes (UF1 ¼ 12 m/s, UF2 ¼ 2.92 m/s, Gs1 ¼ 258.4 kg/(m2s)) [1]

velocity. We believe that the solids entering section II through the slanted pipeline first move downwards, proceed a certain distance without blocking from the distributor, and then mix with upflowing particles and gas stream, resulting a drastic change in velocity. Therefore, the pressure data measured at those positions include the contributions from particle collision and acceleration/deceleration, leading to a big error of the solids concentration calculated using Eqs. (3.1) and (3.2). Such a phenomenon was not observed in experiments on the second DTFB with a perforated plate distributor above the diffuser [3]. Figure 3.10 depicts the variation of axial profiles of solids concentration with the secondary solids flux at a lower primary solids flux of Gs1 ¼ 118.2 kg/(m2s) with UF1 ¼ 12 m/s. The behavior in Fig. 3.10 is similar to that in Fig. 3.9. Figure 3.11 shows the variation in the mean solids concentration of section II with the secondary solids flux at two different Gs1. At the larger primary solids flux, i.e., Gs1 ¼ 274.9 kg/(m2s), the voidage in section II decreased from about 0.924 to 0.894 when Gs2 was increased from 0 to 17.3 kg/(m2s). At the smaller primary solid flux, i.e., Gs1 ¼ 118.2 kg/(m2s), the increase of Gs2 contributed weakly to the densification of the solids flow when Gs2 was below about 17.3 kg/(m2s) and then the influence of Gs2 became stronger. In general, introduction of supplementary solids feed is an effective approach to form a dense bottom and increase the mean solids concentration in section II.

86

3 Cold Model Experiment and Reactor Modeling

Fig. 3.10 Axial profiles of voidage at different secondary solids fluxes (UF1 ¼ 12 m/s, UF2 ¼ 2.92 m/s, Gs1 ¼ 118.2 kg/(m2s)) [1]

Fig. 3.11 Effect of the secondary solids flux on the solids concentration in section II at two different specified Gs1 (UF1 ¼ 12 m/s, UF2 ¼ 2.92 m/s) [1]

3.3.3

Effect of Gas Velocity

The effect of gas velocity on the axial profile of solids concentration is shown in Fig. 3.12. For the three considered cases with different operating gas velocities, the secondary solids feed was stopped (Gs2 ¼ 0). The measured primary solids feed rate

3.3 Results and Discussion

87

Fig. 3.12 Axial profiles of voidage at different gas velocities (UF1 ¼ 12 m/s, UF2 ¼ 2.92 m/s, Gs1 ¼ 355.9 kg/(m2s); UF1 ¼ 15 m/s, UF2 ¼ 3.65 m/s, Gs1 ¼ 326.3 kg/(m2s); UF1 ¼ 16 m/s, UF2 ¼ 3.91 m/s, Gs1 ¼ 375.8 kg/(m2s)) [1]

varied within a narrow range with increasing gas velocity because it was difficult to keep the primary solid feed rate constant during the regulation process of the gas stream. Figure 3.12 reveals that increasing the gas velocity from 12 to 16 m/s strongly diluted the solids flow in the first and second sections of the riser, thus decreasing the overall bed pressure drop (ΔPt). At the top of the riser, the three cases with different operating gas velocities showed similar dilute solids flow with a voidage of about 0.99.

3.3.4

Radial Distribution of Solids Velocity

Local solids concentration and velocity were measured in the second DTFB (Setup II), which is shown in Fig. 3.2. In a concurrent upward gas–solid riser, flow structures are heterogeneous and unsteady. Particles move in all directions under the combined effects of gas–solid interactions, solid–solid collision, and solid–wall friction, and considerable downflow of solids can be found, especially near the wall. Schut et al. [6] analyzed trajectories of particles and a cluster containing 20 FCC particles in a diffuser. They concluded that neither particles nor the cluster trajectory followed the gas streamlines and their inertia caused the solids to move upwards in vertical paths rather than follow the gas streamlines. Marjanovic et al. [7] pointed out

88

3 Cold Model Experiment and Reactor Modeling

Fig. 3.13 Radial profiles of particle velocity at four elevations (UF1 ¼ 10 m/s, UF2 ¼ 2.5 m/s, Ws1 ¼ 4.7 kg/min, Ws2 ¼ 0.7 kg/min) [3]

that complex flow structures through the diffuser are caused by the difference between the gas and solids velocities as well as the momentum exchange between them. Figure 3.13 shows radial profiles of solids velocities at different elevations in Setup II. It was found that a core–annulus structure appeared at each cross section at different elevations, in which the solids velocity decreased from the center to the wall, showing the minimum velocity in the vicinity of the wall and maximum in the center of the riser. At a height of 2.34 m (in section I), the velocity difference between the center and near the wall of the riser was remarkable. All the particle velocities in section I were positive, although some were close to zero near the wall. By comparison, the particle velocity in section II (H ¼ 4.3, 5.63, and 7.77 m) varied gently along the radial direction and the axial particle velocity decreased sharply because of the bed expansion. At a lower position in section II (H ¼ 4.3 m, just above the diffuser), the inertia caused particles to possess high velocity, whereas the gas velocity decreased to 25% of that in section I, leading to the separation of two phases. The particle velocity at this elevation was distinctly higher than those at higher elevations in section II, and no negative particle velocity was detected near the wall. The particle vertical velocity lowered further with increasing height (H ¼ 5.63 and 7.77 m) and became negative along the wall because the gas velocity decreased so much that it did not provide adequate drag force to counterbalance the particle gravity and particle–wall friction. The effect of secondary solids feed was then investigated at fixed gas velocity (UF1 ¼ 10 m/s) and primary solids feed rate (Ws1 ¼ 4.7 kg/min). As shown in Fig. 3.14, the particle velocity in section I (H ¼ 2.34 m) remained almost unchanged at different Gs2. Just above the diffuser, i.e., H ¼ 4.30 m, particle velocity decreases remarkably with increasing Gs2. The decrease of particle velocity was more pronounced in the core region than near the wall. When H ¼ 7.77 m, particle velocities at different Gs2 were similar to each other, indicating a fully developed flow.

3.3 Results and Discussion

89

Fig. 3.14 The effect of the secondary solids feed rate on the radial profile of particle velocity at different elevations (UF1 ¼ 10 m/s, UF2 ¼ 2.5 m/s, Ws1 ¼ 4.7 kg/min) [3]

3.3.5

Radial Distribution of Solids Concentration

Extensive studies in the literature have reported that core–annulus structure prevails in all cross sections of a riser where particles migrate from the core towards the riser wall and then fall down along the wall as clusters, streamers, sheets, or films in the annulus against the upward flow, creating the internal recirculation of particles. Our experiments also showed that such a core–annulus structure formed primarily in section II of the riser, as plotted in Fig. 3.15. The radial voidage profile was relatively flat in the core and the voidage decreased sharply towards the wall in the annulus, with lowest voidage observed in the vicinity of the wall. At a height of 2.34 m in section I, the core–annulus structure was not very obvious because the voidage in the core was high and then decreased sharply near the wall. At this elevation, the gas– solid flow operated in the pneumatic conveying regime with a superficial gas velocity of 10 m/s and particle velocity greater than 13 m/s in the core region, resulting in extremely dilute flow in the center coexisting with a thin layer of dense

90

3 Cold Model Experiment and Reactor Modeling

Fig. 3.15 Radial voidage profiles at four elevations (UF1 ¼ 10 m/s, UF2 ¼ 2.5 m/ s, Ws1 ¼ 4.7 kg/min, Ws2 ¼ 0.7 kg/min) [3]

annulus. Just above the diffuser (H ¼ 4.30 m), the solids concentration in the core region increased evidently compared to that in section I. The decrease of gas velocity and the secondary solids feed to section II resulted in such an increase of solids concentration. Because of the abrupt bed expansion, the gas velocity decreased instantly, whereas the inertia caused the particles to keep their velocity for a while, leading to the occurrence of phase separation and strong reflux. Voidage in the annulus was much higher than those at heights of 5.63 and 7.77 m. As the height increased up to 5.63 and 7.77 m, the voidages in the core region of both cross sections approached each other but showed a big difference in the annulus region. At a height of 7.77 m, the voidage remained almost constant near the wall. In section II, the size of the core region with higher voidage decreased whereas the size of the annulus region with lower voidage increased with rising height, which was remarkably different behavior from that of a conventional riser. At the same gas velocity (UF1) and primary solids feed rate (Ws1), radial voidage profiles at four elevations in the riser were investigated. The influence of secondary feed rate (Ws2) on the radial voidage profile is shown in Fig. 3.16. At a height of 2.34 m, where the gas–solid mixture was in the pneumatic conveying regime with a superficial gas velocity of 10 m/s, Gs2 had only a slight influence on voidage. Just above the diffuser (H ¼ 4.30 m), voidage decreased with increasing Ws2 and showed strong fluctuation. At this elevation, particle velocity decreased and average solids flux increased with rising secondary solids feed rate, leading to much lower voidage. The voidage decreased from 0.995 to 0.942 in the core and from 0.860 to 0.839 near the wall when Ws2 was increased from 0 to 2.1 kg/min. As the height increased, the radial voidage profiles showed much smaller fluctuation and gradually become similar. From the above discussion, the influence of the diffuser and secondary solids feed rate on the radial distribution of voidage gradually weakened with increasing height. The voidage at each axial elevation increased with increasing gas velocity and

3.4 Theoretical Modeling

91

Fig. 3.16 Effect of the secondary solids feed rate on the radial voidage profiles at different elevations (UF1 ¼ 10 m/s, UF2 ¼ 2.5 m/s, Ws1 ¼ 4.7 kg/min) [3]

decreasing solids circulation rate, similar to the behavior in a conventional riser,. The trends in section II shows pronounced differences from those in a conventional riser; that is, the area of the core region decreased with increasing height and showed more complex hydrodynamics in the vicinity of the diffuser.

3.4 3.4.1

Theoretical Modeling Industrial DTFB Settings and Conditions

Based on extensive experiments and empirical knowledge, an industrial-scale DTFB for the maximizing isoparaffins (MIP) process was designed and constructed in Gaoqiao, Shanghai in 2003. A schematic of the DTFB is shown in Fig. 3.17. This riser reactor could be divided into four parts from bottom to top according to their functions; i.e., the pre-lift zone (section I), feedstock injection zone (section II),

Fig. 3.17 The schematic diagram of the plant-scale DTFB used to optimize MIP processes

3.4 Theoretical Modeling

93

enlarged reaction zone (section III), and quenching or outlet zone (section IV). In the pre-lift zone, hot catalysts from the regenerator were conveyed by the pre-lift gas with a gas velocity of 2 m/s and solids flow rate of 380 kg/s. In the feedstock injection zone, hot feeding oil was sprayed into the reactor through the nozzle and contacted with the hot catalyst particles, initiating rapid reactions and causing the gas volume to increase along with a large variation in gas velocity from zero to 16.5 m/s induced by the formation of lower-molecular-weight products. In the reaction zone (section III), because of the enlargement of bed diameter and supplementary supply of solid catalysts, the solids flow was densified to favor the production of more isoparaffins through alkene isomerization and hydrogen transfer reactions. The mass flow rate of supplementary solid catalysts was regulated in the range of 380–580 kg/s in experiments. After complete reaction, the product gas quickly left the riser through the quenching zone (section IV) with a smaller cross section. Catalyst particles leaving the riser entered the sedimentation vessel and underwent two-stage separation through the cyclones. They were then pressed into the regenerator for reactivation and finally returned to the riser through the slanted standpipe. To improve this design, Cheng [8] extended the energy-minimization multiscale (EMMS) model proposed by Li and Kwauk [9] by introducing a two-dimensional steady-state distribution of parameters into the model, which thus enabled prediction of the radial and axial profiles of solids concentration. Below we detail the results under different operating conditions obtained using this extended steady-state EMMS model to search for a reasonable range of operating parameters and bed dimensions. In practical calculations, the particle density of FCC catalyst was set to 1400 kg/m3 and the Sauter mean particle size was 60 μm. The gas density and viscosity were set at 2.89 kg/m3 and 1.76
105 Pas, respectively, which were obtained at a realistic operating temperature (490–500  C). The mass flow rate of solids to the bottom of riser was 380 kg/s and three solid feed rates to the expanded zone (section III), i.e., 0, 100, and 200 kg/s, were investigated. Because no reactions were considered in the calculations, to mimic the variation of gas velocity in industrial operation caused by the cracking reaction, especially in section II, the gas velocity in section I and at the inlet of section II were set to 2 and 5 m/s, respectively, and the gas velocity at the outlet of section II (Ug2) was regulated from low velocity (i.e., 5 m/s) to high velocity (i.e., 15 and 16.5 m/s). Here, Ug2 ¼ 5 m/s represents a typical initial state and Ug2 ¼ 15 m/s corresponds to the conventional running state in industrial operation. The aim of the calculations was to predict the concentration of catalyst particles in all sections of the riser as well as the operation range of superficial gas velocity, especially in the expanded reaction zone (section III). Cheng [8] firstly analyzed the pressure drop balance of the system and obtained the following relationship between different pressure drops: Δpr ¼ Δpdf þ Δpdc þ Δpc

ð3:11Þ

94

3 Cold Model Experiment and Reactor Modeling

Here, Δpr represents the static pressure drop of the riser, Δpdf is the static pressure drop of the dilute phase of the regenerator, Δpdc is the static pressure drop of the dense phase of the regenerator, and Δpc is the additional pressure drop associated with geometries of the regenerator, overall solids inventory, and riser as well as the slide valve in the slanted standpipe. The pressure balance of a given DFTB system was realized by regulating the slide valve. If the overall solids inventory was kept constant, varying the opening of the slide valve regulated the axial pressure drop of the riser.

3.4.2

Results and Discussion

3.4.2.1

Choking Prediction and Flow Regime Analysis

Identification of the flow regime is important for industrial operation of risers. In a typical riser flow, Li and Kwauk [9] described the “choking” phenomenon as a flow regime transition, at which the flow state is sensitive to the variation of operating conditions. In greater detail, a bell-shaped region characterized by an axial “Sshaped” voidage profile, where a dilute top coexists with a dense bottom, may abruptly change to dense transport or dilute flow if the gas velocity or solids circulating rate is adjusted only a little. At the choking point, the solids flux remains almost constant as the solids inventory varies. This solids flux was defined as the saturation carrying capacity (K) along with the relevant superficial gas velocity being defined as the choking velocity (Uck). When physical properties of gas and solid particles are fixed, Uck can be determined at a known solids flux (Gs) and K can be determined at a known operating velocity Ug. In the intrinsic flow regime diagram determined purely by hydrodynamics, the S-shaped coexistence of the dilute top and dense bottom regions can only be found at the choking point. In other regimes, either all-dense or all-dilute flow prevails throughout the riser. However, the flow behavior of a practical reactor also depends on geometric factors such as the inlet/outlet dimensions or riser height. As a result, an S-shaped axial profile may be found over a much wider range of operating conditions than those at the choking point. Such a regime is sometimes termed fast fluidization or even turbulent fluidization, although its range is rather ambiguous because geometric factors can vary greatly between systems [10, 11]. In practice, an S-shaped voidage profile is a reasonable indicator that operating conditions are near the predicted choking state. Table 3.6 summarizes the calculated conditions for choking in terms of Uck and K using the original steady-state EMMS model developed by Li and Kwauk [9]. Because the bed diameter varied in different sections, the choking velocity differed accordingly. To overcome this complexity, calculations based on the original EMMS model were performed for four separate sections marked I–IV in Fig. 3.17. Here, Ug denotes the operating gas velocity and Gs denotes the solids flux for each section, which was determined from the solids feed rate divided by the

8.65

597.3

5 ~ 15

6.03

2

8.65

597.3

5 ~ 16.5

6.03

The gas velocity at the outlet of section II, Ug2 ¼ 16.5 m/s

2

Section I Section II Ug Uck Gs Ug Uck m/s m/s kg/(m2s) m/s m/s The gas velocity at the outlet of section II, Ug2 ¼ 5 m/s 2 8.65 597.3 5~5 6.03 The gas velocity at the outlet of section II, Ug2 ¼ 15 m/s

286.3

2.72

2.48

0 100 200 0 100 200

0.83

0

286.3

286.3

Section III ΔW3 Ug kg/s m/s

Gs kg/(m2s)

47.2 59.7 72.1

47.2 59.7 72.1

47.2

Gs kg/(m2s)

53.8 53.8 53.8

43.8 43.8 43.8

4.33

K kg/(m2s)

19.4

17.6

5.87

6.51 7.30 8.02

6.51 7.30 8.02

6.51

Section IV Ug Uck m/s m/s

336 424.4 512.8

336 424.4 512.8

336

Gs kg/(m2s)

Table 3.6 Operating parameters for each section of a DTFB as well as the calculated choking gas velocity (Uck) and saturation carrying capacity (K) [8]

3.4 Theoretical Modeling 95

96

3 Cold Model Experiment and Reactor Modeling

cross-sectional area of each section (the calculation of solids flux for section III and IV also needed to consider the supplementary solids feed rate). The predicted choking velocity in section I was about 8.65 m/s, which was much higher than the operating gas velocity of 2 m/s. Therefore, the gas–solid flow in section I was typical of the dense fluidization regime. Because of the occurrence of catalytic cracking reactions, the gas velocity in section II in industrial operation varied from a low velocity at the entrance of section II to a much higher gas velocity at its outlet. Therefore, three cases with different Ug2, i.e., 5, 15, and 16.5 m/s, were investigated in these calculations; the results are presented in Table 3.6. The predicted choking velocity for section II was about 6.03 m/s. For section III, when the gas velocity was 5 m/s, the predicted K, i.e., 4.33 kg/(m2s), was much lower than the solids flux of 47.2 kg/(m2s), and therefore we can infer that section III operates in the dense flow regime. When the gas velocity was 15 m/s, the predicted K was about 43.8 kg/(m2s) without the supplementary catalyst feed (ΔW3 ¼ 0), which was close to the operating solids flux of 47.2 kg/(m2s). Thus, an S-shaped profile of solids concentration arose in section III. For larger ΔW3, i.e., 100 and 200 kg/s, because the corresponding solids flux was much larger than K, we can infer that the dense flow regime will form in section III. Likewise, when the gas velocity was 16.5 m/s, the predicted K of 53.8 kg/(m2s) was close to the operating solids flux with ΔW3 smaller than 200 kg/s. Therefore, only the case with ΔW3 ¼ 200 kg/s operated in the dense fluidization regime and the other two cases operated in the fast fluidization regime with S-shaped profiles. Similarly, for section IV, dilute transport prevailed for gas velocities of 15 and 16.5 m/s, whereas dense flow was observed in the initial period with low gas velocity.

3.4.2.2

Distribution of Solids Concentration at Different Operating Conditions

Using the extended steady-state EMMS model developed by Cheng [8], we can obtain the axial and radial profiles of solids concentration in each section as well as the corresponding pressure drop in the DTFB. During the start-up, no reactions occurred, so the gas velocity of 5 m/s in section II did not vary with height. According to the choking prediction presented in Table 3.6, we know that the operating gas velocities in all sections were lower than the choking velocity; thereby it was determined that the whole reactor operated in the dense fluidization regime. During the start-up, the supplementary solids feed to the expanded zone (section III) was stopped (ΔW3 ¼ 0) and the pressure drop over section III was relatively large because of the formation of a dense flow state. The impetus was not sufficient to carry the particles out of section III, thus a bubbling bed with a dense region at a certain height, i.e., about 2.87 m, formed. In this state, the calculated backmixing flux was about 232 kg/(m2s), which was much higher than the external circulating solids flux of 47.2 kg/(m2s). Figure 3.18 presents the axial profiles of solids density throughout the entire reactor. It can be seen that all sections showed an even distribution of solids concentration.

3.4 Theoretical Modeling

97

Fig. 3.18 Calculated axial profile of the bed density in section III with a solids inventory of 10 t (Ug2 ¼ 5 m/s, ΔW3 ¼ 0) [8]

During normal operation, the gas volume expanded because of the interphase heat transfer and reactions, so the gas velocity at the outlet of section II was much higher than that at the entrance, reaching 15 m/s or even higher. At Ug2 ¼ 15 m/s, three cases with different supplementary solids feed rates (ΔW3) were analyzed. When ΔW3 ¼ 0, according to Table 3.6, the solids flux throughout the expanded zone (section III) was about 47.2 m/s, which is close to the corresponding K of 43.8 kg/ (m2s). Therefore, the solids concentration along the height of section III showed an S-shaped profile. The height of the dense bottom of the S-shaped profile was determined by the overall pressure drop of the riser and the cross-sectional average solids concentration and backmixing solids flux were obtained. Table 3.7 summarizes the relationship between the height of the dense bottom, cross-sectional average bed density, overall pressure drop, and solids inventory of section III calculated using the extended steady-state EMMS model [8] at Ug2 ¼ 15 m/s and ΔW3 ¼ 0. The mean solids concentration and pressure drop of the expanded section (section III) could be changed by regulation of the slide valve; however, the solids concentration and pressure drop of other sections remained almost unchanged, as listed in Table 3.8. The overall pressure drop of the DTFB was controlled by regulating the slide valve and further influenced the solids distribution of section III. Taking the case with a solids inventory of 10 t in section III as an example, the calculated axial profile of bed density is shown in Fig. 3.19. A dense flow formed in section I and then quickly turned into a dilute flow in section II because of the rapid increase of gas velocity. Arriving at the expanded section (section III), the gas velocity decreased because of diameter expansion and the solids flux approached K (as presented in

98

3 Cold Model Experiment and Reactor Modeling

Table 3.7 Relationship between the height of the dense bottom, voidage, and overall pressure drop of section III (Ug2 ¼ 15 m/s, ΔW3 ¼ 0) [8] Height of dense region (m) 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0

Cross-sectional average voidage 0.9367 0.9315 0.9249 0.9161 0.9080 0.9008 0.8936 0.8864 0.8791 0.8753 0.8647

Cross-sectional average bed density (kg/m3) 88.60 95.83 105.18 117.44 128.85 138.85 148.93 159.09 169.29 174.53 189.47

Overall pressure drop (kPa) 51.5 52.2 53.1 54.3 55.4 56.4 57.4 58.4 59.4 59.9 61.3

Solids inventory (t) 7.13 7.71 8.46 9.44 10.36 11.17 11.98 12.79 13.61 14.04 15.24

Table 3.8 Calculated bed density and pressure drop for sections of the DTFB apart from section III when Ug2 ¼ 15 m/s and ΔW3 ¼ 0 [8] Section I Between section I and II Section II Between section II and III Between section III and section IV Section IV Pressure drop

Bed density (kg/m3) 532.17 553.30 55.27 27.84 19.67 18.97

Pressure drop (kPa) 26.6 5.4 7.0 0.5 0.4 2.8 42.7

Table 3.6), thereby displaying an axial profile typical of fast fluidization. Figure 3.20 depicts the corresponding radial profile of bed density at a height of 25 m (in the middle of section III). Figure 3.20 shows a core–annulus structure with a very high solids density near the wall of 500 kg/m3, which is close to that in section I. Table 3.9 summarizes the solids concentration in each section and pressure drop at Ug2 ¼ 15 m/s and a supplementary solids flow rate of 100 kg/s (the overall flow rate of solids was 480 kg/s in the expanded reaction zone, section III). The solids flux through section III was about 59.7 kg/(m2s), which was larger than the corresponding K of 43.8 kg/(m2s). Therefore, the expanded zone operated in a dense fluidized state. The overall pressure drop across the entire DTFB reactor was 62.6 kPa. If Ug2 was increased to 17.3 m/s, choking occurred and the pressure drop changed with the overall solids inventory at a given flow rate of gas and solids. When the solids inventory in the secondary reaction zone was 10 t, the exponentially decaying axial profile of solids concentration formed an S-shape, displaying a coexisting dense bottom and dilute top, as illustrated in Fig. 3.21. When the

3.4 Theoretical Modeling

99

Fig. 3.19 Calculated axial profile of bed density in section III with a solids inventory of 10 t [8] (Ug2 ¼ 15 m/s, ΔW3 ¼ 0)

Fig. 3.20 Calculated radial profile of bed density at a height of 25 m (Ug2 ¼ 15 m/ s, ΔW3 ¼ 0) [8]

superficial gas velocity remained at 15 m/s and the supplementary solids flow rate was increased to 200 kg/s, the gas–solid flow was still in the dense fluidization state but with a denser distribution in the expanded reaction zone. The radial distributions of solids catalysts in the secondary reaction zone at a height of around 28 m showed core–annulus structures in all three cases (Fig. 3.22).

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3 Cold Model Experiment and Reactor Modeling

Table 3.9 Predicted results for each section in the DTFB when Ug2 ¼ 15 m/s and W3 ¼ 100 kg/s [8] Section I Between section I and II Section II Between section II and III Section III Between section III and section IV Section IV Overall pressure drop

Bed density (kg/m3) 532.17 553.30 55.27 27.84 225.88 67.95 23.87

Pressure drop (kPa) 26.6 5.4 7.0 0.5 18.2 1.3 3.6 62.6

Fig. 3.21 Predicted axial distribution of cross-sectional average bed density using three different operating parameters with the same solids inventory in section III (I3 ¼ 10 t) [8]

Simulations were performed for a series of operating conditions, allowing the hydrodynamic behavior and flow regime transitions of the reactor to be investigated. The results were used to finalize the parameters of an actual MIP reactor at Gaoqiao, Shanghai. This reactor was the first of its kind and was later declared a success. As a result, the MIP process has now replaced the conventional FCC process throughout China.

3.5

Conclusion

This chapter described two DTFBs, one with an outer diameter of 284 mm and ID of 140 mm (Setup I) and the other with an outer diameter of 90 mm and ID of 45 mm (Setup II), as well as a series of cold-flow experiments using them. Using Setup I, experiments were mainly performed to investigate the axial voidage profiles under a

3.5 Conclusion

101

Fig. 3.22 Predicted radial profiles of solids concentrations at a height of about 28 m for three different sets of operating conditions with a solids inventory in section III of 10 t. [8]

series of operating conditions. The cold-flow experiments demonstrated that the use of bed expansion and multistage solids feed can effectively manipulate the axial distribution of bed density to realize fully dilute or dense transport in the first section and an S-shaped profile in the expanded section. The solids concentration and height of the dense bottom in the expanded section could be regulated by varying the operating gas velocity through the first section and solids circulating rates in the two loops. Using Setup II, local information including local solids velocity and concentrations was obtained. The following main conclusions were obtained: 1. In Setup I, at UF1 ¼ 5 m/s without a supplementary solids supply (Ws2 ¼ 0), the increase of the primary solids feed rate above 1.5 t/h resulted in the transition of fully dilute transport to dense transport in section I, increased the solids concentration in the diffuser, and formed a coexisting dilute top and dense bottom in section II. 2. For Setup I, when UF1 ¼ 12–16 m/s, Ws1 ¼ 20.82 t/h (Gs1 ¼ 375.7 kg/(m2s)), and Ws2 ¼ 0, the reactor operation was very stable. Under these conditions, section I operated in the dense flow regime and section II was maintained in the fast fluidization state with a dense region at a height of about 2 m. At a fixed Ws1 without the secondary solids supply, the increase of gas velocity was favorable to achieve stable operation. An increase of Ws1 at a given UF1 resulted in densification of the flow throughout the whole reactor but caused more fluctuations.

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3 Cold Model Experiment and Reactor Modeling

3. For experiments on the influence of supplementary solids feed rate at different gas velocities (i.e., UF1 ¼ 5, 12, 15, and 16 m/s), it was found that the supplementary solids feed rate had a pronounced effect on the densification of the solids flow. With increasing solids feed rate, the solids concentration increased in section II but decreased in section I. 4. The experiments using Setup II showed that the influences of bed expansion and supplementary solids feed were attenuated with increasing bed height. In the expanded section, the solids velocity gradually decreased with increasing bed height and the core region correspondingly decreased. The effects of the operating gas velocity and solids flow rate on the cross-sectional averaged voidage in the DTFB was similar to that in a conventional riser. 5. The EMMS model extended by Cheng [8] was used to predict the axial and radial profiles of solids concentration as well as the pressure drop of each section and also helped to determine suitable conditions based on choking prediction. When the superficial gas velocity in section II was 15 m/s, choking occurred in the expanded section without a supplementary solids supply. The introduction of supplementary solids feed resulted in the occurrence of dense transport in the expanded section. When the superficial gas velocity in section II was 16.5 m/s, supplementary feed rates in the range of 0–100 kg/s were able to induce choking.

References 1. Chen, B.Y., Xia, L.P., Gao, S.Q., Wang, X.H., Li, J.H.: Internal report of RIPP: experimental research on cold-model of MIP industrial unit (in Chinese) (2002) 2. Wang, X.: Gas-solid flow patterns of a dual-loop FCC riser with varying diameter. Doctoral Thesis, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, China (2006) 3. Wang, X., Gao, S., Xu, Y., Zhang, J.: Gas-solids flow patterns in a novel dual-loop FCC riser. Powder Technol. 152, 90–99 (2005) 4. Zhang, H., Johnston, P.M., Zhu, J.X., de Lasa, H.I., Bergougnou, M.A.: A novel calibration procedure for a fiber optic solids concentration probe. Powder Technol. 100(2), 260–272 (1998) 5. Zhu, J.X., Li, G.Z., Qin, S.Z., Li, F.Y., Zhang, H., Yang, Y.L.: Direct measurements of particle velocities in gas–solids suspension flow using a novel five-fiber optical probe. Powder Technol. 115(2), 184–192 (2001) 6. Schut, S.B., van der Meer, E.H., Davidson, J.F., Thorpe, R.B.: Gas–solids flow in the diffuser of a circulating fluidised bed riser. Powder Technol. 111(1), 94–103 (2000) 7. Marjanovic, P., Levy, A., Mason, D.J.: An investigation of the flow structure through abrupt enlargement of circular pipe. Powder Technol. 104(3), 296–303 (1999) 8. Cheng, C.L.: Engery minimization multi-scale core-annulus model for CFBs. Doctoral Thesis, Institute Process Engineering, Chinese Academy of Sciences, Beijing, China (2001) 9. Li, J., Kwauk, M.: Paticle-Fluid Two-Phase Flow: The Energy-Minimization Multi-Scale Method. Metallurgical Industry Press, Beijing (1994) 10. Wang, W., Lu, B., Dong, W., Li, J.: Multi-scale CFD simulation of operating diagram for gas-solid risers. Can. J. Chem. Eng. 86(3), 448–457 (2008) 11. Wang, W., Lu, B., Li, J.: Choking and flow regime transitions: simulation by a multi-scale CFD approach. Chem. Eng. Sci. 62(3), 814–819 (2007)

Chapter 4

Multiscale CFD Simulation for DTFB Scale-Up

Abstract This chapter introduces an energy-minimization multiscale-based computational fluid dynamics approach and its application to the simulation of industrialscale diameter-transformed fluidized bed (DTFB) reactors. The effects of geometrical and operating factors are numerically investigated to search for the optimal design of DTFB reactors for the maximizing iso-paraffins (MIP) process. The simulation results indicate that the geometrical factors including the configurations of the exit tube, feeding tube, and distributor do not strongly affect the macroscopic flow state in the expanded second section, but are important to maintain a steady transition between the two neighboring sections. The simulation accurately predicts the flow regime transition, in particular, the choking phenomenon, in a series of curves relating the solids flux and solids inventory at specified operating gas velocities. The simulation results can be used to determine the optimal operating conditions and diameter ratio of the expanded second reaction zone to the first reaction zone. A reactive simulation of a 120-Mt/a DTFB reactor for the MIP process further reveals the variation of velocities, temperature, and product species with the reactor height. Results and challenges to the scale-up of this reactor are then discussed.

4.1

Simulation Approaches

With the rapid development of computational fluid dynamics (CFD) and multiphase flow theory, in particular, the modeling of mesoscale structures between the particle scale and the reactor scale to determine constitutive relations [1–4], we are now able to accurately predict the complex hydrodynamic and reaction behaviors of multiphase flow reactors. This chapter summarizes the numerical simulations of a series of diameter-transformed fluidized beds (DTFBs) using a multiscale CFD approach; i.e., a combination of CFD and the energy-minimization multiscale (EMMS) drag model. The effects of operating and geometrical parameters on the

© Springer Nature Switzerland AG 2020 Y. Xu et al., Diameter-Transformed Fluidized Bed, Particle Technology Series 27, https://doi.org/10.1007/978-3-030-47583-3_4

103

104

4 Multiscale CFD Simulation for DTFB Scale-Up

hydrodynamics and reactions of the DFTBs are investigated extensively. Such an investigation can be expected to provide information for the simulation-aided scaleup of fluidized bed reactors from laboratory to commercial scale [5]. Fluidization is intrinsically a nonequilibrium and nonlinear process and features multiscale structures [1]. In a fluidized bed, the microscale usually refers to a single particle, for which the fluid–particle interactions have been thoroughly investigated, and the macroscale is the fluidized bed, for which one may regulate operating parameters to achieve the optimum process. Between the microscale and macroscale is the mesoscale, which is characterized by a broad spectrum of dynamic structures such as clusters or bubbles. At the mesoscale, the behavior of individual particles is quite different from that of isolated single particles. Different simulation methods to describe such a fluid–particle system at different scales have been developed. Currently, CFD is emerging as a powerful tool to help understand the hydrodynamics, heat/mass transfer, and reaction behavior in multiphase systems. Among various simulation approaches for gas–solid flows, direct numerical simulation (DNS), where the motion of each particle is tracked and the fluid flow is resolved to a much smaller scale than the particle size, is regarded as the most accurate method but has the highest computational load [6]. The discrete particle model (DPM), which tracks the motion of each particle in the same manner as DNS and resolves the fluid flow on a much larger scale than the particle size [7, 8], has much lower computational cost than that of DNS, but is still restrained to a limited number of particles. In many cases, DPM is represented by CFD-DEM, where DEM is the discrete element method, because it is able to model multiple particle collisions and thus is widely used in dense gas–solid flow [6]. In recent years, different coarsegrained approaches have been proposed to further decrease the computational cost by introducing a parcel representing a group of particles. A typical coarse-grained method, the multiphase particle-in-cell method [9, 10], omits the actual collision between particles but the consequence of collisions is expressed by the kinetic theory of granular flow (KTGF) or empirical correlations. These simplifications require additional modeling to improve coarse-grained methods. The Eulerian–Eulerian method (also called the two-fluid model (TFM) or pseudofluid model) is the least computationally expensive approach available and is thus commonly used for industrial applications. The TFM treats gas and solid phases as interpenetrating continua and averages microscopic conservation equations to provide locally averaged quantities. Early rigorous derivations of the TFM were published by Anderson and Jackson [11], Soo [12], Drew and Segel [13] and Ishii [14]. These derivations are very similar: instantaneous mass, momentum, and energy conservation equations governing two-phase flow at the microscopic level as well as the related interphase jump conditions are first derived, followed by different averaging techniques to smooth local variables/jump conditions, and finally the averaged pseudo-fluid model equations are obtained. The TFM equations can also be derived using the KTGF [15]. Generally, applying different averaging techniques to conservation equations at the microscopic level leads to different forms of the

4.1 Simulation Approaches

105

pseudo-fluid model equations, such as Model A and Model B [16], but no big difference between simulation results has been found. However, the averaging process can erase flow details at the level of individual particles. The microscopic flow details lost in the averaging can be remedied by developing constitutive relations to describe parameters such as solid phase stress and gas–solid drag. The generic averaged equations combined with different models of constitutive relations can lead to quite different results.

4.1.1

Basic Governing Equations

The widely used basic governing equations of the TFM are written as follows. For more details, readers can refer to the documentation of commercial software Ansys®Fluent [17]. The continuity equation for phase q (q ¼ g, s; p ¼ s, g) is: 
 ∂
εq ρq þ ∇ ∙ εq ρq uq ¼ Γ pq  Γ qp , ∂t

ð4:1Þ

where uq is the velocity of phase q, and Γ pq characterizes the mass transfer from phase p to phase q. The momentum balances for the gas and solid phases are respectively: 
 ∂
εg ρg ug þ ∇ ∙ εg ρg ug ug ¼ εg ∇p þ ∇ ∙ τ g þ εg ρg g  Fd ∂t
 þ Γ sg usg 2 Γ gs ugs

ð4:2Þ

∂ ðεs ρs us Þ þ ∇ ∙ ðεs ρs us us Þ ¼ εs ∇p  ∇ps þ ∇ ∙ τ s þ εs ρs g þ Fd ∂t
 þ Γ gs ugs 2 Γ sg usg ,

ð4:3Þ

where τ is the stress tensor (q ¼ g, s) using the Newtonian form: h  
T i 2 τ q ¼ εq μq ∇uq þ ∇uq þ ε q λ q  μ q ∇ ∙ uq I 3

ð4:4Þ

Here, μq and λq are the shear and bulk viscosities of phase q, respectively, p is the pressure shared by both phases, ps is the solid pressure, and ugs and usg are the interphase velocities. If Γ sg > 0, usg ¼ us, otherwise usg ¼ ug; likewise, if Γ gs > 0, ugs ¼ ug, otherwise ugs ¼ us. Note that here Fd refers to the drag and other interaction forces such as the lift force and virtual mass force were omitted for the sake of simplicity, because drag dominates the other interaction forces in gas–solid fluidization. Fd can be expressed as Fd ¼ (ug  us)β, where β is the drag coefficient.

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4 Multiscale CFD Simulation for DTFB Scale-Up

The conservation of energy for each phase (q ¼ g, s; p ¼ s, g) can be written as: 
 ∂ρq ∂
þ τq εq ρq hq þ ∇ ∙ εq ρq uq hq ¼ εq ∂t ∂t : ∇uq  ∇ ∙ qq þ Sq þ Qpq
 þ Γ pq hpq 2 Γ qp hqp ,

ð4:5Þ

where hq is the specific enthalpy of phase q, qq is the heat flux, Sq is a source term that includes sources of enthalpy (e.g., chemical reaction or radiation), and Qpq is the heat exchange between phase p and phase q. Note that hpq is the interphase enthalpy (e.g., the enthalpy of the vapor at the temperature of the droplets in the case of evaporation) and is not considered in gas catalytic reactions. The generalized conservation equation for chemical species (q ¼ g, s) can be expressed as: 
 ∂
ρq εq Y q,i þ ∇ ∙ ρq εq uq Y q,i ¼ ∇ ∙ εq Jq,i þ εq Rq,i þ R, ∂t

ð4:6Þ

where J is the diffusion flux of species i, Rq,i is the net rate of production of homogeneous species i by chemical reaction for phase q, and ℜ is the heterogeneous reaction rate.

4.1.2

Solid Phase Stress

Under the continuum framework, how to close the momentum interaction between gas and solid phases, mass/heat transfer, and solid phase stress, has become a topic of considerable interest in not only the academic community but also industry. The KTGF developed from the kinetic theory of gases has been recognized as a reliable approach to close the solid phase stress for rapid granular flows [16]. The granular temperature equation is written as   3 ∂ ðεs ρs Θs Þ þ ∇ ∙ ðεs ρs us Θs Þ ¼ ðps I þ τ s Þ 2 ∂t : ∇us  ∇ ∙ q 2 γ  3Θs β:

ð4:7Þ

Here, Θs is the granular temperature, q is the flux of fluctuating energy, and γ is the collisional energy dissipation. The following algebraic form is more widely used in simulations than Eq. (4.7) because of better convergence and lower computational cost,

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107

Table 4.1 Frequently used sub-models of the KTGF Solids viscosity: μs ¼ μs, col + μs, kin + μs, fr Collisional viscosity using Gidaspow model: μs,col ¼

4 5 ρs εs d s g0 ð1

þ ess Þ

qffiffiffi θs π

Kinetic viscosity using Gidaspow model: pffiffiffiffiffiffi 2 10d s ρs Θs π ½1 þ 45 ð1 þ ess Þεs g0,ss  μs,kin ¼ 96ε s ð1þess Þg

(4.9) (4.10)

(4.11)

0,ss

φ Frictional viscosity using Schaeffer model: μs,fr ¼ p2spsinffiffiffiffiffi I

(4.12)

2D

Granular bulk viscosity using Lun et al: model: λs ¼ 43 εs ρs ds g0 ð1 þ ess Þðθπs Þ

1=2

(4.13)

Solids pressure using Lun et al:: ps ¼ εs ρs θs þ 2ρs ð1 þ ess Þε2s g0 θs   1=3 1 s Radial distribution function using Lun et al: model: g0 ¼ 1  εs,εmax

(4.14) (4.15)

ðps I þ τs Þ : ∇us  γ s ¼ 0:

ð4:8Þ

Table 4.1 lists the frequently used sub-models in the KTGF, which were used in the simulations described later in this chapter.

4.1.3

Gas–Solid Drag Model

In gas–solid fluidization, immense effort has been focused on developing the gas–solid drag, because the drag has been found to play a crucial role in predicting heterogeneous gas–solid flows. Early research on drag modeling was primarily based on experimental data, such as Wen and Yu drag (εg > 0.8) [18] and Ergun drag (εg < 0.8) [19] as well as their combination, Gidaspow drag [20]. In the past decade, drag correlations obtained from DNS or fine-grid simulations have become popular. All these correlations depend on the experimental or numerical analysis of a nearly homogenous system. However, the presence of strong inhomogeneities in the spatial distribution of particles is a salient feature in gas–solid fluidization and has been recognized to have a considerable influence on drag force and thus should be taken into account in modeling. There are some drag models considering the effects of heterogeneous structures, such as EMMS-based drag models [2, 4, 21, 22] and filtered drag models [23–27]. Because successful applications of filtered models are primarily found in simulations of bubbling fluidized beds and turbulent fluidized beds with relatively low velocity [27–32], here, we employ the EMMS-based drag model [2], which has been continually improved for more than a decade [3, 4], and shows only weak dependence on the grid size [3, 4]. Thus, the EMMS-based drag model can be used for simulations of industrial-scale fluidized bed reactors. Because the Gidaspow model has been used for the first step in a large number of simulation experiments, for comparison, it is also employed here. The relevant drag models are presented below.

108

4.1.3.1

4 Multiscale CFD Simulation for DTFB Scale-Up

Gidaspow Drag Model

The Gidaspow model [20] is expressed by

β¼

8 > > >
ð1  εg Þ2 μg ð1  εg Þρg jug  us j > > þ 1:75 ðεg < 0:8Þ : 150 2 dp εg d p

,

ð4:16Þ

where

C D0

4.1.3.2

 8
0:687 > < 24 1 þ 0:15 Re s , Re s < 1000 Re s ¼ > : 0:44, Re s  1000

ð4:17Þ

EMMS Drag Model

EMMS Model The EMMS model [1] was originally proposed to describe the flow structure in a steady-state gas–solid fluidization system. Now it becomes the physical basis for developing a drag model that considers the effects of flow structures. In what follows, a brief introduction to the EMMS model is given first to facilitate understanding of the EMMS-based drag models. Figure 4.1 presents a general concept of the EMMS model in which the gas–solid fluidization is divided into a particle-rich dense phase in the form of clusters or aggregates and a gas-rich dilute phase in the form of dispersed particles. The parameters describing the gas–solid flow involve three scales: operating parameters (superficial gas velocity Ug and particle velocity Us) are related to the macroscale scale; voidage εgc, superficial gas velocity Ugc and superficial particle velocity Usc for the dense phase and voidage εgf, superficial gas velocity Ugf and superficial particle velocity Usf for the dilute phase are related to the microscale; and the volume fraction of the dense phase (or cluster) f and the equivalent cluster diameter dcl are the parameters at the mesoscale. In total, there are eight unknown variables (εgc, Ugc, Usc, εgf, Ugf, Usf, f, and dcl), but only six equations can be established from conservation laws and the cluster diameter correlation. To close these equations, a stability condition was subsequently proposed through an analysis of dominant mechanisms. That is, the gas tends to choose an upward path with minimal resistance, expressed by the minimum energy consumption for suspending and transporting particles per unit volume (Wst ¼ min), and the particles tends to maintain the lowest gravitational potential, denoted by the minimum voidage (εg ¼ min). The stability condition is consequently

4.1 Simulation Approaches

109

Fig. 4.1 The EMMS model, adapted from Li and Kwauk [33]

expressed by the compromise between these two dominant mechanisms in their competition, as follows: N st ¼


  ρ  ρg εgf  εg W st  ¼ s Ug  f ð1  f ÞU gf g⟶ min : ρs 1  εg 1  ε g ρs

ð4:18Þ

The stability condition bridges the macro- and microscale parameters, making the behavior of mesoscale structures subject to a combination of both bottom-up and top-down constraints. This concept is quite different from the filtered model in which the flow structures are resolved in a “bottom-to-top” manner by performing a finegrid simulation normally under a force balance condition over the whole domain. EMMS-Global Drag Model Because the force balance for the dense and dilute phases does not hold in a local volume, Yang et al. [2] first proposed the EMMS-based drag model by introducing an acceleration shared by three force balance equations. This model is named EMMS-global in EMMS® software and is formulated as a set of nonlinear equations for vertical components of forces, as follows. Force balances for the dense phase, interphase, and dilute phase of the EMMS model are modified by introducing an acceleration a on the right-hand side of three equations:

110

4 Multiscale CFD Simulation for DTFB Scale-Up




F dc



 1  εgc 1 π ¼ C dc ρg U 2slipc d2p ¼ 1  εg ρs  ρg ðg þ aÞ, 3 2 4 πd p =6



 1 π Cdi ρg U 2slipi d2cl ¼ f εg  εgc ρs  ρg ðg þ aÞ, 2 4


 1  εgf 1 π F df ¼ Cdf ρg U 2slipf d2p ¼ 1  εgf ρs  ρg ðg þ aÞ: 3 2 4 πdp =6 F di ¼

f

πd3cl =6

ð4:19Þ ð4:20Þ ð4:21Þ

Mass balance equations for the gas and solid phases are: U g ¼ f U gc þ ð1  f ÞU gf ,

ð4:22Þ

U s ¼ f U sc þ ð1  f ÞU sf :

ð4:23Þ

The cluster diameter equation is: dcl ¼

dp ½U s =ð1  εmax Þ  ðU mf þ U s εmf =ð1  εmf ÞÞg
 : N st ρs = ρs  ρg  ðU mf þ U s εmf =ð1  εmf ÞÞg

ð4:24Þ

The mean voidage εg is related to the voidages of the dilute and dense phases by εg ¼ εgc f þ εgf ð1  f Þ:

ð4:25Þ

In total, there are nine parameters, i.e., εgc, Ugc, Usc, εgf, Ugf, Usf, f, dcl, and a, closed by seven equations (Eqs. 4.19, 4.20, 4.21, 4.22, 4.23, 4.24, and 4.25) and a stability condition (Eq. 4.18). All nine parameters can be obtained by using a fullsearch scheme [34] and the structure-dependent drag coefficient β is determined by: β¼

ε2g ð f F dc þ F di þ ð1  f ÞF df Þ: U slip

ð4:26Þ

The parameter ω is then introduced to reflect the influence of surrounding particles on the standard drag coefficient, ω¼

β , β0

ð4:27Þ

where β0 represents the standard drag coefficient, β0 ¼

3 1  εg ρg U slip CD0 : 4 dp

ð4:28Þ

4.1 Simulation Approaches

111

For a drag model for homogeneous fluidization such as the Wen and Yu model [18], ω is equal to ε2:65 . The parameter ω is a function of voidage or solids g concentration, i.e., ω ¼ f(εg), in which εg is the mean voidage for a given control volume; e.g., the mean voidage of a computational grid in a CFD simulation. To date, this model has been successfully used in the simulation of riser flows with Geldart A particles [35–39]. However, whether the correlation of cluster diameter is suitable for other fluidization regimes has not been fully investigated. In addition, the assumption that the same acceleration term applies to all the momentum equations deserves serious consideration. Effort has been devoted to resolving these issues. For example, Wang et al. [21] introduced different acceleration terms in the momentum equations of the dilute and dense phases, respectively, and correlated them with an added mass force according to the research of Zhang and Vanderheyden [40]. Then, the original cluster equation was replaced with a correlation of voidage in the dense phase. Further effort is still needed to explore the underlying mechanism of the dynamic formation and dissolution of mesoscale structures. EMMS-Matrix Drag Model The EMMS-global drag model [2] was extended by differentiating the acceleration terms in the force balance equations of the dense phase, dilute phase, and interphase and proposing a two-step scheme to obtain all the structural parameters of the model [3, 4]. The two-step scheme stems from the following considerations: (1) The external energy sustains the bulk flow of the whole fluidization system against gravity. The formation of mesoscale structure primarily originates from the macroscale mean relative motion between gas and particles. This relationship is also reflected in the cluster equation (Eq. 4.24), where the cluster diameter is assumed to be inversely proportional to the external energy [1]. As a consequence, the mesoscale parameters such as dcl and εgc are primarily restrained by macroscale hydrodynamic conditions and resolved in the first step. (2) Mesoscale structures are intrinsically unstable or dynamic because they are subject to local hydrodynamics such as interactions with surrounding fluid and particles. Thus, the dynamic parameters related to mesoscale structures, such as β and multiple inertia parameters, need further microscale or local hydrodynamic information, which are resolved in the second step. Therefore, the equations in the first step encompass the continuity equations (Eqs. 4.22 and 4.23), cluster equation (Eq. 4.24), voidage equation (Eq. 4.25), and three force balance equations (Eqs. 4.29, 4.30, and 4.31) which are modified from Eqs. 4.20, 4.21, and 4.22 of the EMMS-global model by introducing different acceleration terms as follows:


F dc



 1  εgc 1 π ¼ C dc ρg U 2slipc d2p ¼ 1  εg ρs  ρg ðg þ ac Þ, 3 2 4 πdp =6

ð4:29Þ

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4 Multiscale CFD Simulation for DTFB Scale-Up



 1 π C di ρg U 2slipi d2cl ¼ f εg  εgc ρs  ρg ðg þ ai Þ, 2 4


 1  εgf 1 π F df ¼ Cdf ρg U 2slipf d 2p ¼ 1  εgf ρs  ρg ðg þ af Þ, 3 2 4 πdp =6 F di ¼

f

πd3cl =6

ð4:30Þ ð4:31Þ

where the acceleration term for the mesoscale phase ai is related with ac and af through the following pressure-drop balance equation: 



ð1  f Þ 1  εg ðg þ ac Þ  1  εgf ðg þ af Þ
 ai ¼  g: f εg  εgc

ð4:32Þ

Consequently, there are ten parameters, that is, εgc, Ugc, Usc, εgf, Ugf, Usf, f, dcl, ac, and af, closed by seven equations (Eqs. 4.29, 4.30, and 4.31 and 4.22, 4.22, 4.23, 4.24, and 4.25) and the stability condition (Eq. 4.18). Using an optimization scheme [3], the mesoscale structural parameters (dcl and εgc) can be obtained as functions of εg or solids concentration. In addition, the solutions of εf and af (εf ¼ εmax and af ¼ g) are assumed to hold in the second step. The solutions for εf and af for dilute flow obtained from the first step of the model were found to agree with the experimental results of Matsen [41] and CFD-DEM simulation reported by Li and Kuipers [42]. In the second step, only six parameters (Ugc, Usc, Ugf, Usf, f, and ac) are left unknown because dcl, εgc, εmax, and af were resolved in the first step. Six governing equations (Eqs. 4.29, 4.30, and 4.31, 4.22, 4.23, and 3.25) are available, which can be further simplified into three equations by reorganizing the conservation equations as functions of three unknown variables (Uslipc, Uslipi, and ac) [4]:




 1  εgc 1 π C dc ρg U 2slipc d 2p ¼ 1  εg ρs  ρg ðg þ ac Þ, 3 2 4 πd p =6 f

πd 3cl =6



 1 π C di ρg U 2slipi d2cl ¼ f εg  εgc ρs  ρg ðg þ ai Þ, 2 4

 εgf 1  εg U slipi ¼ U slip  f U slipc : εgf  εg

ð4:33Þ ð4:34Þ ð4:35Þ

A heterogeneity index or drag correction factor HD to quantify the disparity between homogeneous and heterogeneous drag models is then defined as: HD ¼

β , βw

ð4:36Þ

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113

Fig. 4.2 The drag correction factor for a fluid catalytic cracking (FCC)/air system obtained using the EMMS-matrix model and EMMS-global model (ρs ¼ 930 kg/m3, dp ¼ 54 μm, Ug ¼ 1.52 m/s, Gs ¼ 14.3 kg/m2s, εmf ¼ 0.4, εmax ¼ 0.9997, Re ¼ Uslipdpρg/μg). (Adapted from Lu et al. [4] Copyright (2009) Elsevier)

where the drag coefficient βw refers to the Wen and Yu model (1966) [18] and the resultant β with the same definition as in Eq. 4.26 depends on the structural parameters resolved by the above model. This new model is named the EMMS-matrix model. The relevant HD from the definition in Eq. 4.36 after substituting the expressions of β and βw can be expanded as    U slip,c 2 C D0,c 1  εgc ε4:65 g : HD ¼
 2    1  εg ε4:65 gc U slip C D0


ð4:37Þ

HD can be expressed as a function of both εg and Uslip. When Re (¼εguslipdpρp/ μg) < > >
εg Þ dp 4

> ð1  εg Þ2 μg ð1  εg Þρg jug  us j > > þ 1:75 ðεg < εg Þ : 150 dp εg d 2p

8   0:0214 > > εg < εg < 0:82 0:5760 þ
 > 2 > > 4 εg  0:7463 þ 0:0044 > >
 <
 0:0038 ω εg ¼ 0:0101 þ 0:82 < εg < 0:97
 > 2 > > 4 εg  0:7789 þ 0:004 > > > >
 : 31:8295 þ 32:8295εg εg > 0:97

ð4:38Þ

ð4:39Þ

Because the physical properties and operating parameters for the laboratory-scale reactors are close to the conditions for the riser flow reported by Yang et al. [2], we employed the drag correction calculated based on the conditions in Yang et al. [2], in which εg depends on the nature of gas and particles and operating conditions and was set at 0.74 in their study.

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117

Fig. 4.5 Distribution of solids concentration in a laboratory-scale reactor. (a) Instantaneous plot of solids concentration and (b) timeaveraged axial voidage profiles [36]

4.2.2

Results and Discussion

4.2.2.1

Solids Concentration

Figure 4.5a illustrates the obvious presence of heterogeneous flow in both axial and radial directions, displaying a transition from dilute pneumatic transport in the first zone to a denser fluidization state in the second zone. Figure 4.5b compares experimental and predicted time-averaged voidage profiles. The simulation shows fair agreement with experiments results, even with a 2D simulation configuration. The simulation with the Gidaspow model predicted much more dilute flow, even using a three-dimensional (3D) configuration. To investigate the effect of distributors on the flow behavior of maximizing iso-paraffins (MIP) risers, we simulated the reactor in Fig. 4.4b mounted with a perforated plate with an orifice number n of 27 and an opening ratio of 8.33%. The opening ratio and average spacing between neighboring orifices were the same in both 2D and 3D simulations. Figure 4.6 shows that both 3D and 2D simulation results were in reasonable agreement with experimental data in the upper dilute region except near the distributor, where the predicted solids volume fraction was lower than the experimental data. By and large, the 3D simulation provided much better results than the 2D, which is because the 3D meshing scheme can better reflect the asymmetric behavior of the reactor than the 2D. However, the agreement between the 3D simulation and experimental data was not as high as that in the aforementioned case without a distributor. This is probably because the distributor meshing was not fine enough. It

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Fig. 4.6 Comparison of voidage profiles obtained from 3D and 2D simulations of laboratory-scale reactors with experimental data (27 orifices were uniformly distributed on a perforated plate) [36]

should be noted that experimental measurements may not be accurate near the distributor, because the balance between pressure drop and effective gravity assumed during measurements could be violated as a result of strong acceleration/ deceleration and vigorous mixing in the distributor region. More elaborate work should be carried out to investigate the flow near the distributor, because the heat/ mass transfer in this region is usually the critical driving force for reactions in fluidized beds.

4.2.2.2

Flow Regime Transition of Choking

The flow regime transition from dilute pneumatic transport to dense transport leads to marked differences in the flow behavior. Understanding such differences is important to the design and scale-up of CFB reactors. There are many publications that have focused on flow regime transitions through analysis of experiments, including Bi and Grace [51], Grace [52], and Sun and Zhu [53], but we are still far from reaching a comprehensive understanding of these transitions. Figure 4.7 plots the relationships between the three variables Ug, solids flux Gs, and solids inventory I for a cylindrical CFB riser at the laboratory scale. The saddle area is the region referred to as “choking”. Choking is characterized by the coexistence of two flow regimes where Gs is equal to the saturation carrying capacity K, for which the constant–Ug curves are horizontal lines. The particle–fluid compromising (PFC) zone towards the right refers to the single dense region with Gs > K and the fluid-dominating (FD) zone towards the left refers to the single dilute region with

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119

Fig. 4.7 Relationships between Ug, Gs, and I (FCC/air in a riser with a height of 10 m and inner diameter of 90 mm). (Adapted from Li [54])

Gs < K. Point D is the critical point for the coexistence of two flow regimes with an S-shaped axial voidage profile. If Ug is larger than the gas velocity corresponding to this point, namely, the critical gas velocity, the coexisting region (PFC/FD) changes into a single dilute flow region and the flow regime undergoes a smooth transition from dilute pneumatic transport to dense transport without choking in between. In contrast, the flow regime experiences an abrupt transition with increasing I when Ug is lower than the critical value. Accordingly, if Gs is larger than the solids flux corresponding to the critical point D, the coexisting PFC/FD regions are replaced by a single dense flow region. It can be seen that choking (PFC/FD zone) corresponds to Ug ¼ Upt and Gs ¼ K, to its right is the PFC zone corresponding to Ug < Upt and Gs > K, and to its left is the FD zone corresponding to Ug > Upt and Gs < K. It is noteworthy that the S-shaped profiles can only exist within certain range of I, as represented by the saddle-shaped PFC/FD zone in Fig. 4.7. Thus, to realize a given mode of operation, the conditions that need to be satisfied should include the solids inventory I in addition to the normally specified Ug and Gs. Furthermore, K is important to determine the operating mode. To examine whether the multiscale CFD approach can capture the flow regime transition with choking, a series of simulations of a CFB riser with a height H of 10 m and inner diameter (ID) of 90 mm were conducted with varying Ug and I. At the beginning of these simulations, a certain amount of solids was uniformly distributed throughout the riser. During the simulations, the solids entrained out of the riser were monitored and then returned to the riser from the bottom inlet. The collection of time-averaged statistics started when the simulation reached a steady state and then lasted for a period of time to obtain the time-averaged data. The time for statistics should be longer than the mean residence time of particles in the riser.

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4 Multiscale CFD Simulation for DTFB Scale-Up

Fig. 4.8 Relationships between the simulated solids flux Gs, superficial gas velocity Ug, and mean solids concentration εs0 (FCC/air system: ρs ¼ 930 kg/m3, ρg ¼ 1.1795 kg/m3, μg ¼ 1.8872  105 Pas, dp ¼ 54 μm, riser height ¼ 10 m, and ID ¼ 90 mm) [55]

By varying the initial solids concentration at a given Ug, a Gs–I curve was obtained, as shown in Fig. 4.8. Figure 4.8 displays the simulated flow regime diagram, which was similar to that obtained experimentally (Fig. 4.7). Because the simulation was performed only for the riser zone, the imposed pressure drop ΔPimp or the total I on the abscissa of the plot which was obtained from experimental data (Fig. 4.7) was replaced by the mean solids concentration of the riser in Fig. 4.8. This predicted flow regime diagram also shows three operating modes; that is, the PFC zone towards the right of Fig. 4.8 for the dense transport regime, the FD zone towards the left for the dilute flow regime, and the transition zone between them with S-shaped axial profiles of voidage. In this transition zone, the dense flow regime coexists with the dilute flow regime with Gs ¼ K, in which the iso-Ug curve features a horizontal segment. The highest point of the saddle-shaped area, which represents the critical point for the coexistence of flow regimes, corresponded to a Ug of 2.8 m/s, showing good agreement with the experimental value (point D in the experimental data has a Ug of 2.6 m/s). Figure 4.9 was adapted from Fig. 4.7 by replacing the total I on the abscissa with the mean solids concentration to directly compare the simulation (Fig. 4.8) and experiment (Fig. 4.9). When Ug was 1.52 m/s, the horizontal line corresponds to the range of solids concentration between 0.02 and 0.1, whereas in the experiment (Fig. 4.9), the solids concentration at the horizontal line falls in the range of solids concentration between 0.02 and 0.16. The initial point of the horizontal line predicted by the simulation agrees well with the experimental findings, whereas the other end of the horizontal line shows evident disparity between the simulation and experiment. Compared to the simulation, the experiment gave a much higher solids concentration at the right end of the horizontal line. This is probably because the solids concentration was converted from the measured pressure drop, which is influenced more strongly by the downward motions of particles and wall friction under denser flow.

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121

Fig. 4.9 Relationships between Ug, Gs, and mean solids concentration εs0 (FCC/air system: ρs ¼ 930 kg/m3, ρg ¼ 1.1795 kg/m3, μg ¼ 1.8872  105 Pas, dp ¼ 54 μm, riser height ¼ 10 m, and ID ¼ 90 mm). Modified from Fig. 4.7

Figure 4.10 compares the distribution of solids concentration of different iso-Ug curves. On the curve with a Ug of 1.52 m/s, choking is observed between the dilute pneumatic transport and dense transport where Gs equals about 18 kg/(m2s). Points a, b, c, and d correspond to different flow states; that is, a represents dilute pneumatic transport, b and c the choking state, and d dense flow. At the choking state, points b and c display different heights of the dense region. The right-hand side of Fig. 4.10a shows that at point a, the solids concentration is almost constant along the bed height except for the region near the outlet/inlet. Points b and c show a typical S-shaped profile with different solids concentrations in the dense region but identical solids concentration in the dilute region. For point d, the variation of solids concentration with bed height is not remarkable compared to the case for the choking state. When Ug increases to 2.8 m/s, the choking phenomenon disappears. At different points on this iso-Ug curve, no evident dense bottom is observed. With increasing ΔPimp, the flow regime transitions smoothly from dilute pneumatic transport to dense flow. The axial profiles of solids concentration shown on the right-hand side of Fig. 4.10b are quite different from those in Fig. 4.10a. The solids concentration decreases gradually towards the outlet without evident turning points like in Fig. 4.10a. Bed height can also affect axial voidage profiles and flow regime. Investigating the effects of bed height experimentally is very costly and time consuming. Here, five risers with H of 2, 5, 10.5, 15, and 20 m are investigated numerically; the grid schemes for these risers are 30  134, 30  167, 30  310, 30  500, and 30  670, respectively. Figure 4.11 displays the flow maps for these five risers. It is found that the horizontal section of the iso-Ug curve decreases with bed height, and it is more difficult to develop an S-shaped profile in a shorter riser than in a taller one. Taking a Ug of 1.52 m/s as an example, no evident horizontal segment can be found for the riser with an H of 2 m. With increasing H, the horizontal section appears and expands because of the increased solids capacity. The critical point, in turn, shifts to a higher position with respect to the critical gas velocity Ug and the critical solids

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4 Multiscale CFD Simulation for DTFB Scale-Up

Fig. 4.10 Simulated relationships between superficial gas velocity Ug, solids flux Gs, and imposed pressure drop ΔPimp in an FCC/air CFB system: (a) an iso-Ug across the saddle-shaped area (Ug ¼ 1.52 m/s) and the relevant time-averaged axial profiles of solids volume fraction. The snapshots of solids concentration profile correspond to the transition from dilute pneumatic transport to the coexistence of dense and dilute flows with different dense bottom heights to dense upflow [55]. (b) An iso-Ug right across the critical point (Ug ¼ 2.8 m/s) and the relevant time-averaged axial profiles of solids volume fractions. The snapshots of solids concentration profile illustrate the smooth transition from dilute pneumatic transport to dense upflow [56]

flux Gs, but the saturation capacity K at a given Ug remains constant with varying H if choking occurs. Thus, the choking observed in a taller riser may be absent in a short riser, because it could be easily obscured by the comparatively strong effects of the developing flow near the inlet/outlet. In general, the intrinsic flow regime is important to understand the real hydrodynamic aspects behind the various states observed in reactors. Bases on flow regimes, we can expect to draw a series of operating diagrams, which demand geometrical parameters as well as common

4.3 Simulation of Industrial DTFB Reactors

123

Fig. 4.11 Calculated flow regime maps for risers with different heights of (a) 2 m, (b) 5 m, (c), 10.5 m, (d) 15 m, and (e) 20 m (FCC/air system: ρs ¼ 930 kg/m3, ρg ¼ 1.1795 kg/m3, μg ¼ 1.8872  105 Pas, dp ¼ 54 μm, uT ¼ 0.08 m/s) [56]

parameters such as Ug and Gs. Such operating diagrams can help to guide CFB operation. In practical operation, because ΔPimp or the blower pressure head may change a lot even at given Ug and Gs, the prediction choking is of crucial importance. Many simulations take for granted that a riser flow can be determined by specification of only gas and I, but this is not the case at the choking state. In-depth understanding of choking can facilitate troubleshooting of CFB units, because the gas–solid reactions in them are sensitive to the flow regime and related flow behavior.

4.3 4.3.1

Simulation of Industrial DTFB Reactors Operating and Simulation Parameters

A series of simulations of industrial DTFB reactors for the MIP process were conducted to search for the optimal geometrical and operating parameters and validate the model. Because a higher solids concentration and lower temperature in the expanded second reaction zone are favorable to facilitate isomerization and hydrogen transfer reactions in the expanded zone, the effects of geometrical and operating factors on the hydrodynamics in the expanded reaction zone are thus focused on.

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4 Multiscale CFD Simulation for DTFB Scale-Up

Table 4.4 Dimensions of two industrial DTFB reactors Diameter of section I, m Diameter of section II, m Diameter of section III, m Height of section II, m Diameter of the secondary solids feeding tube, m

Industrial DTFB-1 1.3 3.4 1.1 10 0.6

Industrial DTFB-2 1.4 4.2 1.36 7.5 0.7

Table 4.5 Base operating conditions of the two industrial DTFB reactors

Ug, m/s Solids feed rate, t/h Gs, kg/(m2s) Distributor

Industrial DTFB-1 Section I 13 1014

Section II 1.9 600 49.38 Arc-shaped perforated plate with 390 orifices of the diameter of 50 mm, denoted arc-shaped plate (390, ϕ50)

Industrial DTFB-2 Section I Section II 13 1.444 1840 1000 56.94 Arc-shaped plate (516, ϕ50)

The structure of the industrial DTFB reactors is the same as that shown in Fig. 4.4b. The dimensions for the two industrial reactors are listed in Table 4.4. The catalyst particles are Geldart A particles with a diameter of 65 μm and density of 1500 kg/m3. The gas density and viscosity are 1.76 kg/m3 and 2.89  105 Pas, respectively, which were obtained based on the practical operating pressure and temperature in the second reaction zone. Table 4.5 lists the base operating parameters including Ug, solids feed rate to the section I and section II. The hydrodynamics predicted under other operating and geometrical conditions will be compared to those with the base operating conditions. The TFM introduced in Sect. 4.1 with EMMS-global drag was used to describe the gas–solid flow in the industrial DTFB reactors. The solids flow rate out of the bed was monitored. If the solids outflow rate was greater than 105.5 kg/s, the solids feed rate to section I was set to 105.5 kg/s and the rest of solids returned to section II, whereas all the particles returned to the reactor from the bed bottom. Other simulation settings were the same as those described in Sect. 4.2.

4.3.2

Industrial DTFB Reactor 1

4.3.2.1

Effect of the Distributor

Three arc-shaped perforated plate distributors are investigated. The distributor in the base operating conditions shown in Table 4.5 is denoted as distributor 1, which has an opening ratio of 8.43% and 390 orifices with a diameter ϕ of 50 mm. The gas velocity across each orifice is denoted as the orifice gas velocity uoi (m/s). Aoi

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125

Table 4.6 Mean solids concentration and suspension density of each section of the industrial DTFB reactor 1 with different distributors Distributor Distributor 1 390,ϕ50, 8.43% (base) Distributor 2 98,ϕ100, 8.47% Distributor 3 169,ϕ100, 14.6%

Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3)

Section I 1.86 17.80

Section II 11.23 171.35

Exit tube 2.59 38.89

Whole bed 9.72 145.73

1.18 17.65

11.51 172.59

2.69 40.40

9.90 148.56

1.40 21.04

11.54 173.08

2.51 37.62

9.89 148.35

represents the cross-sectional area of the orifice and Q the total gas volumetric flow rate. For distributor 1, 2, and 3, uoi can be expressed as uo1 ¼ Q/(Ao1  390), uo2 ¼ Q/(Ao2  98), and u3 ¼ Q/(Ao3  169), respectively. Because distributor 1 and 2 have the same opening area ratio, the uoi values for both distributors are the same according to the above equations. Distributor 3 has the highest opening area ratio, so its uoi is the lowest among these three distributors. The mean solids concentration and suspension density in reactors with the different distributors are summarized in Table 4.6. The solids concentrations in section II in reactor 1 with distributor 1, 2, and 3 are 11.23%, 11.51%, and 11.54%, respectively. This indicates that varying the opening area ratio or ϕ does not substantially increase the mean solids concentration in section II. Varying the opening area ratio and ϕ affected the axial profile of solids concentration, primarily the local flow in the region just above the distributor, as shown in Fig. 4.12. Within the influenced region (H of 0 to 5 m), the reactor with distributor 1 was able to maintain relatively steady operation, whereas in the reactors with the other distributors, the solids concentration exhibited has an abrupt change at H ¼ 1–2 m. Because of the large opening area ratio of distributor 3, an abrupt increase in solids concentration appeared below the distributor (about H ¼ 2.5 m), implying that particle leakage occurred with distributor 3 with 169 orifices with ϕ ¼ 100 mm and an opening area ratio of 14.6%. Figure 4.13 presents the distribution of time-averaged solids concentration of the whole bed. Obviously, among these cases, the reactor with distributor 1 displays the most even distribution of time-averaged solids concentration. For the reactors with other two distributors, regions with very low solids concentration were observed in the vicinity of the distributor. A larger ϕ and smaller n led to greater heterogeneity of the time-averaged solids concentration, as shown in Fig. 4.13b. Just above the distributor, an arc-shaped “vacant zone” formed because of the jet flow. The reactor with distributor 3 showed the smallest vacant zone because it had the lowest uoi, whereas the vacant zones in the other cases were of similar size. Table 4.7 summarizes the pressure drop over the different distributors and section II or reactor 1. At the same opening area ratio of the distributor, a larger ϕ gave rise

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4 Multiscale CFD Simulation for DTFB Scale-Up

Fig. 4.12 Axial profiles of cross-sectional timeaveraged solids concentration for the industrial DTFB reactor 1 with different distributors (“0” on the vertical axis corresponds to the position of the distributor)

Fig. 4.13 Distribution of time-averaged solids concentration throughout the whole bed in DTFB reactor 1 with arc-shaped perforated plate distributor (a) 1 (n ¼ 390, ϕ50 mm, 8.43%), (b) 2 (n ¼ 98, ϕ100 mm, 8.47%), and (c) 3 (n ¼ 169, ϕ100 mm, 14.6%)

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127

Table 4.7 Pressure drop of different distributors and section II of the industrial DTFB reactor 1 Distributor Distributor 1 (390,ϕ50, 8.43%) Distributor 2 (98,ϕ100, 8.47%) Distributor 3 (169,ϕ100, 14.6%)

Pressure drop of distributor, ΔPdis (kPa) 4.57

Pressure drop of section II, ΔPII (kPa) 21.01

ΔPdis/ΔPII (%) 21.76

5.12

21.86

23.42

2.82

19.23

14.60

Table 4.8 Mean solids concentration and suspension density in each section of the industrial DTFB reactor 1 at different supplementary solids feed rates WsII WsII (t/h) 300 600 (base) 1014

Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3)

Section I 1.19 17.78 1.19 17.80 1.20 18.02

Section II 10.95 164.28 11.42 171.35 11.68 175.13

Exit tube 2.13 31.93 2.59 38.89 3.11 46.70

Whole bed 9.11 136.67 9.72 145.73 10.07 151.04

to larger pressure drop throughout the distributor, probably because less orifices with larger ϕ more readily caused the phenomenon of bias current where most particles flowed through orifices in the center of the distributor, leaving some orifices near the wall disabled. As seen from Table 4.7, ΔPdis/ΔPII for the reactor with distributor 3 was about 14.60%, which was much lower than those for reactor 1 with the other two distributors.

4.3.2.2

Effect of Supplementary Solids Feed Rate

The supplementary solids feed is used to regulate the solids concentration and temperature in section II. Here, the flow hydrodynamics with three different supplementary solids feed rates WsII of 300, 600, and 1014 t/h were investigated. The gas velocity of section I, UgI and the solids feed rate to section I, WsI, are kept the same as those in the base operating conditions shown in Table 4.5. The influence of WsII on the mean solids concentration of each section is summarized in Table 4.8. It is clearly seen that the increase of WsII from 300 to 1014 t/h caused the mean solids concentration in section II and the exit tube to increase substantially, whereas it had little influence on section I. Figure 4.14 presents the axial profiles of cross-sectional time-averaged solids concentration and pressure of reactor 1 with different WsII. The solids concentration just above the distributor (H ¼ 0–2.5 m) and in the exit tube was strongly affected by

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4 Multiscale CFD Simulation for DTFB Scale-Up

Fig. 4.14 Axial profiles of (a) cross-sectional time-averaged solids concentration and (b) pressure for the industrial DTFB reactor 1 at different supplementary solids feed rates WsII

the supplementary solids feed, increasing with WsII. All pressures at each elevation shown in Fig. 4.14b increased with WsII, whereas the pressure drop over the distributor remained almost constant regardless of supplementary solids feed rate. The distribution of time-averaged solids concentration shown in Fig. 4.15 reveals that a certain amount of particles accumulated below the feeding tube (at the right corner of the distributor) with increasing WsII, rendering a vacant zone just above the distributor because of the jet flow towards the left. As WsII increased, the accumulation of particles at the left corner of the distributor was mitigated.

4.3.2.3

Effect of Gas Velocity

Three cases with UgI of 10, 13, and 18 m/s were then simulated with other operating parameters kept as the same as those in Table 4.5 (WsI ¼ 1014 t/h, WsII ¼ 600 t/h, distributor 1 with n ¼ 390, ϕ ¼ 50 mm, and 8.43%). The influence of UgI on the mean solids concentration of each section is presented in Table 4.9. The increase of UgI from 10 to 18 m/s caused a large decrease of the mean solids concentration. When UgI was 18 m/s, the mean solids concentration in section II was only about 1.66%, which was very close to that in section I. The axial profiles of cross-sectional time-averaged solids concentration shown in Fig. 4.16 allow clear comparison of three cases with different gas velocities. When UgI was 18 m/s, the reactor operated in the dilute pneumatic transport regime with almost all cross-sectional averaged concentrations of less than 2%. Above the distributor, the solids concentration remained nearly constant with changing bed

4.3 Simulation of Industrial DTFB Reactors

129

Fig. 4.15 Distribution of time-averaged solids concentration for the industrial DTFB reactor 1 at different supplementary solid feed rates to section II WsII of (a) 300 t/h, (b) 600 t/h, and (c) 1014 t/h Table 4.9 Mean solids concentration and suspension density of each section of the industrial DTFB reactor 1 with different gas velocities of section I, UgI UgI (m/s) 10 13 (base) 18

Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3)

Section I 1.59 23.82 1.19 17.80 0.84 12.54

Section II 13.25 198.81 11.42 171.35 1.66 24.94

Exit tube 3.64 54.64 2.59 38.89 1.70 25.46

Whole bed 11.56 173.40 9.72 145.73 1.64 24.61

height. When UgI was lowered to 13 m/s, the solids concentration in section II increased substantially, whereas only slight increases of solids concentration were observed in section I and the exit tube. When UgI was further decreased to 10 m/s, the solids concentration throughout the whole bed increased, indicating that dense upflow was achieved. Figure 4.16b presents the corresponding pressure profiles at the three UgI considered. The pressure profile at UgI ¼ 18 m/s shows slight variation in section I and section II with changing bed height, indicating very dilute flow therein.

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4 Multiscale CFD Simulation for DTFB Scale-Up

Fig. 4.16 Axial profiles of (a) cross-sectional time-averaged solids concentration and (b) timeaveraged pressure at different gas velocities of section I, UgI

The three different UgI corresponded to evidently different distributions of timeaveraged solids concentration, as illustrated in Fig. 4.17. Dense upflow was observed at UgI ¼ 10 m/s and dilute pneumatic transport arose at UgI ¼ 18 m/s. For the case with UgI ¼ 13 m/s, the dense region spreads over almost all of section II, so it can be expected that a further decrease of UgI or increase in solids feed rate will result in the appearance of dense upflow.

4.3.3

Industrial DTFB Reactor 2

4.3.3.1

Effect of Opening Area Ratio of the Distributor

The base operating conditions of the industrial DTFB reactor 2 are listed in Table 4.5; that is, UgI ¼ 13 m/s, WsI ¼ 1840 t/h, WsII ¼ 1000 t/h, and an arc-shaped perforated plate distributor with n ¼ 516, ϕ ¼ 50 mm, and 7.3% mounted at the bottom of section II. For the industrial DTFB reactor 2, the effects of opening area ratio were first investigated by changing n and ϕ. Table 4.10 summarizes the mean solids concentration in each section. Table 4.10 reveals that no obvious change in the mean solids concentration occurred with increasing opening area ratio of the distributor, whereas the opening area ratio strongly affected the axial profiles of solids concentration, as shown in Fig. 4.18. Distributor 2 showed a smooth change in solids concentration with changing bed height.

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131

Fig. 4.17 Distribution of time-averaged solids concentration throughout the industrial DTFB reactor 1 at different gas velocities in section I, UgI, of (a) 10 m/s, (b) 13 m/s, and (c) 18 m/s Table 4.10 Mean solids concentration and suspension density in each section of the industrial DTFB reactor 2 with distributors with different opening area ratios Distributor Distributor 1 (516,ϕ50, 7.3%) Distributor 2 (197,ϕ100,11.2%)

Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3)

Section I 2.13 31.93

Section II 11.97 179.49

Exit tube 4.76 71.36

Whole bed 10.27 154.10

2.21 33.20

11.80 177.06

4.44 66.57

10.05 150.67

Figure 4.19 illustrates the fluctuation of the cross-sectional averaged solids concentration at H ¼ 4 m above the distributor and further indicates that the reactor with distributor 1 (n ¼ 516, ϕ ¼ 50 mm, 7.3%) showed much greater fluctuation of

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4 Multiscale CFD Simulation for DTFB Scale-Up

Fig. 4.18 Axial profiles of cross-sectional timeaveraged solids concentration for the industrial DTFB reactor 2 with distributors with different opening area ratios

Fig. 4.19 Variation of cross-sectional average solids concentration at a height of 4 m

solids concentration above the distributor than the case for the reactor with distributor 2 (n ¼ 197, ϕ ¼ 100 mm, 11.2%). The same behavior was also detected from the time series of solids concentration and pressure at other H. This is probably because the opening area ratio of distributor 2 (11.2%) approaches D2I =D2II (~11.1%), where DI and DII are the diameters of section I and section II, respectively, rendering a small difference between the UgI and cross-sectional average gas velocity in section II. This indicates that an opening area ratio of the distributor close to D2I =D2II is favorable to achieve steady operation in section II. Table 4.11 presents the pressure drop over the distributors with two different opening area ratios. It can be seen that distributor 1 has a large pressure drop over

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133

Table 4.11 Pressure drop of distributors and section II of the industrial DTFB reactor 2 with arc-shaped perforated plate distributors with different opening ratios

Distributor Distributor 1 (516, ϕ50, 7.3%) Distributor 2 (197, ϕ100, 11.2%)

Pressure drop of distributor, ΔPdis (kPa) 4.81

Pressure drop of zone II, ΔPII (kPa) 18.14

ΔPdis/ΔPII (%) 26.51

2.84

16.12

17.61

Fig. 4.20 Distribution of time-averaged solids concentration throughout the industrial DTFB reactor 2 with different arc-shaped perforated plate distributors (a) 1 (n ¼ 516, ϕ ¼ 50 mm, 7.3%) and (b) 2 (n ¼ 197, ϕ ¼ 100 mm, 11.2%)

section II (ΔPII) of 26.51%, whereas ΔPII of distributor 2 is 17.61%. Figure 4.20 depicts the distribution of time-averaged solids concentration. The reactor with distributor 2 showed a relatively more homogeneous distribution of solids concentration than the case for the reactor with distributor 1, because no low-concentration regions in the vicinity of wall were detected.

134

4.3.3.2

4 Multiscale CFD Simulation for DTFB Scale-Up

Effect of Distributor Structure

Besides the opening area ratio, three distributor structures, i.e., arc-shaped, basinshaped and cone-shaped perforated plate with the same opening area ratio of 11.2%, n ¼ 197, and ϕ ¼ 100 nm were investigated. Figure 4.21 presents schematics of the three different distributors. Other operating parameters are listed in Table 4.5. The effect of the distributor structure on the mean solids concentration is presented in Table 4.12. Unlike the opening area ratio or orifice-related parameters, the distributor structure played a certain role in changing the solids concentration of section II. The reactor mounted with the basin-shaped distributor showed the highest mean solids concentration in section II among the three cases. To explore the underlying cause of the change of the solids concentration in section II with distributor structure, more hydrodynamic details are considered. Figure 4.22 presents the axial distribution of cross-sectional time-averaged vertical gas velocity. The lowest vertical gas velocity in section II was found for reactor 2 with the basin-shaped distributor among the three cases. For the basin-shaped distributor, the orifices distributed in its side face partially changed the flow direction and thus decreased the vertical component of gas velocity. Other factors with respect to the distributor such as the pressure drop and the degree of uniformity also need be considered for thorough distributor evaluation. Figure 4.23 compares the distributions of solids concentration in DTFB reactor 2 with the three distributors. For the reactor with the basin-shaped distributor, the cross flow in the region near the distributor improved the gas–solid mixing, thus providing a relatively homogeneous distribution of mean solids concentration above the distributor. Serious leakage was detected in the case of the cone-shaped distributor, where the slanted plate of the distributor increased the downward force exerted on the particles almost above the orifice in the center. A more heterogeneous distribution of mean solids concentration was also found in the reactor with the cone-shaped distributor than in that with the basin-shaped distributor. The pressure profiles of reactor 2 with the three different distributors are shown in Fig. 4.24. The region near the distributor is different in the three systems. Below the position of H ¼ 0, the basin- and cone-shaped distributors showed smooth changes in pressure whereas the arc-shaped distributor exhibited an abrupt change. Accordingly, the pressure drop over the arc-shaped distributor was larger than that for other two cases. Because large fluctuations of pressure often occur in the transition region or near the internal/inlet/outlet, the solids concentration converted from the measured pressure drop is therefore less reasonable for the system with the arc-shaped distributor compared with that of the reactors with basin- and cone-shaped distributors.

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135

Fig. 4.21 Schematics of an (a) arc-shaped perforated plate distributor (n ¼ 197, ϕ ¼ 100 nm, 11.2%), (b) basin-shaped perforated plate distributor (n ¼ 197, ϕ ¼ 100 nm, 11.2%), and (c) coneshaped perforated plate distributor (n ¼ 197, ϕ ¼ 100 mm, 11.2%)

136

Fig. 4.21 (continued)

4 Multiscale CFD Simulation for DTFB Scale-Up

4.3 Simulation of Industrial DTFB Reactors

Fig. 4.21 (continued)

137

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4 Multiscale CFD Simulation for DTFB Scale-Up

Table 4.12 Mean solids concentration and suspension density in each section of industrial DTFB reactor 2 with different distributors Distributor Distributor 1: Arc-shaped Distributor 2: Basinshaped Distributor 3: Coneshaped

Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3)

Section I 2.21 33.20

Section II 11.80 177.06

Exit tube 4.44 66.57

Whole bed 10.05 150.67

2.08 31.20

12.60 188.77

5.60 84.01

10.31 154.71

2.52 37.83

12.08 181.25

5.59 83.85

9.70 145.47

Fig. 4.22 Axial profiles of time-averaged gas velocity in section II of DTFB reactor 2 with different distributors

4.3.3.3

Effect of the Structure of the Secondary Feeding Tube

Because the supplementary solids feed to section II strongly affects the solids concentration and formation of the dene region in section II, the angle between the feeding tube and section II θ may also influence the operation of section II and gas– solid mixing. In the base operating condition in Table 4.5, θ, is 45 . Here, two cases with θ of 135 and 100 were investigated. Table 4.13 lists the mean solids concentration at different θ and shows that there was no evident change in the solids concentration with varying θ.

4.3 Simulation of Industrial DTFB Reactors

139

Fig. 4.23 Distribution of time-averaged solids concentration for the industrial DTFB reactor 2 with different perforated plate distributors: (a) arc-shaped (n ¼ 197, ϕ ¼ 100 mm, 11.2%), (b) basinshaped (n ¼ 197, ϕ ¼ 100 mm, 11.2%), and (c) cone-shaped (n ¼ 197, ϕ ¼ 100 mm, 11.2%) Fig. 4.24 Axial profiles of time-averaged pressure for DTFB reactor 2 with different perforated plate distributors

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4 Multiscale CFD Simulation for DTFB Scale-Up

Table 4.13 Mean solids concentration and suspension density in each section of industrial DTFB reactor 2 with different angles between section II and the secondary feeding tube θ 45 135 100

Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3)

Section I 2.13 31.93 2.15 32.24 2.13 32.03

Section II 11.97 179.49 12.01 180.13 12.06 180.91

Exit tube 4.76 71.36 5.04 75.59 5.17 77.58

Whole bed 10.27 154.10 10.34 155.05 10.30 154.48

Fig. 4.25 Axial profiles of cross-sectional timeaveraged solids concentration for industrial DTFB reactor 2 with different angles between the secondary feeding tube and section II

Feedstock injection has been reported strongly affect the backmixing of particles [57, 58]. Chen et al. [57, 58] found that a large angle between the feeding tube and riser (upward injection), θ, could give rise to secondary flow in the region near the injection because of the transverse lift effect. The secondary flow adheres to the wall and swings alternately with respect to time and space, which strongly affects its timeaveraged behavior. The particles accumulated in the region where there is secondary flow detach from the wall, merging into the mainstream of the jet, and the backmixing is strengthened. Because the cases with angles of 100 and 135 had similar results, the case with θ ¼ 135 was selected to compare with that with θ ¼ 45 . As shown in Fig. 4.25, the change of θ primarily affected the distribution of solids concentration near the feeding tube. Above an H of 4 m, the axial profiles of solids concentration were similar for the two cases.

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141

Fig. 4.26 Distribution of time-averaged solids concentration throughout the whole industrial DTFB reactor 2 with angles between the secondary feeding tube and section II, θ, of (a) 45 and (b) 135

Figure 4.26 more clearly shows the effects of θ on the local solids distribution. With increasing θ, the area of vacant zone caused by the jet flow decreased. This means that the residence time of solid particles in the enlarged section may be increased, which is consistent with the findings of Chen et al. [57, 58] In addition, an obvious dilute region formed in the vicinity of the wall close to the feeding tube, which was probably caused by the transverse lift effect [57, 58]. The pressure profiles at different θ are shown in Fig. 4.27. A larger θ of 135 resulted in a smooth transition of pressure through the distributor region, whereas a smaller θ of 45 (downward injection) led to an abrupt change in the pressure profile. These results reveal that θ has almost no effect on the solids concentration in the enlarged reaction zone, but it is closely related to the operating stability. A larger θ seems facilitates a steady transition between the first and second reaction zones.

4.3.3.4

Effect of the Diameter of the Exit Tube

The diameter of the exit tube (DIII) affects the velocity in the exit section of the reactor. Here, four cases with DIII of 1.36, 2.0, 2.5, and 3.0 m were examined using

142

4 Multiscale CFD Simulation for DTFB Scale-Up

Fig. 4.27 Axial profiles of cross-sectional timeaveraged pressure with different angles between the feeding tube and section II

Table 4.14 Mean solids concentration and suspension density of each section of industrial DTFB reactor 2 with exit tubes with different diameters Diameter the exit tube, DIII (m) 1.36

2.0

2.5

3.0

Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3)

Section I 2.13

Section II 11.97

Section III (Exit tube) 4.76

Whole bed 10.27

31.93

179.49

71.36

154.10

2.11

12.14

5.40

10.30

31.61

182.15

80.64

154.53

2.11

11.97

6.75

10.24

31.66

179.52

101.25

153.55

2.11

12.19

7.31

10.45

31.65

182.88

109.70

156.73

the base operating conditions (Table 4.5). The effects of DIII on the mean solids concentration in each section are summarized in Table 4.14. Increasing DIII resulted in a higher solids concentration in the exit tube but did not influence the solids concentration in the other sections. However, the variation of DIII affected the axial distribution of solid particles, as shown in Fig. 4.28a. A larger DIII gave a smoother

4.3 Simulation of Industrial DTFB Reactors

143

Fig. 4.28 Axial profiles of (a) cross-sectional time-averaged solids concentration and (b) pressure for industrial DTFB reactor 2 with exit tubes with different diameters

change of solids concentration between section II and the exit tube. However, the increase of DIII led to serious solid backflow because of the decrease of the velocity in the exit tube, particularly in the case of DIII ¼ 2.5 m. The axial pressure profiles presented in Fig. 4.28b show that the case with DIII ¼ 1.36 m had the largest total pressure drop of these four cases; the other three had almost the same pressure drop.

4.3.3.5

Effect of the Structure of the Exit Tube

Besides the diameter of the exit tube, its structure is another factor that also influences the hydrodynamics in the second reaction zone. Here, two structures, one with a constricted top exit and other with a side exit, as pictured in Fig. 4.29, were compared. Table 4.15 reveals that modification of the traditional exit with a constricted top to the side exit resulted in a decrease of the solids concentration in section II from 11.97% to 10.69%. The axial profiles of solids concentration were quite different for the two cases with different exit structures, as illustrated in Fig. 4.30. There was an abrupt drop in solids concentration near the side exit. An obvious dilute region formed at the top of the second reaction zone for the setup with the side exit (Fig. 4.31). A large number of particles accumulated at the corner and wall of the side exit. The side exit also caused a bigger pressure drop than that of the traditional exit, as presented in Fig. 4.32. Figure 4.33 depicts the radial profiles of vertical solids velocity at H of 4 and 6 m. As H was closer to the exit, the velocity became more asymmetric in the case with the side exit.

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4 Multiscale CFD Simulation for DTFB Scale-Up

Fig. 4.29 (a) Traditional constricted top and (b) side exit structures of industrial DTFB reactor 2 Table 4.15 Mean solids concentration and suspension density of each section of industrial DTFB reactor 2 with exit tubes with different configurations Structure of exit section Top shrunk exit

Sideway exit

4.3.3.6

Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3)

Section I 2.13 31.93

Section II 11.97 179.49

Exit tube 4.76 71.36

Whole bed 10.27 154.10

2.19 32.85

10.69 160.35

5.36 80.42

9.42 141.22

Effect of Supplementary Solids Feed Rate

The introduction of an enlarged second reaction zone primarily aims to provide an environment that promotes isomerization and hydrogen transfer reactions. Therefore, the solids concentration (solids residence time) and temperature are two important parameters of the second reaction zone. The supplementary solids feed rate in section II, WsII, can be used to regulate the solids concentration as well as the

4.3 Simulation of Industrial DTFB Reactors

145

Fig. 4.30 Axial profiles of cross-sectional timeaveraged solids concentration for DTFB reactor 2 with exit tubes with different structures

Fig. 4.31 Distribution of time-averaged solids concentration throughout industrial DTFB reactor 2 with (a) constricted top and (b) side exit tubes

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4 Multiscale CFD Simulation for DTFB Scale-Up

Fig. 4.32 Axial profiles of pressure drop for industrial DTFB reactor 2 with exit tubes with different structures

Fig. 4.33 Radial profiles of time-averaged vertical solids velocity at heights of 4 and 6 m for industrial DTFB reactor 2 with exit tubes with different structures

4.3 Simulation of Industrial DTFB Reactors

147

Table 4.16 Mean solids concentration and suspension density of each section of industrial DTFB reactor 2 at different supplementary solids feed rates to section II, WsII WsII (t/h) 500 1000 1840

Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3)

section I 2.11 31.64 2.13 31.93 2.11 31.70

section II 11.75 176.24 11.97 179.49 12.20 183.01

Exit tube 3.58 53.67 4.76 71.36 6.11 91.68

Whole bed 9.94 149.05 10.27 154.10 10.60 158.98

Fig. 4.34 Axial profiles of (a) cross-sectional time-averaged solids concentration and (b) pressure for industrial DTFB reactor 2 at different supplementary solids feed rates to section II, WsII

temperature if low-temperature catalysts are fed to section II. Here, we focus on the effects of the WsII on the solids concentration and distribution of solids concentration in the second reaction zone. WsII of 500, 1000, and 1840 t/h are investigated while keeping other operating parameters unchanged (UgI ¼ 13 m/s and WsI ¼ 1840 t/h). As presented in Table 4.16, the increase of feed rate WsII from 500 to 1840 t/h led to an evident increase of solids concentration in section III (exit tube) but not in section II. As discussed in Sect. 4.2.2, when a reactor is operated at the choking state with the dense region spreading throughout section II, the increase of I cannot further increase the solids concentration of section II. Thus, we may infer that the reactor operating under the conditions of UgI ¼ 13 m/s, WsI ¼ 1840 t/h, and WsII ¼ 500 t/h has already entered a choking regime that is near the dense upflow regime. This means that the relationship between WsII and solids concentration in section II depends the operating flow state. This will be discussed further in Sect. 4.3.4. Figure 4.34 presents the axial profiles of cross-sectional time-averaged solids concentration and pressure for the setups with different WsII. The solids

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4 Multiscale CFD Simulation for DTFB Scale-Up

Fig. 4.35 Distribution of time-averaged solids concentration of industrial DTFB reactor 2 at different supplementary solid feed rates, WsII, of (a) 500 t/h, (b) 1000 t/h, and (c) 1840 t/h

concentration in the exit tube and the region with H ¼ 0–2 m increased with WsII. The increase of pressure shown in Fig. 4.34 is caused by the increased total I. Figure 4.35 shows that with increasing WsII, the dense region gradually spread out of section II to the exit tube and a number of particles accumulated near the feeding tube. The influence of WsII on the jet zone above the distributor was almost negligible.

4.3.3.7

Effect of Gas Velocity

UgI is undoubtedly the main factor influencing the flow hydrodynamics in DTFB reactor 2. Here, different UgI at WsI ¼ 1840 t/h and WsII ¼ 1000 t/h were investigated. Table 4.17 compares the mean solids concentrations at different UgI. As shown in Table 4.17 and Fig. 4.36, UgI has a remarkable influence on the solids concentration. When UgI ¼ 8 m/s, the mean solids concentration in section II is about 15% and that in section III is about 8%, corresponding to the dense transport regime with the biggest pressure drop of the three cases. As UgI increased up to 18 m/ s, the solids concentration throughout the reactor decreased greatly, but the change of UgI from 13 to 18 m/s only caused a slight change in the solids concentration in

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149

Table 4.17 Mean solids concentration and suspension density of each section of industrial DTFB reactor 2 at different gas velocities in section I, UgI UgI (m/s) 8 13 18

Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3) Mean solids con. (%) Suspension density (kg/m3)

Section I 4.46 66.84 2.13 31.93 1.86 27.96

Section II 15.06 225.88 11.97 179.49 11.08 166.17

Exit tube 7.98 119.75 4.76 71.36 4.46 66.90

Whole bed 13.53 202.88 10.27 154.10 9.47 142.06

Fig. 4.36 Axial profiles of (a) cross-sectional time-averaged solids concentration and (b) pressure for industrial DTFB reactor 2 at different gas velocities in section I, UgI

the second reaction zone. The axial pressure profiles at different UgI also showed a similar trend. With increasing UgI, the jet zone above the distributor was also clearly affected. As shown in Fig. 4.37, when UgI ¼ 8 m/s, a small jet zone formed just above the distributor and a layer of solid particles emerged along the wall of the diffuser. When UgI increased to 13 m/s, a steady jet zone formed, and the solid layer near the diffuser wall disappeared. When UgI increased further to 18 m/s, the jet zone changed slightly and less particles accumulated near the feeding tube.

150

4 Multiscale CFD Simulation for DTFB Scale-Up

Fig. 4.37 Distribution of time-averaged solids concentration in industrial DTFB reactor 2 at different gas velocities in section I, UgI, of (a) 8 m/s, (b) 13 m/s, and (c) 18 m/s

4.3.4

Choking Prediction

As discussed above, it is known that UgI and WsII feed rate are important to regulate the solids concentration in the second reaction zone. However, the relationship between these parameters and the solids concentration of section II also depends on the operating conditions and flow regime. Therefore, obtaining a flow map and operating points in the flow map are of great importance to determine suitable operating parameters. In Sect. 4.2.2, we predicted a flow regime transition with choking in a cylindrical riser. In the following, a series of simulations with varying solids inventory I at a specified UgI for two industrial DTFB reactors is carried out. For industrial DTFB reactor 1, as shown in Fig. 4.38, point a with a small I corresponds to the dilute pneumatic transport regime where the solids concentration keeps nearly constant with increasing bed height except in the distributor region. As I increases, Gs becomes saturated; this state corresponds to the horizontal line in Fig. 4.38a. On the right-hand side of the horizontal line, the system is in the dense upflow state. The three operating points investigated in Sect. 4.3.2.2 all fall into the choking regime. Therefore, we can see that in the choking regime and before achieving the state of dense upflow, the increase of solids concentration contributes

4.3 Simulation of Industrial DTFB Reactors

151

Fig. 4.38 Flow regime transitions for industrial DTFB reactor 1. (a) Solids flux Gs (kg/m2s) against imposed total pressure at UgI ¼ 13 m/s (UgII ¼ 1.9 m/s) ΔP. (b) Axial profiles of solids concentration at operating point a–d in (a) [36]

directly to the increase of solids concentration and the height of dense bottom in section II. Figure 4.38b clearly shows the difference between two states in the choking regime; that is, the two states have the same solids concentration in the upper region but different heights of dense bottom. Because all the operating points on the horizontal line correspond to the same Gs, i.e., saturation carrying capacity, Ug and Gs alone cannot determine the flow state. This point should be paid attention in industrial operation. In the choking state, the increase of solids feeding does not result in the increase of Gs expected by industrial practitioners, until the whole of section II is occupied by a dense transport state. The misunderstanding of choking behavior may make it difficult to regulate the solids feed rate during operation and thus an abrupt rise of pressure drop may occur. From such an abrupt rise of pressure drop, it is difficult to return to normal operation within a short period of time because of the long circulation line in industrial units, thus leading to an undesired shutdown of the reactor. The flow regime map for industrial DTFB reactor 2 was also obtained in the same way and is shown in Fig. 4.39. It is noted that all three operating points of WsII ¼ 300, 600, and 1014 t/h were in the dense upflow regime. Because the second reaction zone has reached a saturation state, further increase of WsII will increase the solids concentration in the exit tube. Therefore, this flow map can explain the findings discussed in Sect. 4.3.3.6 of the effect of WsII on DTFB reactor performance. Although the choking phenomenon is closely related to Ug, I, Gs, and geometrical factors such as bed height, in practical operation, the rapid increase of UgI is possibly the only effective way to avoid or delay the occurrence of choking.

152

4 Multiscale CFD Simulation for DTFB Scale-Up

Fig. 4.39 Flow regime transitions for industrial DTFB reactor 2. (a) Solids flux Gs (kg/m2s) against imposed total pressure at UgI ¼ 13 m/s (UgII ¼ 1.444 m/s) ΔP. (b) Axial profiles of solids concentration at operating point a–d in (a) [56]

4.4

Reactive Simulation of a 1.2-Mt/a Industrial DTFB Reactor

To further scale up the current DTFB unit for a chemical process, more information on both hydrodynamics and reaction behaviors is needed. In the following, taking the MIP process as an example, we aim to realize a 3D reactive simulation of a realistic industrial DTFB reactor during hot operation to obtain more information about such a system.

4.4.1

Geometry

Figure 4.40 shows a schematic diagram of the 120-Mt/a feedstock industrial MIP reactor installed in the SinoPec Huizhou Refinery. The entire reactor has three zones (the prelift zone was excluded in the simulation): section I with ID ¼ 0.95 m and H ¼ 10.75 m, section II with ID ¼ 2.9 m and H ¼ 9 m, and an exit tube with ID ¼ 0.9 m and H ¼ 20 m. A basin-shaped perforated plate distributor is mounted at the bottom of the second reaction zone. The supplementary feeding tube is installed 1.2 m above the distributor bottom.

4.4 Reactive Simulation of a 1.2-Mt/a Industrial DTFB Reactor Fig. 4.40 Schematic diagram of the 3D MIP reactor: 1 is the primary inlet, 2 is the secondary inlet, and 3 is the pressure outlet

153

154

4.4.2

4 Multiscale CFD Simulation for DTFB Scale-Up

Mathematical Equations

With development of the CFD technique, more and more researchers have tried to couple complex chemical reaction kinetics and flow dynamics equations such as the continuum model. The multiscale CFD approach is useful to capture cluster structures and predict macroscale parameters such as Gs and choking. When reactions occur in a DTFB reactor, the physical properties of the gas phase will change, which in turn influences the flow structures and heat transfer. In the following, we consider the effects of heterogeneous flow structures on both momentum and heat transfer using a reactive simulation model. The multiphase Eulerian–Eulerian model was used and related governing equations have been described above in Sect. 4.1. The solid phase stress was closed by the KTGF and the gas–solid drag was described using the EMMS-matrix drag model.

4.4.2.1

Gas–Solid Drag

As discussed in Sect. 4.1.3, the drag force is strongly affected by flow structures, and thus drag models that take into account the effects of heterogeneous structures are becoming increasingly popular in the simulation of gas–solid fluidization. The EMMS-based drag model is a structure-dependent model that is widely employed in both academia and industry because of its ease of use and clear physics. Because many more grids are required to mesh a full-scale 3D reactor compared to the number needed for 2D geometry, the EMMS-matrix model [3, 4], which has been proved to have higher accuracy and lower grid-size sensitivity than its previous model [2], is suitable for coarse-grid simulations of such a full-scale large 3D reactor. Through the integration of the EMMS-matrix model into the TFM, one does not need to carry out a series of tests on grid dependence before starting numerical experiments. Because of the complex reactor geometry and corresponding unstructured grids, a strict evaluation of grid dependence is an impossible task. Therefore, applying the EMMS-matrix drag model, which shows a weak dependence on grid size with certain numerical accuracy, is an efficient way to realize a reasonable coarse-grid simulation of a 3D large-scale reactor. To show the superiority of this structure-dependent drag model over the traditional homogenous model, a commonly used homogeneous model that was obtained from experiments on homogeneous fluidization, i.e., the Gidaspow model, is also used for comparison. Because the formation of clusters is mainly observed in the second reaction zone, the operating parameters Ug and Gs as well as physical properties of the gas phase used to obtain the EMMS-matrix drag coefficient were calculated based on the dimensions and operating conditions (such as temperature and pressure) of the second reaction zone. Table 4.1 lists the fitting formulas for the heterogeneity index HD for this industrial DTFB reactor for the MIP process (Table 4.18).

0:090227 0:32443εg0:00016 Þ

a ¼ 1:46525=ð4851:47  4898:19εg Þ0:565259

0:44496 1 þ ðεg =0:4973724:4191 Þ

b ¼ ð0:32443 þ

8 1 1 > >

a ¼ 0:234044 þ 1:66868 1  > > 1 þ exp ððεg  0:99984Þ=0:00059Þ ðεg  0:99504Þ > > > 1 þ exp  < 0:00269

> 1 1 > > b ¼ 0:20652  0:38268

1  > > 1 þ exp ððεg  0:99343Þ=0:01558Þ ðεg  0:99255Þ > > : 1 þ exp  0:00205 a ¼ 1, b ¼ 0

(

> > : b ¼ 0:40211 

g

H ¼ a(Res)b, Res ¼ dpUslipρg/μg, 0.001 Uslip 1000 8D 0:46621 > < a ¼ 0:73364  1 þ ðεg =0:42667Þ26:6505 > : b ¼ 243:79  2324:44ε þ 8305:91ε2  13183:38ε3 þ 7842:72ε4 g g g g 8 0:72306 > > < a ¼ 0:2314 þ 1 þ ðε =0:48708Þ36:8913

0.9997 εg 1

0.988 < εg < 0.9997

0.56747 < εg 0.988

0.45709 < εg 0.567

Range (εmf εg 1) 0.4 < εg 0.45709

Table 4.18 Fitting formulas for the heterogeneity index HD (ρs ¼ 1500 kg/m3, ρg ¼ 3.65 kg/m3, μg ¼ 1.3  105 Pas, dp ¼ 65 μm, Ug ¼ 1.67 m/s, Gs ¼ 34.6 kg/(m2s), εmf ¼ 0.4, εmax ¼ 0.9997)

4.4 Reactive Simulation of a 1.2-Mt/a Industrial DTFB Reactor 155

156

4.4.2.2

4 Multiscale CFD Simulation for DTFB Scale-Up

Heat Transfer Model

Given that the catalytic cracking reactions are fast and strongly endothermic, heat transfer should be considered in the reactive simulation. The traditional heat transfer coefficient was obtained based on homogeneous fluidization as follows, h¼

6λg εs εg Nus , d2p

ð4:40Þ

where λg is the thermal conductivity coefficient of the gas phase and Nus for gas– solid fluidization is usually calculated using the Gunn model [59] as follows, 1=3 Nus ¼ ð7  10εg þ 5ε2g Þð1 þ 0:7Re0:2 Þ g Pr 1=3 þ ð1:33  2:4εg þ 1:2ε2g ÞRe0:7 : s Pr

ð4:41Þ

Here, Pr is a dimensionless number with a definition of cpgμg/kg, where cpg is the specific heat capacity at constant pressure. Because the heat transfer is also affected by the distribution of flow structures, a new heat transfer coefficient [60] was proposed to account for the effects of mesoscale structure analogous to the formulation of EMMS drag, hD ¼ f

6λg εsc εgc Nusc 6λg εsf εgf Nusf þ ð1  f Þ 2 dp d 2p

ð4:42Þ

Likewise, the particles were assumed to be uniformly distributed in the dilute and dense phases, so the expression for each part followed the conventional formulation of the heat transfer model (Eq. 4.40). Consequently, hD was expressed as the respective contributions from the dilute and dense phases. In Eq. 4.42, f is the volume fraction of the dense phase and the Nusselt number Nu was determined using the Gunn model (Eq. 4.41). The structural parameters εsc, εgc, εsf, εgf, and f were obtained from the EMMS-matrix model.

4.4.2.3

Lumped Chemical Kinetic Model

A twelve-lumped chemical kinetic model that was established using laboratory-scale experiments and whose kinetic parameters were optimized by considering industrial operating data was used in this simulation. The network of the chemical reaction is shown in Fig. 4.41. There are 24 reaction pathways among the twelve lumps (i.e., Ph, Nh, Ah, Fh, Pm, Nm, Am, Fm, G, Gas1, Gas2, and C). Among these twelve lumps, Ph, Nh, Ah, and Fh belong to heavy oil (slurry); Pm, Nm, Am, and Fm belong to light oil (diesel); G refers to gasoline; Gas1 denotes liquefied petroleum gas (LPG); Gas2 denotes dry gas; and C represents the coke, which is converted from Fh, Fm, Gas1,

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157

Fig. 4.41 Reaction network of the 12-lump FCC kinetic model [60]

and G. Table 4.24 describes these different lumps in the chemical kinetic network and their boiling range (Table 4.19). The lumped reaction rate can be written as Rj ¼

N X

γ jp r p ,

ð4:43Þ

p¼1

where N is the total number of reaction pathways and γ jp is expressed as γ jp ¼ δij

Mi : Mj

ð4:44Þ

Where M is the molecular weight, kg/mol, i denotes the reactant in the reaction route p. If the route p is not linked to lump j, δij ¼ 0; else if, δij ¼ 1 at i 6¼ j (lump j is the product) and δij ¼ 1 at i ¼ j (lump j is the reactant). The rate of one reaction is expressed by 

E aref,p r p ¼ kref,p exp R



 1 1  φcat C mol,p , T g T ref

ð4:45Þ

Here, kref is the rate coefficient, Earef is the activation energy, Cmol,p is the molar concentration of the reactant on reaction pathway p, and φcat is the deactivation function with an expression of

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4 Multiscale CFD Simulation for DTFB Scale-Up

Table 4.19 Lumps of the 12-lump kinetic model [60] Cut Heavy oil

Light oil

Gasoline LPG Dry gas Coke

lump Ph: heavy paraffinics Nh: heavy naphthenics Ah: heavy aromatic substituent groups Fh: heavy aromatic ring carbons Pm: medium paraffinics Nm: medium naphthenics Am: substituent groups in medium aromatic Fm: carbons in medium aromatic ring G: gasoline Gas1: primary gaseous products Gas2: secondary gaseous products C: coke

Boiling range ( C) > 342 > 342 > 342 > 342 216~342 216~342 216~342 216~342 C5~216 C3 + C4 C1 + C2 + H2

φcat ¼ ð1 þ 51Y cat Þ2:78 :

ð4:46Þ

The catalytic cracking reaction is endothermic and the heat produced can be calculated using the following equation, Qcoke ¼ ðR12 M Fh þ R19 M Fm þ R22 M G þ R24 M Gas1 Þρcat εcat ΔH coke ,

ð4:47Þ

where εcat represents the volume fraction of catalyst, ρcat is the density of catalyst particles, and ΔHcoke is the heat of coke formation (6648.889 kJ/kg). In practical simulations, Qcoke can be treated as a source in the energy conservation equation and is a negative term on the right-hand side of the gas energy conservation. Table 4.20 lists the rate coefficient constant and activation energy of each reaction path. Physical properties including molecular weight, viscosity, specific heat capacity, thermal conductivity, and diffusion coefficient are summarized Table 4.21.

4.4.3

Simulation Settings

For hydrodynamic equations, a combination of the TFM and EMMS-matrix drag model was employed using FLUENT®6.2 as a solver. The 12-lump kinetic model described above was combined with hydrodynamic equations. The simulated geometry of the industrial DTFB reactor is shown in Fig. 4.40 and the prelift zone was not considered. It was assumed that the oil gas at inlet 1 was gasified instantly when it contacted with the high-temperature catalyst particles (see Fig. 4.40). Inlet 1 was specified as the mass flow inlet. Inlet 2 was used for supplementary feeding of the solid catalyst and was thus set with the velocity inlet. The pressure outlet was the top

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159

Table 4.20 Parameters of the 12-lump kinetic model [60]

Path number 1 2 3 4 5 6 7 8 9 10 11 12

Rate coefficient kref (103 m3/(kgcats)) 15.56 35.61 8.03 14.22 10.06 50.03 16.19 48.64 11.61 33.06 11.39 3.53

Activation energy Earef (kJ/mol) 38.45 32.60 45.98 38.45 45.98 32.60 38.45 63.53 81.53 38.45 38.45 81.53

Path number 13 14 15 16 17 18 19 20 21 22 23 24

Rate coefficient kref (103 m3/ (kgcats)) 18.94 3.89 24.03 2.44 12.92 0.94 0.32 0.35 0.04 0.08 0.41 1.35

Activation energy Earef (kJ/mol) 32.60 45.98 32.60 45.98 63.53 81.53 81.53 124.14 124.14 124.14 105.00 105.00

outlet with an absolute pressure of about 0.21 MPa and no-slip boundary conditions were employed for both gas and solid phases at the wall. Both phases were treated as mixtures in the simulation. The gas phase contained twelve species, i.e., Ph, Nh, Ah, Fh, Pm, Nm, Am, Fm, G, Gas1, Gas2, and steam. The first eleven species were gaseous lumps in the reaction kinetic model. Steam, which was fed into the first reactor to lift hot catalyst particles from the regenerator, did not participate in the reactions. As shown in Table 4.21, the physical properties of each species depended on temperature and pressure, so user-defined functions were written to integrate these equations into the simulation. The solid phase included catalyst particles and coke generated in the course of the reactions. It was assumed that the coke deposition did not change the physical properties of the catalyst particles and the surface ratio of deposited coke to catalysts (Ycat) was equal to the ratio of coke mass to the total mass of the solid mixture. All of the mass changes caused by reactions were included in the species transport equations in the form of sources. Note that the mass conservation equations of gas and solid phases also need to consider the mass change arising from coke generation, and the heat of endothermic reactions needs to be removed from the energy equation of the gas phase. In this study, because the prelift tube was not included, the inlet was set just above the entrance of the feed oil, where the oil was assumed to contact with the hot catalysts and instantly turn into a gaseous phase called oil gas. Some lower-temperature catalyst particles were fed into the second reaction zone to promote the alkene isomerization and hydrogen transfer reactions therein. The simulation ran for about 100 s and the last 20 s of data were averaged (Table 4.22).

10

g

10

g

g

g

g

8

9

λPh ¼ λNh ¼ λAh ¼ λFh ¼ 0:076 þ 1:028  104 T g λPm ¼ λNm ¼ λAm ¼ λFm ¼ 6:908  103 þ 1:028  104 T g λg ¼  0.0214 þ 1.028  104Tg λGas1 ¼  0.0132 þ 1.0284  104Tg λGas2 ¼  6.3683  103 þ 1.0284  104Tg λsteam ¼ 8:8682  103 þ 1:0371  104 T g þ 1:7518  109 T 2g þ 0:2001=T g

g

g g Þþ2

g Þþ2

3:5450510 þ T 2 ½expð1357:22=T Þ2 Þþexpð1357:22=T

g

6:67225109 T 2g ½expð1492:8=T g Þþexpð1492:8=T g Þþ2

g

g

9

9

g Þþ2

6:498910 þ T 2 ½expð1488:82=T Þþexpð1488:82=T

8:9875310 þ T 2 ½expð619:34=T Þþexpð619:34=T

þ

g Þ2

μPh ¼ μNh ¼ μAh ¼ μFh ¼ 3:3782  108 T 0:94 g μPm ¼ μNm ¼ μAm ¼ μFm ¼ 1:35872  108 T 0:94 g μg ¼ 2:24115  108 T 0:94 g μGas1 ¼ 5.5365  106(0.0116Tg  1.67)0.625 μGas2 ¼ 4.0828  106(0.01966Tg  1.67)0.625 μsteam ¼  1.9  106 þ 3.85  108Tg (4) Thermal conductivity, W/(mK)

Cp, steam ¼ 1910 þ 0.035Tg (3) Viscosity, Pas

g

5:0328710 C p,Gas2 ¼ 1507:3 þ T 2 ½expð3698:4=T Þþexpð3698:4=T

g

3:7547510 C p,Gas1 ¼ 1103:9 þ T 2 ½expð3081:2=T Þþexpð3081:2=T

C p,g ¼ 1328:82 þ

4:648531010 T 2g ½expð3271:2=T g Þþexpð3271:2=T g Þ2

g

g Þ2

10

g

4:2982210 þ T 2 ½expð1489:14=T Þþexpð1489:14=T

4:8050510 C p,Pm ¼ C p,Nm ¼ C p,Am ¼ C p,Fm ¼ 1230:19 þ T 2 ½expð3382:4=T Þþexpð3382:4=T

g g

g

g Þ2

2:4031310 C p,Ph ¼ C p,Nh ¼ C p,Ah ¼ C p,Fh ¼ 973:44 þ T 2 ½expð927:2=T Þþexpð927:2=T

9

(1) Molar mass, kg/kmol M Ph ¼ 461:16, M Nh ¼ 459:16, M Ah ¼ 461:16, M Fh ¼ 455:16 M Pm ¼ 209:75, M Nm ¼ 207:75, M Am ¼ 209:75, M Nm ¼ 203:75 Mg ¼ 102, MGas1 ¼ 50.93, MGas2 ¼ 19.11, Msteam ¼ 18 (2) Specific heat capacity, J/(kgK)

Table 4.21 Physical properties of gas species [60]

g Þþ2

160 4 Multiscale CFD Simulation for DTFB Scale-Up

DGas1 ¼ 20:055  P g DGas2 ¼ 24:066  105 T 1:75 g =P

105 T 1:75

DPh ¼ DNh ¼ DAh ¼ DFh ¼ 7:3457  105 T 1:75 g =P DPm ¼ DNm ¼ DAm ¼ DFm ¼ 9:8099  105 T 1:75 g =P 5 1:75 Dg ¼ 12:742  10 T g =P

(5) Diffusion coefficient, m2/s

4.4 Reactive Simulation of a 1.2-Mt/a Industrial DTFB Reactor 161

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4 Multiscale CFD Simulation for DTFB Scale-Up

Table 4.22 Operating parameters used in the simulation [60] Property/parameter Particle diameter dp, μm Particle density ρs, kg/m3 Primary inlet Solid volume fraction Catalyst mass flow rate, t/h Oil-gas mass flow rate, t/h Oil-gas temperature, K Catalyst temperature, K Composition Mass fraction Ph 0.1025 Nh 0.2461 Ah 0.3819 Fh 0.1304 Pm 0.0204 Nm 0.0227 Side inlet Solid volume fraction Catalyst mass flow rate, t/h Temperature, K Coke, %

4.4.4

Results and Discussion

4.4.4.1

Solids Volume Fraction

Value 65 1500 0.0893 803 146.27 772 782 Composition Am Fm G Gas1 Gas2 Steam

Mass fraction 0.0189 0.0092 0 0 0.0256 0.0423

0.045 20 763 0.012

Figure 4.42 shows the time evolution of solids concentration in the second reaction zone. The statistically averaged solids concentration is about 0.04, which is in good agreement with the experimental value (~0.041). For comparison, a simulation using the homogeneous model was also carried out, which predicted dilute flow. The simulation using the EMMS-matrix model took a much longer time (~80 s) to reach the pseudo-steady state than that with the homogeneous model (~30 s), which is probably because of abundant cluster formation and strong backmixing. To observe the whole process of particle accumulation in the second reaction zone, all simulations started from an empty bed. Figure 4.43 illustrates the instantaneous distribution of solids concentration throughout the entire reactor. In the first reaction zone, both simulations predict dilute pneumatic transport fluidization at the high Ug of 12 m/s, because the structure-dependent drag coefficient approaches the homogeneous model at the extremely dilute state, as illustrated in Fig. 4.2. In the second reaction zone, the solids distributions predicted by the two simulations were quite different. The typical features of fast fluidization in the form of heterogeneous flow structures and the coexistence of a dense bottom and dilute top were predicted using the EMMS-matrix model, whereas a relatively uniform distribution in both axial and

4.4 Reactive Simulation of a 1.2-Mt/a Industrial DTFB Reactor

163

Fig. 4.42 Time evolution of solids volume fraction in the second reaction zone predicted using homogeneous and EMMS models [60]

radial directions with lower solids concentration was predicted using the homogeneous model. In the exit tube, an abrupt rise in solids concentration was detected near the inverted L-shaped outlet by both simulations, which was largely attributed to the constricted diameter of the outlet.

4.4.4.2

Distribution of Temperature and Coke Content

Because solids concentration is closely related to the reaction rate, reactiondependent parameters such as overall conversion, coke content, and temperature are affected by the solids concentration. Figure 4.44 compares the axial temperature profiles determined from both simulations with the experimental data obtained from a stable industrial operation. The experimental data show the a biggest change, with a temperature decrease of about 10  C in the first reaction zone. In practice, the first reaction zone exhibits a bigger temperature change than those in the other zones because of the phase change of the feedstock and endothermic reactions. Because the phase change was neglected in this study, the temperature decrease of 10  C is primarily attributed to the catalytic cracking reactions. Besides the first reaction zone, the region in the vicinity of the distributor with H ¼ 1 to 2.5 m also showed an evident temperature drop of about 7  C. At higher H, the temperature variation was very slight. The temperate variation over the first reaction zone was under-predicted by both simulations, which was probably because the phase change of the feed oil at the inlet

164

4 Multiscale CFD Simulation for DTFB Scale-Up

Fig. 4.43 Instantaneous distributions of solids volume fraction throughout the entire reactor predicted by (a) the homogeneous model and (b) the EMMS-matrix drag model [60]

was ignored. The remarkable temperature gradient in the vicinity of the gas distributor was better captured by the EMMS-matrix model than by the traditional homogeneous model that did not include structural effects. In the second reaction zone, the temperature predicted using the EMMS-matrix model gradually decreased from about 502 to 490  C, whereas the simulation with the homogeneous model predicted higher temperature that underwent stepwise decay with increasing H. Both predictions gave similar results in the outlet tube. As well as temperature, the coke deposition on the catalysts is another parameter associated with reaction rate. Figure 4.45 presents the axial profiles of coke content. The simulations predicted identical coke contents in the first reaction zone. However, after entering the second reaction zone (above H ¼ 0), the difference in coke content predicted by the simulations increased until reaching the outlet. The simulation using the EMMS-matrix model predicted a coke content of about 2%, which was close to the experiment finding, revealing the good prediction of the solids

4.4 Reactive Simulation of a 1.2-Mt/a Industrial DTFB Reactor

165

Fig. 4.44 Axial profiles of catalyst temperature predicted using (a) homogeneous and (b) EMMSmatrix drag models. Black squares indicate experimental data [60]

concentration. In contrast, the simulation using the homogeneous model predicted a relatively lower coke content of about 1%.

4.4.4.3

Oil Gas Velocity

Figure 4.46 shows the variation of Ug along the bed height. Both simulations predicted identical Ug. In the first reaction zone, the oil gas velocity increased from 9 to 14 m/s because of the generation of more light species. In the diffuser, Ug decreased from 14 to ~2 m/s. Because gas expansion occurs simultaneously with the decrease of velocity as a result of reactor enlargement, the degree of the velocity decrease (14/2 ¼ 7) in Fig. 4.46 is not consistent with the diameter expansion ratio (2.92/0.952 9.3). Because the diameter of the exit section is similar to the diameter of the first reaction zone, the gas expansion caused by the reactions in the diffuser can be detected through comparison of the two velocity differences UgIII  UgII and UgII  UgI. In addition, it should be noted that almost no variation of Ug with the height of the second reaction zone was predicted by the simulations. This means that most reactions were completed in the first reaction zone, the diffuser, and the region just above the distributor.

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4 Multiscale CFD Simulation for DTFB Scale-Up

Fig. 4.45 Simulated axial profiles of the mass fraction of coke in the DTFB reactor [60]

4.4.4.4

Product Distribution

As mentioned above, because of its good prediction of solids concentration, the simulation using the EMMS-matrix model was found to provide more reasonable overall conversion and coke content values than the simulation using the homogeneous model. After achieving the pseudo-steady state, the mass fractions of all species can be obtained and they can be converted to the mass fraction of cuts (i.e., heavy oil, light oil, gasoline, LPG, and dry gas), as summarized in Table 4.23. It was found that although the simulation using the EMMS-matrix model predicted higher overall conversion (~98%) than that predicted by the homogeneous model, the mass fractions of gaseous products calculated from both simulations were similar. This is attributed to the reaction parameters such as rate constant and activation energy remaining unchanged despite the variation of temperature and flow structures. In other words, the chemical kinetic model lacks an accurate description of its connection with the flow field. A more reliable chemical kinetic model for heterogeneous reactions should take into account the effects of flow structures to improve reaction predictions, because the motion of solid catalysts and coke deposition are seriously affected by flow hydrodynamics. Table 4.24 lists the mass fractions of all gaseous species at the outlets of the first reaction zone and entire reactor. It can been observed that a large proportion of the

4.4 Reactive Simulation of a 1.2-Mt/a Industrial DTFB Reactor

167

Fig. 4.46 Simulated axial profiles of vertical gas velocity [60]

heavy oil, consisting of Ph, Nh, Ah, and Fh, has already been consumed when the gas mixture leaves the first reaction zone. Because the first section is operated in the dilute pneumatic transport regime with a homogeneous distribution, the chemical kinetic model that is based on the assumption of a homogeneous distribution and neglects the effects of external diffusion can reasonably predict product distribution; e.g., the slurry was predicted well. In the second reaction zone, an obvious change in the mass of the light oil (Pm, Nm, Am, and Fm) was observed. Compared to the prediction using the homogeneous model, the simulation employing the structuredependent model predicted a larger change in the light oil because it captured a much higher solids concentration. Comparing Tables 4.23 and 4.24 reveals both simulations gave similar predictions of the mass fractions of cuts, but they show evident differences in the predicted mass fractions of gaseous species. This indicates that considering the effects of flow structures on the drag and heat transfer helped to improve the prediction of product distribution, because the reaction rate is closely related to the coke content and temperature. However, the current reaction predictions indicate that the reaction is so fast that there only a slight change in the product distribution in the second reaction section. Further fundamental research on the chemical kinetic model is required, for example, more lumps are needed to account for the hydrogen transfer and

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4 Multiscale CFD Simulation for DTFB Scale-Up

Table 4.23 Comparison of the predicted mass fraction of each lump with experimental data [60]

Cut Heavy oil (slurry) Light oil (diesel) Gasoline LPG Dry gas Coke Loss Total

Experiment /% 2.54 24.87 40.55 22.22 2.51 6.86 0.44 100

Homogeneous Mass fraction /% 2.83 22.16 53.24 11.94 3.64 6.18

Relative error 0.11 0.11 0.31 0.46 0.45 0.10

100

EMMS Mass fraction /% 2.0 21.21 52.35 11.78 3.99 8.71

Relative error 0.21 0.18 0.29 0.47 0.59 0.27

100

Table 4.24 Mass fraction of each lump at the outlet of the first reaction zone and reactor [60] Simulation setting

Species Ph Nh Ah Fh Pm Nm Am Fm G Gas1 Gas2 Steam

inlet Mass fraction 0.1025 0.2461 0.3819 0.1304 0.0204 0.0227 0.0189 0.0092 0 0 0.0256 0.0423

Homogeneous

EMMS

Outlet of 1st zone

Reactor outlet

Outlet of 1st zone

Reactor outlet

Mass fraction 0.0229 0.0378 0.0174 0.0868 0.0266 0.0386 0.0486 0.1402 0.4073 0.0949 0.0274 0.0514

Mass fraction 5.7E-04 4.3E-04 2.4E-05 0.0277 0.0071 0.0079 0.0166 0.1931 0.5399 0.1211 0.0369 0.0486

Mass fraction 0.0219 0.0357 0.0160 0.0857 0.0264 0.0382 0.0482 0.1415 0.4117 0.0957 0.0275 0.0515

Mass fraction 2.4E-04 1.6E-04 7.3E-06 0.0201 0.0046 0.0049 0.0123 0.2005 0.5488 0.1235 0.0419 0.0429

isomerization reactions and the mass transfer limitation, which is influenced by the formation of particle clusters, should be considered.

4.5

Conclusion and Prospects

The TFM combined with the EMMS drag model readily predicted the Gs and axial distribution of solids concentration in laboratory-scale DTFB reactors and reasonably captured the flow regime transition of choking. This approach was subsequently used to investigate the effects of operating parameters and geometrical factors on the

4.5 Conclusion and Prospects

169

hydrodynamics in industrial DTFB reactors. Then, the TFM with EMMS-matrix drag and heat transfer models as well as lumped reaction kinetics were used to simulate a full-scale industrial DTFB reactor for the MIP process. The main conclusions were as follows: 1. The structure of the distributor and opening direction played roles in increasing the solids concentration in the second reaction zone. Among the three distributor shapes investigated (arc, basin, and cone), the basin shape helped to increase the solids concentration of section II to a certain degree; serious leakage of particles was found in the reactor with a cone-shaped distributor. 2. The opening ratio and orifice diameter of the distributor did not affect the mean solids concentration. When the total opening area was close to the diameter of the first reaction zone, a smooth transition between section I and II was detected. The pressure drop, particle leakage, and flow transition between section I and II are primary considerations for distributor optimization. 3. A side exit instead of a traditional constricted top exit caused a large decrease of the solids concentration at the top of section II and serious accumulation of particles near the corner and wall of the exit tube, rendering larger total pressure drop. 4. The diameter of the exit tube did not influence the mean solids concentration of section II, but it did affect the axial profiles. When the diameter of the exit tube was similar to that of section II, a smooth transition between section II and the exit tube was observed. 5. The angle between the secondary feeding tube and reactor only affected the local distribution of solids concentration and flow transition between section I and II. 6. Ug and the supplementary feed rate Gs are two factors that directly influence the solids concentration in the second reaction zone. When the reactor is operated in the choking state, increasing WsII could contribute greatly to the formation of a dense bottom in section II. However, if the operation is in the dense flow regime beyond the choking state, the further increase of WsII does not affect the solids concentration in section II, because section II is already in the saturation state. 7. Flow maps are very helpful to determine the optimal operating conditions and geometrical factors of reactors. In the industrial operation of a CFB, the rapid increase of Ug is usually the only effective way to control or delay the occurrence of choking. Full-loop 3D simulations of MIP reactors considering catalytic cracking reactions in the reactor and coke burning in the regenerator are being performed to aid further scale-up. To some extent, multiscale CFD, i.e., the TFM combined with mesoscale modeling, is beginning to act as a virtual experimental tool to solve industrial problems and help develop new processes.

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26. Igci, Y., Pannala, S., Benyahia, S., Sundaresan, S.: Validation Studies on Filtered Model Equations for Gas-Particle Flows in Risers. Ind. Eng. Chem. Res. 51(4), 2094–2103 (2012) 27. Ozarkar, S.S., Yan, X., Wang, S., Milioli, C.C., Milioli, F.E., Sundaresan, S.: Validation of filtered two-fluid models for gas–particle flows against experimental data from bubbling fluidized bed. Powder Technol. 284, 159–169 (2015) 28. Cloete, S., Johansen, S.T., Amini, S.: Evaluation of a filtered model for the simulation of large scale bubbling and turbulent fluidized beds. Powder Technol. 235, 91–102 (2013) 29. Schneiderbauer, S., Puttinger, S., Pirker, S.: Comparative analysis of subgrid drag modifications for dense gas-particle flows in bubbling fluidized beds. AICHE J. 59(11), 4077–4099 (2013) 30. Li, T., Dietiker, J.-F., Rogers, W., Panday, R., Gopalan, B., Breault, G.: Investigation of CO2 capture using solid sorbents in a fluidized bed reactor: cold flow hydrodynamics. Powder Technol. 301, 1130–1143 (2016) 31. Zhu, L.-T., Xie, L., Xiao, J., Luo, Z.-H.: Filtered model for the cold-model gas–solid flow in a large-scale MTO fluidized bed reactor. Chem. Eng. Sci. 143, 369–383 (2016) 32. Xu, Z., Lai, C., Marcy, P.W., Dietiker, J.-F., Li, T., Sarkar, A., Sun, X.: Predicting the performance uncertainty of a 1-MW pilot-scale carbon capture system after hierarchical laboratory-scale calibration and validation. Powder Technol. 312, 58–66 (2017) 33. Li, J., Kwauk, M.: Exploring complex systems in chemical engineering--the multi-scale methodology. Chem. Eng. Sci. 58(3–6), 521–535 (2003) 34. Ge, W., Li, J.: Physical mapping of fluidization regimes—the EMMS approach. Chem. Eng. Sci. 57(18), 3993–4004 (2002) 35. Jiradilok, V., Gidaspow, D., Damronglerd, S., Koves, W.J., Mostofi, R.: Kinetic theory based CFD simulation of turbulent fluidization of FCC particles in a riser. Chem. Eng. Sci. 61(17), 5544–5559 (2006) 36. Lu, B., Wang, W., Li, J., Wang, X., Gao, S., Lu, W., Xu, Y., Long, J.: Multi-scale CFD simulation of gas-solid flow in MIP reactors with a structure-dependent drag model. Chem. Eng. Sci. 62(18–20), 5487–5494 (2007) 37. Shah, M.T., Utikar, R.P., Tade, M.O., Pareek, V.K.: Hydrodynamics of an FCC riser using energy minimization multiscale drag model. Chem. Eng. J. 168(2), 812–821 (2011) 38. Liu, S.-S., Xiao, W.-D.: Evaluation of the flow behavior in a large-scale polydisperse particle fluidized system by an energy minimization multiscale-eulerian combined model. Ind. Eng. Chem. Res. 53(36), 14113–14126 (2014) 39. Shah, M.T., Utikar, R.P., Pareek, V.K.: CFD study: Effect of pulsating flow on gas–solid hydrodynamics in FCC riser. Particuology. 31, 25–34 (2017) 40. Zhang, D.Z., VanderHeyden, W.B.: The effects of mesoscale structures on the macroscopic momentum equations for two-phase flows. Int. J. Multiphase Flow. 28(5), 805–822 (2002) 41. Matsen, J.M.: Mechanisms of choking and entrainment. Powder Technol. 32, 21–33 (1982) 42. Li, J., Kuipers, J.A.M.: On the origin of heterogeneous structure in dense gas–solid flows. Chem. Eng. Sci. 60(5), 1251–1265 (2005) 43. Lu, B., Wang, W., Li, J.: Eulerian simulation of gas–solid flows with particles of Geldart groups A, B and D using EMMS-based meso-scale model. Chem. Eng. Sci. 66(20), 4624–4635 (2011) 44. Zhang, N., Lu, B., Wang, W., Li, J.: Virtual experimentation through 3D full-loop simulation of a circulating fluidized bed. Particuology. 6(6), 529–539 (2008) 45. Wang, W., Lu, B., Zhang, N., Shi, Z., Li, J.: A review of multiscale CFD for gas-solid CFB modeling. Int. J. Multiphase Flow. 36(2), 109–118 (2010) 46. Ge, W., Wang, W., Yang, N., Li, J., Kwauk, M., Chen, F., Chen, J., Fang, X., Guo, L., He, X., Liu, X., Liu, Y., Lu, B., Wang, J., Wang, J., Wang, L., Wang, X., Xiong, Q., Xu, M., Deng, L., Han, Y., Hou, C., Hua, L., Huang, W., Li, B., Li, C., Li, F., Ren, Y., Xu, J., Zhang, N., Zhang, Y., Zhou, G., Zhou, G.: Meso-scale oriented simulation towards virtual process engineering (VPE)—The EMMS Paradigm. Chem. Eng. Sci. 66(19), 4426–4458 (2011)

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47. Zhou, W., Zhao, C.S., Duan, L.B., Chen, X.P., Liang, C.: Two-dimensional computational fluid dynamics simulation of nitrogen and sulfur oxides emissions in a circulating fluidized bed combustor. Chem. Eng. J. 173(2), 564–573 (2011) 48. Lu, B., Zhang, N., Wang, W., Li, J., Chiu, J.H., Kang, S.G.: 3-D full-loop simulation of an industrial-scale circulating fluidized-bed boiler. AICHE J. 59(4), 1108–1117 (2013) 49. Qiu, X., Wang, L., Yang, N., Li, J.: A simplified two-fluid model coupled with EMMS drag for gas-solid flows. Powder Technol. 314, 299–314 (2017) 50. Wang, X., Gao, S., Xu, Y., Zhang, J.: Gas-solids flow patterns in a novel dual-loop FCC riser. Powder Technol. 152, 90–99 (2005) 51. Bi, H.T., Grace, J.R.: Flow regime diagrams for gas-solid fluidization and upward transport. Int. J. Multiphase Flow. 21(6), 1229–1236 (1995) 52. Grace, J.R.: Reflections on turbulent fluidization and dense suspension upflow. Powder Technol. 113(3), 242–248 (2000) 53. Sun, Z., Zhu, J.: A consolidated flow regime map of upward gas fluidization. AICHE J. 65(9), e16672 (2019) 54. Li, J.: Modeling, in advances in chemical engineering. In: Kwauk, M. (ed.). pp. 147–201. Academic 1994 55. Wang, W., Lu, B., Li, J.H.: Choking and flow regime transitions: simulation by a multi-scale CFD approach. Chem. Eng. Sci. 62(3), 814–819 (2007) 56. Lu B.: EMMS-based meso-scale model and its application in simulating gas-solid two-phase flows. Doctoral Thesis, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, China (2009) 57. Chen, S., Fan, Y., Yan, Z., Wang, W., Liu, X., Lu, C.: CFD optimization of feedstock injection angle in a FCC riser. Chem. Eng. Sci. 153, 58–74 (2016) 58. Chen, S., Fan, Y., Yan, Z., Wang, W., Lu, C.: CFD simulation of gas–solid two-phase flow and mixing in a FCC riser with feedstock injection. Powder Technol. 287, 29–42 (2016) 59. Gunn, D.J.: Transfer of heat or mass to particles in fixed and fluidised beds. Int. J. Heat Mass Transf. 21(4), 467–476 (1978) 60. Lu, B., Cheng, C., Lu, W., Wang, W., Xu, Y.: Numerical simulation of reaction process in MIP riser based on multi-scale model. CIESC Journal (in Chinese). 64(6), 1983–1992 (2013)

Chapter 5

Engineering Aspects and Application of DTFB

Abstract This Chapter introduces how to determine the key design parameters of the diameter-transformed fluidized bed (DFB) reactors, i.e., the diameter expanding ratio and the height of multiple reaction zones, based on the “choking” phenomenon captured by numerical investigation with multiscale CFD simulations. To achieve the steady operation in multiple reaction zones, related ancillary techniques are subsequently developed, such as the distributor installed between the first reaction zone and second reaction zone. Meanwhile, the proprietary catalysts are also being developed. The FCC process with two reaction zones, effective utilization of heavy oil and light-olefin production process are exploited in succession by using the DTFB as the core reactor.

5.1 5.1.1

DTFB Structure and Internals DTFB Structure and Dimension

As discussed in previous Chapters, the diameter ratio (D/d) of the DTFB reactor has a big impact on the heat, mass and momentum transfers. The EMMS-based CFD simulation has been performed to study the relationship between the key structural parameters of the reactor and the gas-solid flow characteristics for determining the DTFB structural parameters and providing a basis for engineering design. With the increase of the diameter ratio (D/d), the gas velocity in the second reaction region is reduced, and the catalyst inventory in the second reaction zone increases accordingly. The weight hourly space velocity (WHSV) of catalytic reaction can be adjusted within a certain range to meet the WHSV requirements of various catalytic reaction processes. However, when the gas velocity in the second reaction zone drops to below 1.5 m/s, the range of "choking" in the second reaction zone is quite wide, as shown in Fig. 5.1. If the gas velocity is reduced further, the catalyst inventory in the second reaction zone may increase sharply, resulting in the difficulty of catalyst circulation flow in the reactor. It can also be found from Fig. 5.1 that the "choking" range is reduced with the increase of gas velocity in the second reaction zone while the catalyst inventory is decreased. Consequently, it will be © Springer Nature Switzerland AG 2020 Y. Xu et al., Diameter-Transformed Fluidized Bed, Particle Technology Series 27, https://doi.org/10.1007/978-3-030-47583-3_5

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Fig. 5.1 The relationship between the diameter ratio of the second reaction zone to the first reaction zone and the “choking” phenomenon range

difficult to regulate the WHSV for the second reaction zone, making it impossible to meet the requirements of various catalytic reaction processes for the WHSV. When the gas velocity in the second reaction zone exceeds 2.8 m/s, the “choking” phenomenon is unlikely to occur, but meanwhile, the catalyst inventory in the second zone is quite low and the corresponding WHSV cannot meet the requirements of different catalytic reaction processes. In conclusion, the gas velocity in the second reaction zone should be controlled between 1.5 to 2.8 m/s, and the diameter ratio between the second reaction zone and the first reaction zone should be in the range of 2.0 to 3.0. With the help of other engineering techniques, the WHSV of the second reaction zone can be adjusted flexibly within a certain range to meet the requirements of various catalytic reaction processes. That also ensures that the high-velocity fluidization in the first reaction region can transit smoothly to the fast fluidization in the second region. The relationship between the height of the second reaction zone and the choking phenomenon is shown in Fig. 5.2. It indicates that with the increase of the height of the second reaction zone, the critical point of "choking" rises and the range for choking occurrence becomes wider. When the height exceeds 10 m, the critical choking point is at the position with a fairly high velocity. It is easier to get choked in the second reaction zone when the reactor height is over 20 m, which may lead to a sharp increase in the catalyst inventory in the second reaction zone and make the catalysts flow unsmoothly within the reactor. But when the height of the second reaction zone is less than 5 m, the choking critical point is at a fairly low position, such that when the gas velocity in the second reaction zone is less than 2.0 m/s, a wider "choking" range could appear. If the height of the second reaction zone is less than 5 m, it will be difficult to store sufficient catalysts. The WHSV of the second

5.1 DTFB Structure and Internals

175

Fig. 5.2 Effect of the height of the second reaction zone on the “choking” phenomenon [1]

reaction zone will be thus maintained at such a high value that it is hard to meet the WHSV requirements of some catalytic reaction processes [1]. In summary, when the diameter ratio of the second reaction zone to the first reaction zone is between 2.0 and 3.0, the reasonable height of the second reaction zone should be at the range of 5 to 10 m. With the help of other measures or techniques, the WHSV of the second reaction zone can be flexibly adjusted within a certain range to meet the requirements of different catalytic reaction processes. Meanwhile, it also ensures a smooth catalyst transition from the high velocity fluidized bed zone to the fast fluidized bed zone. The dimension design of transition section is crucial. The function of the transition section is to guarantee that the velocity of high velocity gas-solid fluids decreases evenly. At the same time, a proprietary distributor is set up at the appropriate position of the transition section to change the direction of gas-solid flow and to transfer the high velocity fluidized bed to the fast fluidized bed smoothly, so as to maintain the smooth operation of gas-solid flow. The outlet velocity in the first reaction zone of DTFB should be determined according to the unit capacity and reaction conversion. Considering the difference of the outlet velocity between the second reaction zone and the first reaction zone should be within a reasonable range, the outlet velocity of the first reaction zone should not be too high. The size of the second reaction zone is designed based on experimental & numerical investigation and production requirement. A too high velocity of the second reaction zone is not favorable to the formation of fast fluidized bed, while it is prone to cause the choking transition at lower velocity. The straight

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tube at the top of the second reaction zone is generally designed based on the inlet velocity of the single-stage cyclone. Overall, the size of the first reaction zone, the second reaction zone and the outlet zone (the third reaction zone) of the DTFB should be determined according to the fluidization theory, the properties of the feed, the design objectives, the device factors, the test data and the existing experience.

5.1.2

Steady-State Fluidization Distributor

5.1.2.1

Development of Distributor

A steady-state fluidization distributor is set up in the transition section between the first reaction zone and the second reaction zone. Its function is to make the high velocity vapor and the catalyst coming from the first reaction zone fluidize uniformly and steadily at the bottom of the second reaction zone, form a stable fluidized bed in this area, and eliminate the jet phenomenon of high velocity fluid as much as possible. At the same time, the catalyst added to the bottom of the second reaction zone should be well distributed above the distributor. Distributor is the key equipment for keeping the steady operation of gas-solid system for the DTFB, which directly determines whether the DTFB can be used as a general reactor for complex gas-solid catalytic reaction. For Type III catalytic cracking unit at the early stage, an air distributor was set at the bottom of dense-phase fluidized bed of regenerator, and the air and catalyst entered the bottom of dense-phase fluidized bed of regenerator through the air distributor. A typical air distributor is an arched distributor, as shown in Fig. 5.3. The operation results of early commercial catalytic cracking units showed that the redistribution of high velocity air and catalyst through the arch distributor can easily cause the following problems [2]: (1) some holes in the arch distributor are seriously abraded; (2) the size of holes becomes non-uniform due to the serious abrasion, resulting in uneven distribution of gas-solid flow. Later, with the development of catalytic cracking technology, the spent catalyst is designed to be directly recycled into dense phase above the distributor. Only air passes through the distributor, and the hole abrasion on the arch distributor is significantly alleviated. It can be found that the gas-catalyst two-phase mixture is not suitable for being distributed through distributor. But for the DTFB reactor, the high velocity vapor and catalysts coming out of the first reaction zone are two-phase mixture stream, and the fluid velocity is 15-20 m/s. Even though only air passes through the small holes in the distributor, the distributor must produce a certain pressure drop to uniformly distribute the gas flow. As a result, the gas flow velocity at the nozzle is higher, and the catalyst particles are accelerated by the jet flow, which generates a big impact on the particles in the "distributor affected zone", resulting in a heavy abrasion of the particles. The wear mechanism of jet on catalyst is shown in Fig. 5.4 [3]. The gas jet is surrounded by the particles in the non-fluidized zone. Some of them are brought into the air

5.1 DTFB Structure and Internals Fig. 5.3 Arch-shaped plate distributor

Fig. 5.4 Particle wear mechanism of jet in fluidized bed [3]

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Fig. 5.5 Abrasion rate curve of jet to particles in fluidized bed [3]

stream to be accelerated and collide with the top of the jet. Then it flows upward into the fluidized zone, while falling particles enter the non-fluidized zone. During the collision, the angular parts of particles are worn out. As the shape of particles gradually becomes round, the wear rate gradually decreases to a constant value, i.e. from the unsteady state to the steady state, as shown in Fig. 5.5 [3]. Based on the problems mentioned above in the actual operation of commercial fluidized bed, the following may happen when the distributor is installed in the transition section between the first reaction zone and the second reaction zone: (1) if the hole opening is applied in the distributor, the serious abrasion of some holes cannot be avoided; (2) because of the serious abrasion of some holes and the different size of abrasive holes, the fluid distribution cannot be uniform; (3) due to the uneven distribution of fluid, more fluid will pass through the large holes, while less fluid will flow through the small holes; (4) after long-time operation, some small holes may be blocked by coke generated from the oil gas condensation; (5) catalyst particles not only collide with the hole wall of distributor, but also are attacked by high velocity gas. As a result, the loss rate of catalyst will increase; (6) the distributor is always impacted by high velocity fluid, and the structure of it may be deformed or even damaged, so that it is difficult to run for a long period of time. The uniform distribution of two-phase mixtures of high velocity vapor and catalyst has not been solved in the field of gas-solid fluidization for many years. More effective technique methods are needed to achieve the steady and uniform flow. In order to reduce the catalyst abrasion brought by high velocity fluid flow, and realize long-time operation and uniform distribution and steady gas-solid two-phase flow in large-scale DTFB, a long-term cooperation between the simulation team of IPE, CAS and the engineering team of SINOPEC was established. Four generations

5.1 DTFB Structure and Internals

179

Fig. 5.6 Arch (Convex) plate distributor

of distributors in different types have been developed and applied to DTFB reactors of different scales. The first consideration in the development of distributor is to decompose the high velocity gas-solid two-phase mixing flow at the outlet of the first reaction zone into several small jets by using the existing arch distributor, as shown in Fig. 5.6. The operation results of the commercial plant show that there is a space with less catalyst inventory between the bottom of the second reaction zone and the distributor which is generated by many small vertical jets. Therefore, it is difficult to form a catalyst bed at the bottom of the second reaction zone. Aiming to solve the problems caused by the arch plate distributor during the operation of the commercial plant, the technical ideas were put forward to change the initial flow direction of the high velocity gas-solid mixing flow at the outlet of the first reaction zone from vertically upward (axial) to radically horizontal, and then to vertically upward. It can reduce the initial axial velocity of the two-phase mixing flow at the bottom of the second reaction zone. The basin-shaped plate distributor was developed based on these ideas, as shown in Fig. 5.7. The operation results of the commercial plant show that the basin-shaped distributor has successfully solved the problems caused by several small vertical jets, however, the distributor

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Fig. 5.7 Basin-shaped plate distributor

deteriorates the distribution uniformity of gas-solid mixing flow. After long-run operation, some holes are easily blocked by oil gas coking. And the distributor is unable to withstand the long-term impact of high velocity fluid with structure destruction. A compromise scheme has been chosen to solve the problems caused by the basin-shaped distributor in the operation of the commercial plant. This scheme can partly change the vertically upward flow direction of the small jets, improve the distribution uniformity of gas-solid mixing flow and withstand the impact of high velocity fluid for a long period. Accordingly, the concave distributor was developed, as shown in the Fig. 5.8. In order to reduce the adverse effect brought by the small vertical jets on catalyst inventory in the second reaction zone, whether with the basin-shaped or concave plate, small jets flow against each other horizontally. Although it consumes the dynamic energy of the catalyst, the collision between catalysts is intensified, which may lead to the increase of catalyst damages and loss. If the gas-solid flow is distributed by the pressure drop generated by the small holes on the distributor, it inevitably aggravates the catalyst collision and may increase the catalyst loss. Therefore, a cylindrical barrel is set up in the transition section between the first

5.1 DTFB Structure and Internals

181

Fig. 5.8 Concave plate distributor

reaction zone and the second reaction zone. The bottom of the cylindrical barrel is connected with the outlet of the first reaction zone. A mushroom-shape head is added on the top of the cylindrical barrel. A large slot is opened at the side of the cylindrical barrel to change the flow direction of the gas-solid mixing flow from vertically upward to horizontal direction Thus, a mushroom-shape head distributor was developed, as shown in Fig. 5.9.

5.1.2.2

Arched (Convex) Plate Distributor

When the DTFB was first applied in commercial scale unit in February 2002, the distributor between the first and second reaction zones was an arch (convex) distributor. Gas-solid mixture flows through equal-diameter holes on the distributor, to form a vertically upward jet and enter into the bottom of the second reaction zone. Considering the abrasion brought by high-velocity vapor and catalyst to the pores of the distributor, the wear-proof tube with ceramic inner core was adopted. In order to evenly distribute the fluid, small holes with equal diameter were evenly distributed on the plate, and the total opening area was equivalent to the outlet area of the first

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Fig. 5.9 Mushroom-shape head distributor

Fig. 5.10 Hole distribution on arch plate distributor

reaction zone. This means that the linear velocity of each hole is equal to that of the outlet of the first reaction zone (Fig. 5.10). It was found in the running of the commercial unit that the gas-solid two-phase flow ejects through the orifices in the distributor at the velocity of 15–20 m/s, a local vapor-catalyst mixture jet is formed at the bottom of the second reaction zone. The capacity of carrying catalyst was found to be strengthened. The local high velocity vapor and catalyst jet beam can attenuate the apparent velocity of the gas-solid flow in the second reaction zone only after it passes through a distance of 3–-4 m. Under the influence of this jet, it is hard to form a suitable catalyst density in the bottom

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183

region of the second reaction zone (about 3–4 m above the distributor). Therefore, the two problems were found after the application of arch (convex) distributor in commercial units: (1) a space with less catalyst inventory is formed in the bottom region of the second reaction zone, and the catalyst inventory in the second reaction zone is difficult to meet the design requirements; (2) with the prolongation of operation time, some small holes in the distributor are blocked by coking, resulting in uneven distribution affecting the long-run operation of the unit.

5.1.2.3

Basin-Shaped Plate Distributor

The basin-shaped plate distributor is composed of an open plate and an open side cylinder. It is equipped with a wear-proof tube with a ceramic inner core. In order to reduce the vertical upward jet flow, the hole area on the side cylinder is much larger than that on the bottom plate, as shown in Fig. 5.11. Through the opening hole on the side cylinder, the flow direction of high velocity gas-solid flow at the outlet of the first reaction zone is converted from being vertical upward to being radially horizontal. The initial axial velocity of the two-phase flow decreases to nearly zero at the bottom of the second reaction zone. At the same time, the jet ejected from the small hole on the side cylinder also consumes part of dynamic energy by mutual impact. Under these two effects, the velocity of gas-solid flow can be rapidly reduced to the required range of apparent velocity in the second reaction zone. It is conducive to the enrichment of catalyst above the distributor and obtain an appropriate catalyst density. The basin-shaped distributor was first applied in a commercial DTFB reactor in September 2003. The running results of the commercial unit show that the basinshaped distributor can effectively increase the catalyst density in the second reaction zone, and solve the problem of regulating and controlling the catalyst inventory in the second reaction zone in order to meet the requirement of WHSV for catalytic reaction. Subsequently, the basin-shaped distributor was applied in other different DTFB reactors.

Fig. 5.11 Small holes on the bottom plate and on the side cylinder of basinshaped distributor

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5 Engineering Aspects and Application of DTFB

However, with the increasing run time of DTFB, the problem of uneven distribution of fluid flow emerges. It is attributed to that more fluid flows through the side cylinder because of large hole area on the side cylinder distributor. On the contrary, the hole area on the bottom plate is relatively small, and less fluid flows through the bottom plate. The blockage of some small holes due to the coking leads to more uneven distribution of fluids and affects the long-run operation of unit. Also, the jets from the side cylinder opposes with each other, aggravating the wear of the catalyst. It is found during shutdown and maintenance that the basin-shaped distributor nearly deforms, which indicates that this structure is unable to withstand long-run impact of high-velocity fluid.

5.1.2.4

Concave Distributor

The concave distributor is a distributor with a circular hole on the concave side. The wear-proof tube with ceramic core is installed. The vertical direction of the hole is between the axial and radial directions of the reactor, and is more inclined to radial. Its structure is shown in Fig. 5.12. The two-phase flow of vapor and catalyst enters the bottom of the second reaction zone through the orifices of the distributor. There is a certain angle between the direction of the jet and the radial direction of the reactor, which changes the flow direction of the two-phase flow. It reduces the initial axial velocity of the two-phase flow at the bottom of the second reaction zone. Meanwhile, the jets ejected from the orifices on the side circle also collides with each other and consumes the dynamic energy. Consequently, the velocity of gas-solid two phase flow can be rapidly reduced to the required superficial velocity in the second reaction zone, which is conducive to the enrichment of catalyst on the distributor and obtain the appropriate catalyst density. The application of concave distributor in commercial-scale DTFB reactor shows that it can effectively increase the catalyst density in the second reaction zone, solve the problem of adjusting, control the catalyst inventory in the second reaction zone and meet the WHSV requirement of catalytic reaction. Meanwhile, concave distributor can make the mixing flow distribute evenly, and its structure can also withstand the impact from the long-run high-velocity fluid. However, the problem of jet

Fig. 5.12 Pore distribution on concave distributor

5.1 DTFB Structure and Internals

185

convection from side circle aggravating catalyst attrition has not been solved properly.

5.1.2.5

Mushroom Head Distributor

The mushroom head distributor is composed of a cylindrical barrel in the conical section of the first and second reaction areas. The bottom of the cylindrical barrel is connected with the outlet of the first reaction area. The top of the cylindrical barrel is added with a mushroom head cover. There are slots around the side of the cylindrical barrel. Most catalysts and vapor enter the conical section through the slots. A small amount of vapor and catalyst passes through the tiny pipe (which has wear-proof ceramic inner core) on the top of the mushroom head to the bottom of the second reaction zone (Fig. 5.13). The gas-solid mixture flow from the slot (groove) on the side of the cylinder barrel enters a larger conical section in space. The flow direction is changed and the linear velocity is obviously reduced. It is mixed with the relatively dense phase catalyst formed at the side wall of the second reaction zone. Meanwhile, it carries a part of catalyst back to the bottom of the second reaction zone and enhances the circulation of the catalyst in the central region. Thus, the density of catalyst at the Fig. 5.13 Slot distribution on the side of cylindrical barrel of mushroom head distributor

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Table 5.1 Performance comparison of various distributors

Distributor type Quality of fluid distribution Ease of obtaining certain catalyst inventory in the second II Catalyst attrition Ease of long-cycle run/large scaling

Arch distributor Good Poor

Basin-shaped distributor Fair Good

Concave distributor Good Good

Mushroom head distributor Fair Good

High Fair

High Poor

High Fair

Low Good

bottom of the second reaction zone is enhanced and the problem of adjusting and controlling catalyst inventory in the second reaction zone is also solved. The requirement of WHSV for catalytic reaction is satisfied as well. Because the slot (groove) area on the side of the cylinder barrel is much larger than that of the orifice area on the distributor, the wear between the catalyst particles and the reactor wall is obviously reduced. Additionally, when the mixture flow enters the conical space, the linear velocity is obviously decreased, and the impact of the gas-solid mixture flow after self-mixing on the catalyst particles in the DTFB is also significantly alleviated. It can be found that the mushroom head distributor can minimize the attrition of catalyst particles, thereby resulting in the reduction of both catalyst fines and catalyst make-up rate. The gas-solid mixture flows out of the slot on the side of the cylinder barrel, avoiding the abrasion and impact of high velocity flow on the equipment. Thus, it ensures the stability of the structure of the mushroom head distributor and meets the performance requirements for the long-run operation of the unit. Mushroom head distributor is more suitable for large-scale DTFB reactor because it needs enough space in the reactor. The tricky problems of distribution and flow of high velocity gas-solid mixtures have been successfully solved by the mushroom head distributor and the catalyst attrition is also mitigated, so that long-run operation of distributor can be guaranteed. It has been applied to a DTFB with a maximum diameter of 5.5 m (the largest catalytic cracking unit of 4.80 Mt/a in China). Mushroom head distributor has become an ideal equipment for the transition from the high-velocity fluidized bed to fast fluidized bed, which provides reliable technical support for DTFB to be a general reactor for complex gas-solid catalytic reaction. The arch (convex) distributor, basin-shaped distributor, concave distributor and mushroom head distributor were applied to the commercial DTFB reactors at different times. Related advantages and disadvantages of these four distributors are listed in Table 5.1.

5.1 DTFB Structure and Internals

5.1.3

187

Pre-Lifting Section of Low Pressure Drop

A pre-lifting section is arranged at the bottom of a riser reactor with equal diameter. The structure is shown in Fig. 5.14. The pre-lifting media is injected from the bottom of the riser to the pre-lifting section, and the catalyst is carried upward. The catalyst can be pre-accelerated and pre-fluidized, which improves the distribution of the catalyst [2]. The function of the pre-lifting stage is to keep the catalyst flow in a stable state. The contact between the stable catalyst and the fresh feedstock droplets injected by the nozzle can lessen the velocity gradient of the catalyst, and maintain a relatively constant ratio of catalyst to oil on the cross section of the riser. The catalyst back-mixing is relieved as well, which is conducive to the uniform contact, rapid mixing and vaporization of the atomized feeding oil with the catalyst. Thermal cracking reaction is maximally limited. In order to make the catalyst flow stable, the height of this type of pre-lifting section is better to be more than 4 m or exceed 6 m, depending on the linear velocity of the media within the pre-lifting section. Because the catalyst density in the pre-lifting section is relatively high, generally at 300-400 kg/m3, the pressure drop increases with the height of the pre-lifting section. The total pressure drop of a DTFB reactor is usually about 10 ~ 20 kPa higher than that of an equal-diameter riser reactor. Generally, technical measures such as increasing the driving force, reducing the length of the pre-lifting section and reducing the pressure drop of the distributor in the second reaction area should be Fig. 5.14 Pre-lifting section of high pressure drop

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5 Engineering Aspects and Application of DTFB

Fig. 5.15 Pre-lifting section of low-pressure drop

considered. It is unavoidable to consume more energy to increase the driving force. However, reducing the pressure drop of the distributor in the second reaction zone may adversely affect the uniform distribution of the two-phase mixture flow. The most effective method is to reduce the length of pre-lifting section. To this end, a low-pressure drop pre-lifting section is developed. The structure of pre-lifting section with low pressure drop can control the height of pre-lifting section between 2 m to 3 m. Within this height, the catalyst flow can reach a stable state and the vertical height can be greatly reduced, which reduces the pressure drop of pre-lifting section. The pressure drop of the DTFB is almost equal to that of an equal-diameter riser. The outlet of the central straight pipe, which is used for the injection of the pre-lifting media, of the low pressure drop pre-lifting section is moved upward, exceeding upper edge of the catalyst cycle pipeline at the bottom of the DTFB (shown in Fig. 5.15). The pre-lifting section of this structure is in favor of the formation of dense-phase fluidized bed in the space below the outlet of the central straight pipe. This can avoid the S-shaped non-uniform distribution of the catalyst after the catalyst enters into the DTFB, and ensure that the catalyst density is at a high level in the initial stage, so that the catalyst flow can reach a stable state within 2-3 m. For the pre-lifting section with low pressure drop, the pre-lifting media flows vertically upward, forming a negative pressure area near the outlet of the central straight pipe. Then the catalyst flows naturally to this area. Within this region, the

5.2 Ancillary Engineering Technology

189

catalyst is carried upward by the flowing material. Below the outlet of the central straight pipe is a dense-phase fluidized bed, which can provide enough catalyst for the negative pressure region near the outlet of the central straight pipe. In this way, the flowing pre-lifting media can continuously carry enough catalyst to flow upward. For the pre-lifting section with high pressure drop, the flowing pre-lifting media is injected from the center between the catalyst circulation and the pipeline at the bottom of the riser. Because the linear velocity of the flowing pre-lifting media is above 1.5 m/s, the catalyst recycled to the bottom of the riser is carried by the flowing pre-lifting media with a relative high linear velocity. It is unable to form a dense-phase fluidized bed here and only an S-shaped uneven distribution is generated, which results in the insufficient catalyst carried by the flowing pre-lifting media and the difficulty of maintaining stability at the initial stage. Only by increasing the height of the pre-lifting section can the catalyst flow reach a stable state. When the linear velocity of the flowing pre-lifting media gets higher, the height of the pre-lift segment will increase more accordingly. Only in this way the catalyst flow can reach a stable state.

5.2

Ancillary Engineering Technology

5.2.1

Double-Cycle Catalyst Transportation Technology

In order to simultaneously adjust the catalyst density and temperature in the second reaction zone of DTFB, control the catalyst inventory and temperature in the second reaction zone, and provide more reasonable process parameters for complex gas-solid catalytic reaction, the most effective method is to supplement the catalyst to the second reaction zone. Supplementary catalysts are classified into three states: (1) high-temperature, regenerated catalyst; (2) low-temperature, regenerated catalyst after cooling; (3) low-temperature, spent catalysts. Three types of double-cycle catalyst transportation techniques have been developed, i.e., technology of draw-off and transportation for spent and hot regenerated catalyst, as shown in Fig. 5.16 (a); technology of draw-off and transportation for two streams of hot regenerated catalyst, as shown in Fig. 5.16 (b); technology of draw-off and transportation for hot and cool regenerated catalysts, as shown in Fig. 5.16 (c).

5.2.1.1

The Temperature of the Second Reaction Zone Lower than the Outlet Temperature of the First Reaction Zone

In view of various types of regenerator and reactor layout, several supporting techniques are proposed to regulate the temperature and catalyst density in the second reaction zone. According to the specific conditions, cool regenerated catalyst or spent catalyst can be added into the second reaction zone. However, for engineering design, supplementing cool regenerated catalyst and supplementing spent

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Fig. 5.16 Three types of catalyst double-cycle transportation technologies

catalyst are two different technical routes, which is difficult to implement these both technical routes simultaneously. Which route should be chosen depends on the technological parameters required by the gas-solid catalytic reaction process. (1) Draw-off and transportation technology of hot and cool regenerated catalyst A stream of high-temperature, regenerated catalyst is sent to the bottom of the DTFB reactor. Another stream of cool regenerated catalyst is drawn from the catalyst cooler, then is lifted and transported to the degassing tank. The cool regenerated catalysts are mixed, degassed and buffered in the degassing tank to form a static pressure head, which are then sent to the bottom of the second reaction zone. The process flow scheme of the draw-off and transportation of two-stream catalyst is illustrated in Fig. 5.17. The pressurized air or dry gas is used as the lifting media. If the main air is used to boost the pressure, a new supercharger system is needed, and the main air should return to the dense phase of the regenerator to be used for burning. If the dry gas is applied, it can be returned to the reaction system without setting up of the supercharger system. However, the gas-phase load of the fractionation and absorptionstabilization system is increased by lifting dry gas. The energy consumption of the compressor goes up as well. Additionally, the gas-liquid phase load of the absorption-stabilization system is also getting higher correspondingly, which means the energy consumption is increased. (2) Draw-off and transportation technology of high-temperature, regenerated catalyst and spent catalyst Based on the different reaction-regeneration layout, the draw-off and transportation technology of the catalyst can be divided into the three specific schemes:

5.2 Ancillary Engineering Technology

191

Fig. 5.17 Draw-off and transportation for hot and cool regenerated catalysts

Scheme 5.1 External DTFB with a rough cyclone separation at its top: A soft connection is set between the outlet of rough cyclone separation and the top cyclone separation. After the catalyst recovered by rough cyclone separation being collected through the diplegs, a part of the spent catalyst in the first way is sent to the bottom of the second reaction zone. An overflow hopper is set in the upper cone section of the stripping section. The catalyst recovered by rough cyclone separation flows into the bottom of the overflow hopper through the diplegs. Steam is injected at the bottom for stripping and fluidization of the catalyst. There is not much space in the overflow hopper so the catalyst inventory is quite limited, which has little effect on the foundation of the reaction-regeneration system. The overflow hopper is equivalent to a buffer hopper, which not only creates opportunities for the circulation of catalyst from the external regeneration method, but also reduces the amount of vapor carried by the spent catalyst and helps to prevent the coking of the settler (Fig. 5.18). This scheme has the least change to the operation mode of the original device. Also, there are not much reconstruction work involved, and little influence on the pressure balance. Thus, Scheme 5.1 is suitable for the external DTFB with a settler of medium height, such as the coaxial parallel device with a relative high settler.

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5 Engineering Aspects and Application of DTFB

Fig. 5.18 Process flow scheme of draw-off and transportation of the catalysts in Scheme 5.1

Scheme 5.2 External DTFB is adopted: The vortex-head rapid separation is applied at its outlet end. After the rapid separation, the vapor enters the settler and the softconnected to the top cyclone. The spent catalyst flows to the pre-stripping section for its pre-stripping, and then part of the spent catalyst enters the bottom of the second reaction zone. Most of the spent catalyst flows to the stripping section, as shown in Fig. 5.19. The advantage of this scheme is that there is no requirement for the height of the original settler, and it is suitable for the retrofit within short shutdown time. Although a sliding valve is added, the operation difficulty is basically unchanged. Scheme 5.3 Built-in DTFB. For the inner reactor with high settler height, the second reaction zone can be arranged below the settler. The full-stripped spent catalyst is introduced from the bottom of stripping section, a part of spent catalyst is transferred to the bottom of the second reaction zone. The operation difficulty is merely increased, and the overall layout of the original device is not affected, as shown in Fig. 5.20.

5.2 Ancillary Engineering Technology

193

Fig. 5.19 Process flow scheme of draw-off and transportation of the catalysts in Scheme 5.2

5.2.1.2

The Temperature of Section II Higher than the Outlet of Section I

Two streams of hot regenerated catalysts are drawn from the dense-phase bed of the regenerator. One stream is delivered to the bottom of the reactor, while the other stream is sent to the degassing tank by lifting. Then two streams of regenerated catalysts are mixed, degassed and buffered in the degassing tank to form a static pressure head, and transported to the bottom of the second reaction zone. The process flow scheme of draw-off and transportation of two-stream catalyst is shown in Fig. 5.21. The pressurized air or dry gas is used as the lifting media. If the pressurized air is used to boost the pressure, a new supercharger system is needed, and the gas after lifting should return to the dense phase of the regenerator to be used for burning. If the dry gas is applied, it can be returned to the riser without setting up of the

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5 Engineering Aspects and Application of DTFB

Fig. 5.20 Process flow scheme of draw-off and transportation of the catalysts in Scheme 5.3

supercharger system. However, the gas-phase load of the fractionation and absorption-stabilization system is increased by lifting dry gas. The energy consumption of the compressor goes up as well. Additionally, the gas-liquid phase load of the absorption-stabilization system is also getting higher, which means the energy consumption is increased.

5.2.2

Cool and Hot Catalyst Pre-Lifting Mixer

The cool and hot catalyst pre-lifting mixer is located at the bottom of the DTFB. The cool catalyst is drawn out from the catalyst cooler and enters from the upper part of the pre-lift mixer. The hot catalyst is drawn from the dense-phase fluidized bed of the regenerator and enters from the middle of the pre-lifting mixer. The fluidized steam is injected from the bottom distributor while the pre-lifting steam from the center straight tube, as shown in Fig. 5.22. In the mixer, the cool catalyst and the hot catalyst are carried upward by the lifting media at the same time. The two streams of catalysts mix evenly in very short time during the mixed fluid flow process, and the temperature of the catalyst is basically the same. The simulation results shows that the heat transfer between particles can be neglected if the concentration of particles is relatively low, and the heat transfer

5.2 Ancillary Engineering Technology

195

Fig. 5.21 Process flow scheme of draw-off and transportation of two-stream hot regenerated catalysts

between gas and solid phase is dominant. At this time, the temperature of catalyst particles at the cool and hot inlets becomes the same in very short time. The temperature of the mixed catalyst particles at the outlet of the pre-lifting mixer is almost the same. If the particle concentration is high, although the heat transfer between particles cannot be neglected, the temperature change of the cool catalyst has little effect on the temperature of the mixed catalyst at the outlet. The cool and hot catalysts have fairly good mixing at the outlet of the pre-lifting mixer, and the temperature is basically identical.

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Fig. 5.22 Structure scheme of pre-lifting mixer

The pre-lifting mixer is used for homogenizing the concentration and temperature of cool and hot catalysts before contacting with the feedstock. For these two streams of catalysts, the temperature of hot regenerated catalyst generally does not change much, but for the cool regenerated catalyst from the catalyst cooler, the temperature change can be achieved by controlling the catalyst circulation rate in a certain range. Therefore, the temperature control of the cool catalyst is very important for the uniform distribution of the concentration and temperature of the final mixture (cool and hot mixtures). Reducing the temperature of the catalyst contacting with feedstock can bring the following benefits: (1) as the catalyst temperature decreases, the catalyst circulation rate increases accordingly so as to enlarge the contact area between feedstock and catalyst. It also facilitates the vaporization of feedstock and reduces the formation of additional coke; (2) reducing the temperature of those catalysts in contact with feedstock can alleviate the thermal cracking reaction. The yield of dry gas and coke can be reduced at the same conversion, so that the target product yield can be enhanced; (3) as the catalyst temperature decreases, the catalyst circulation rate increases accordingly. Under the condition of same coke yield, the carbon content of the catalyst is reduced, which is beneficial to make full use of the catalytic reaction performance, especially in the second reaction zone; (4) as the catalyst temperature decreases, the operating flexibility of the unit increases. For example, the catalyst circulation rate can be adjusted and the preheating temperature of feedstock can be increased. For the DTFB reactor, the reduction in temperature of the catalyst in contact with feedstock has other additional benefits. When the circulation catalyst rate increases, the catalyst inventory in the second reaction zone can be improved correspondingly. As for some catalytic reaction requiring a higher WHSV, the process flow of adding catalyst to the second reaction zone can be eliminated. Moreover, the carbon content

5.2 Ancillary Engineering Technology

197

Fig. 5.23 Process flow scheme of direct cooling of hot catalyst and transported to the bottom of DTFB reactor

of the spent catalyst decreases as the circulation catalyst rate increases. Therefore, the catalyst activity in the second reaction zone is at a high level and the catalytic reaction performance is further improved. In addition to mixing the cool catalyst with the hot catalyst in the pre-lifting mixer for reducing the catalyst temperature, a catalyst cooler can be installed on the regenerated catalyst transportation pipeline to directly cool down the hot regenerated catalyst, as shown in Fig. 5.23. The hot regenerated catalyst can also be mixed with the spent catalyst at lower temperature in the pre-lift mixer to lower the catalyst temperature.

5.2.3

Other Engineering Techniques

Based on the difference of reactant conversion ability, the feedstock which is difficult to be converted are injected into the bottom of the first reaction zone, while the feedstock which is easy to be converted are injected into the bottom of the second reaction zone. Usually, the feedstock which is difficult to be converted refers to the inferior heavy oil and the alkanes, and the feedstock which is easy to be converted refers to olefins, polycyclic cycloalkanes, methanol and so on. In order to reduce the reaction temperature or adjust the product distribution in the second reaction zone, naphtha, light gasoline, heavy gasoline and other fractions or

198

5 Engineering Aspects and Application of DTFB

stripped acid water can be injected back into the second reaction zone. Because of the increase of energy consumption and the load of the fractionator, whether the cooling media is injected into the second reaction zone should be determined according to the specific conditions of the unit. Heat exchanger is installed in the second reaction zone for adjusting the temperature of the second reaction zone. It can remove the excess heat generated in the second reaction zone and also provide the required heat to the second reaction zone.

5.3 5.3.1

Proprietary Catalyst Catalytic Active Component

It has been discussed in Chap. 1 that to achieve the optimal conversion and selectivity of catalytic reaction, it requires the use of appropriate reactors. DTFB reactor has been successfully applied to catalytic cracking process (see Chap. 6), heavy oil processing (see Chap. 7) and petroleum and coal chemical processing (see Chap. 8). Different types of proprietary catalysts have been developed successively, the catalytic active components cover Y-zeolite, ZSM-5 zeolite and SAPO-34 zeolite. The proportion of various active components on different types of proprietary catalysts is shown in Fig. 5.24. It can be found that in the field of catalytic cracking and heavy oil processing, the active components on catalysts are mainly Y-zeolite with supplementary of ZSM-5 zeolite; in the field of petrochemical technology, the active components on catalysts are just the opposite—mainly ZSM-5 zeolite with supplementary of Y zeolite.

5.3.2

Coke Migration on Catalyst

Because the catalyst in the second reaction zone comes from the first reaction zone, its catalytic performance is greatly affected by the coke deposition from the reactions in Section I. However, the influence of carbon content on catalytic performance is not only related to the content of coke, but also to the location of coke deposition.

Fig. 5.24 Proportion of active components on proprietary catalysts and corresponding catalytic reaction processes

5.3 Proprietary Catalyst

199

Table 5.2 Physicochemical properties and acidity of proprietary catalyst and comparative catalyst

Catalyst Proprietary catalyst Comparative catalyst

Bulk density/ (g/mL) 0.75

Pore volume/ (mL/g) 0.75

Total acidity/ (mmol/g) 28.4

Acidity/ (μmol/g) 250  C 450  C L B L B 14.8 13.7 11.3 10.2

0.70

0.33

26.9

13.9

12.1

10.1

9.1

Table 5.3 The activities of proprietary catalyst, comparative catalyst and the carbonized catalyst

Catalyst Proprietary catalyst Comparative catalyst

Micro-reactivity/% Carbonized Regenerated catalyst catalyst 46 66

Carbon content/% Carbonized Regenerated catalyst catalyst 1.57 25.0 nm 41.44 39.37

are listed in Table 5.15. It shows that compared to the results gained from carbonfree catalyst, the catalytic conversion of high olefin gasoline with carbon-attached catalysts can be characterized as high liquid yield, low dry gas and coke yield, and high olefin content in gasoline products. It can be concluded that although the conversion of high olefin gasoline with carbon-free catalyst is much higher (15%), the selectivity (dry gas + coke reached 23.93%) is still quite poor. Meanwhile, the olefins in gasoline are converted to more isoalkanes but less aromatics. Since the octane number of isoalkanes is lower than that of aromatics, and the olefins of gasoline are more converted into isoalkane by the action of zeolite catalyst, as listed in Table 5.14, it results in the significant reduction of MON octane number. The olefins in gasoline are converted into isoalkanes and aromatics by the catalyst with carbon deposit in the second reaction zone, which leads to an increase in MON octane number. Detailed analysis of the reaction mechanism is shown in Sect. 5.1, Chap. 6. Why is the selectivity of carbonized catalyst better than that without carbon? From Table 5.5, it can be found that catalyst with carbon has a lower content of strong acid B and catalyst without carbon has higher strong acid B content, but the difference of total acid content between both catalysts is not obvious. Additionally, the pore size of carbonized catalyst is 8.0 – 25.0 nm. The ratio of carbonized catalyst is higher than that of catalyst without carbon (See Table 5.16). Based on Table 5.16, it is concluded that when the molecules react on the carbonized catalyst with larger pore size, especially in the supercage, the reactants and products can enter and exit the zeolite freely, avoiding "excessive cracking". Moreover, the content of strong acid B is relatively low, which weakens the adsorption towards aromatic. However, the total acid content is not so low, which is beneficial to the bimolecular cracking

5.5 Application Analysis of DTFB Reactor

217

reaction or selective hydrogen transfer reaction. Better product selectivity and product properties can be obtained.

5.5.2

Comparison with Equal-Diameter Fluidized Bed Reactor

One 1.5 Mt/a catalytic cracking unit of a Chinese petrochemical company was revamped from a single equal-diameter riser to a dual riser reactor in 2004. The product distribution and energy consumption before and after the revamping are listed in Table 5.17. The operation results show that the product distribution and energy consumption of the dual riser reactor are worse than that of the single riser reactor. In 2010, the reactor has been improved into a DTFB reactor. The product distribution and energy consumption of the unit are listed in Table 5.17 [7]. Table 5.17 shows that, compared with the equal-diameter dual riser reactor, the energy consumption of DTFB reactor decreases. The processing feedstock quantity increases by 4.99%, the low-valued dry gas and coke yield decreases by 46.36% and 12.74%, respectively. The high-value LPG and gasoline yield increases by 25.40% and 30.03%, respectively, and the ratio of LCO to gasoline decreases by 51.12%. The energy consumption is reduced by 18.91%. As a result, the annual economic benefit of this unit is increased by 90 million Chinese yuan [8]. Table 5.17 also shows that compared with the single equal-diameter riser reactor, the DTFB reactor has a strong competitive advantage in terms of minimizing energy consumption, improving processing amount of feedstock, reducing the yields of low-value dry gas and coke, enhancing the yields of high-value LPG and gasoline, and lessening the ratio of LCO to gasoline. Table 5.17 Product distribution and energy consumption of a petrochemical catalytic cracking unit before and after revamping Item Capacity, t/d Product distribution/% Dry gas LPG Gasoline LCO Slurry Coke Loss Total Liquid yield/% Ratio of LCO to gasoline Energy consumption /(kg equivalent oil/t)

Single riser 4812.3

Dual riser 4761.4

DTFB 4999.0

4.78 14.76 43.87 23.92 4.70 7.62 0.35 100.00 82.55 0.55 63.37

5.50 16.10 38.30 25.30 6.50 7.93 0.37 100.00 79.70 0.66 69.60

2.95 20.19 49.80 16.08 3.65 6.92 0.41 100.00 86.07 0.32 56.44

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5 Engineering Aspects and Application of DTFB

Table 5.18 Product distribution and energy consumption before and after revamping of catalytic cracking unit in another Petrochemical Company Item Processing capacity,t/d Product distribution/% Dry gas LPG Gasoline Light circulating oil Slurry Coke Loss Total Ratio of LCO to gasoline Total liquid yield /% Total energy consumption /(kJ/t)

Equal-diameter dual riser 3119

DTFB 3721

△ 19.30

3.53 12.84 40.79 24.67 9.44 8.25 0.48 100.00 0.60 78.30 2526.52

3.43 17.68 43.15 20.70 6.60 8.03 0.41 100.00 0.48 81.53 2305.32

2.83 37.69 5.79 16.09 30.08 2.67 0.00 20.00 4.13 8.76

The 1.2 Mt/a catalytic cracking unit of another Petrochemical Company in China was put into operation in 1998. A single equal-diameter riser reactor was adopted. In 2004, a single equal-diameter riser reactor was replaced by a dual riser reactor. After the revamping, its operation results are still not as good as that of single riser reactor even through many-year operation. In 2011, the dual riser reactor was forced to be transformed into the DTFB reactor. The unit has been in operation since the revamping. The product distribution and energy consumption of the unit before and after the revamping are listed in Table 5.18 [9]. From Table 5.18, it can be found that compared with dual riser reactor, when the DTFB reactor is applied, the energy consumption of the unit is reduced by 8.76%, the processing amount of feedstock is increased by 19.30%, the yields of low-value dry gas and coke are reduced by 2.83% and 2.67%, and the yields of high-value LPG and gasoline are increased by 37.69% and 5.79%, respectively. And the ratio of LCO to gasoline is decreased by 20.00%, showing a strong competitive advantage of the DTFB reactor in many technical indicators.

5.5.3

Comparison with Equal-Diameter Riser Plus Dense-Phase Fluidized Bed Reactor

Light olefins, such as ethylene, propylene and butene, are the most basic organic chemical raw materials. Based on the catalytic cracking technology platform, the research and development of a technical route for direct production of propylene from heavy oil by deep catalytic cracking are popular in major oil companies and research institutions. In the late 1980s, SINOPEC RIPP developed a catalytic cracking process which uses heavy oil as feedstock for propylene production

5.5 Application Analysis of DTFB Reactor

219

(known as Deep Catalytic Cracking, DCC). For paraffin-based Daqing VGO, the propylene yield of DCC process is as high as 22.9%. Even though the propylene yield of intermediate-based VGO is slightly lower, the propylene yield is still over 17%. However, when maximizing the production of propylene and aromatics, the gasoline yield decreases with the increase of LPG yield, and the aromatics and benzene content in gasoline increases substantially. Additionally, the most unacceptable fact is that the dry gas yield increases nearly by five times, resulting in the waste of heavy oil resources. The reason is that DCC process uses an equal-diameter riser plus a dense-phase fluidized bed reactor which could retain vapor in the settler for a long time. If a DTFB reactor is used which connects vapor outlet directly with the cyclone separator, the residence time of vapor in the settler would be greatly reduced and the thermal cracking reaction could be alleviated, thus the dry gas yield would be further minimized. Please refer to Chap. 8 for detailed discussion. Moderate Catalytic Cracking Process (MCC) applies DTFB as the reactor, which can realize the cracking reaction of light olefins under mild conditions without excessive cracking. This process can avoid a significant increase in dry gas yield, especially in hydrogen and methane yields. The pilot plant test results of MCC and DCC processes are listed in Table 5.19 [6]. Table 5.19 Pilot plant test results of MCC and DCC processes Process types Test number Crude oil Reactor Operating conditions Reaction temperature/ C Catalyst to oil ratio Mass balance/% Dry gas LPG Propane Propylene Butane Butene Gasoline LCO DO Coke Total Conversion /% Total liquid yeild /% Propylene /% Propylene/propane Butene/butane LPG/dry gas

MCC B40-12-MC Daqing VGO + 30% VR DTFB

DCC 892-6 Daqing VGO Riser and fluidized bed

Base Base

+50 +4

3.86 37.93 1.76 17.81 3.16 15.20 39.04 9.58 3.48 6.11 100.0 90.41 86.55 46.95 10.12 4.81 9.83

11.97 42.56 3.34 19.07 4.22 15.93 28.33 9.94 – 5.35 98.15 90.06 80.83 44.81 5.71 3.77 3.55

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5 Engineering Aspects and Application of DTFB

It can be found from Table 5.19 that compared with DCC process using an equaldiameter riser plus a dense-phase fluidized bed reactor, the MCC process which applies the DTFB reactor can significantly suppress thermal cracking reaction. The yield of dry gas can also be significantly reduced. The product distribution is improved, and the total liquid yield increases by more than 5%, while the highvalue propylene yield is basically the same. Thus, the precious heavy oil resources are saved and the oil resources are utilized efficiently, and the economic benefit of the unit is greatly boosted. Based on more than 90 literatures published by the Chinese catalytic cracking experts, Sun et al. [10] summarized 174 sets of industrial production data obtained from more than 40 catalytic cracking units with DTFB reactors, and statistical data analysis was made as well. Compared with the equal-diameter riser, the gasoline yield increases by 2.41% while the LCO yield decreases by 3.67% after application of the DTFB reactor. Also, LPG increases by 1.72%, the olefins in gasoline decreases by 12.1 units, RON octane number increases by 0.2 unit and MON increases by 0.7 unit .

5.6 5.6.1

Commercial Application and Economic Analysis of DTFB Reactor Commercial Application

In the past 20 years, the technology of DTFB reactor has been continuously developed. Some tricky problems in terms of stable operation of reactor, reasonable distribution of gas-solid mixture flow, catalyst wear and long-term operation of distributor, etc. have been properly solved. The DTFB reactor can be used as a dedicated reactor for some complex gas-solid catalytic reactions. A number of original and innovative catalytic reaction technologies have been developed as well. In the field of catalytic cracking technology, catalytic cracking processes for maximizing iso-paraffin (MIP), catalytic cracking processes for producing clean gasoline and propylene (CGP), catalytic cracking processes for producing high octane number gasoline (LTG), catalytic cracking processes for reducing dry gas and coke (DCR) have been developed, and catalytic cracking processes for producing ultra-low olefin gasoline and fine catalytic cracking processes are being developed. The features of these processes, and their reaction chemistry and industrial application are covered in Chap. 6. A brief introduction about the application of these technologies is described below. Based on the technology platform of DTFB reactor, combined with the development of proprietary catalyst and the design of operating parameters, MIP or CGP process has achieved the improvement of product yield and product structure of catalytic cracking unit. Also, the olefin content of gasoline produced by MIP or CGP process has been greatly reduced and the range of reduction can be controlled to

5.6 Commercial Application and Economic Analysis of DTFB Reactor

221

meet the requirements of gasoline quality of their respective enterprises. During the past 20 years, most of FCC units in China have replaced their riser reactors with the DTFB reactors.

5.6.2

Economic Analysis

Taking the original FCC unit as the basis, the technical and economic benefits of CGP process (the CGP unit of ZH Refinery and Chemical Company) adopting DTFB as the reactor is analyzed. The feedstock composition, product distribution, gasoline properties and energy consumption data of CGP unit are obtained from the run test data gathered on July 7, 2017. Feedstock composition, product distribution, gasoline properties and unit energy consumption data of FCC unit applies the data gathered on September 22, 2003. Feedstock and product prices are the market prices of 2004, provided by ZH Refinery and Chemical Company Finance Department. Dry gas is the internal fuel of the company, whose price is calculated based on heavy oil. Coke is also the internal fuel of the unit, and the price is calculated based on heavy oil. According to the composition of feedstock, product distribution, gasoline properties, energy consumption and its prices, the value-added per ton of feed oil processed by CGP can be calculated. The specific data of economic return are shown in Table 5.20. From Table 5.20, the following conclusions could be drawn: (1) The value added of feedstock is 17.81 yuan/t. The residue blending ratio of CGP unit is basically the same as that of the original FCC unit, while the price of VGO is different from that of residue oil. According to the residue blending ratio data of CGP and FCC units after calibration, the value added of feedstock per ton processed by CGP process can be calculated to be 17.81 yuan/t. (2) The value added of the product is 134.01 yuan/t. CGP unit can greatly increase the yield of LPG, especially propylene, which is a high value-added product. And the dry gas yield and slurry yield of the CGP unit are reduced. As a result, the yield of other high value-added products goes up accordingly, resulting in a significant increase in the value of the products. Based on the calibrated product distribution and their price of CGP and FCC units, the value added per ton of the feedstock processed by CGP process is 134.01 yuan/t. (3) The increment of energy consumption of the unit is 2.03 yuan/t. The energy consumption of CGP unit is reduced by 1.43 kg EO/t. When the price of fuel oil is calculated based on heavy oil, the increment of energy consumption per ton of crude oil is 2.03 yuan/t. (4) The value-added of gasoline is 44.26 yuan/t.

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5 Engineering Aspects and Application of DTFB

Table 5.20 Comparison of economic return of CGP Process and FCC process per ton Items Run test date Wax oil Residue Subtotal Dry gas LPG Gasoline LCO Slurry Coke Propylene Subtotal Total Catalyst Catalyst price/(Yuan/t) Energy consumption Energy price /(Yuan/t) Gasoline quality Revenue of octane number /(Yuan/t) Revenue per ton /(Yuan/ t)

Price/ (Yuan/t)

CGP/% 2005-01-07

Value added/ (Yuan/t)

2154 1450

0.6747 0.3253

FCC/% 200309-22 0.70 0.30

1422.84 3101.81 2689.49 2692.78 1422.84 1422.84 5989.21

2.58 15.47 39.52 22.23 4.98 7.11 7.63

3.46 11.03 44.42 23.16 5.29 7.06 5.10

24333.543

Change of unit catalyst consumption

0.062

1.51

1422.84

Changes in energy consumption /(kgEO/t)

1.43

2.03

70.0

Change of octane number

1.6

44.26

54.50 36.69 17.81 12.52 137.72 131.79 25.04 4.41 0.71 151.53 116.20 134.01

181.81

When applying CGP process, the quality of gasoline has been obviously improved, the sulfur content and the olefin content of gasoline has decreased, and the induction period has increased. The resulting value increment has not been calculated temporarily. The decrease of sulfur content of gasoline is beneficial to the production of low sulfur and high grade gasoline. The increase of induction period can partly reduce the addition of antioxidants. The increment of gasoline quality mainly concentrates on the price increasing of high RON octane value of gasoline after the unit modification. The gasoline RON number was increased by 1.60 units. The value added by gasoline octane number increase is 44.26 yuan per ton of feedstock since the value of per octane number unit is 70.00 yuan. (5) The increment of catalyst consumption is 1.51 yuan/t. Only taking the catalyst consumption into account as the consumption of chemical raw materials used in the unit. The consumption of other chemical raw materials is basically the same before and after revampment which is temporarily not included. The consumption of catalyst in CGP unit is reduced by 0.064 kg/t. The price of

5.6 Commercial Application and Economic Analysis of DTFB Reactor

223

catalyst is calculated at 24333.543 yuan per ton. Then, the increment of catalyst consumption per ton of feed oil is 1.51 yuan/t. Based on the mentioned increment of feed oil, product, energy consumption, gasoline quality and catalyst consumption, the annual economic return of CGP unit is 181.81 yuan/t. The total annual economic benefit of a 1.4 Mt/a CGP unit of ZH Refinery and Chemical Company is 25.53 million yuan. By December 2018, 55 commercial catalytic cracking units have adopted DTFB reactor with a processing capacity of 93.82 million t/a. Based on the annual economic benefit of 154.53 million yuan produced by the 14Mt/a CPG unit of ZH Refinery and Chemical Company, its economic benefit was about 16.8 billion yuan/ a, and the cumulative economic benefit from 2002–2008 was about 134.4 billion yuan. Thus, the catalytic cracking process with DTFB reactor can not only produce low olefin gasoline, reduce environmental pollution, but also produce enormous economic benefits due to the increase of high value-added products. The total processing capacity of DCR technology is 17.3 million ton/year, and the economic benefit is 770 million yuan/year. In addition, the total processing capacity of LTG process is 8.05 ton/year whose economic benefit is 3.1 billion yuan/a. The economic return of the subsequent desulfurization unit is 6.15 billion yuan/a due to less reduction of octane number. According to production data, when producing clean gasoline with sulfur content less than 10 μg/g, the octane number loss of MIP gasoline is 1.48 units less than that of regular FCC gasoline on average. Based on the octane number (RON) of 110 yuan /t per unit, the average MIP gasoline yield is about 41.7%, while that of clean gasoline is about 37.896 Mt/a. The economic benefits are about 6.15 billion yuan/ a. The output of proprietary catalyst needed for the process matching with variable diameter fluidized bed is about 70 000 t/a, and the annual sales increment is about 210 million yuan.

5.6.3

Technology Licensing

DTFB and its corresponding technology patent have been licensed to SINOPEC, PetroChina, CNOOC, Sinochem Corp., Yanchang Group, China Chemical and other private refineries. Since its industrialization in 2002, several refineries have used DTFB reactor and its corresponding technology through patent licensing every year. Till the end of December 2018, the number and scale of licensed devices are listed in Table 5.21. It can be seen that from 2002 to 2018, the DTFB reactor and its corresponding process patents are licensed to 70 units, whose processing capacity is about 123 million t/a and income exceeds 626 million yuan. The annual economic return of the proprietary catalysts needed for the matching process of DTFB reactor were considerable.

224

5 Engineering Aspects and Application of DTFB

Table 5.21 Number and scale of permitted devices for DTFB and corresponding technologies per year Year 2002 2003 2004 2005 2006 2007 2008 2009 2010

5.7 5.7.1

Number of licensed units/ sets 1 2 5 6 4 4 2 6 5

Scale/ (Mt/a) 1.40 1.84 6.00 8.30 6.50 7.00 4.30 6.65 6.90

Year 2011 2012 2013 2014 2015 2016 2017 2018 Total

Number of licensed units/ sets 4 5 2 4 3 4 5 8 70

Scale/ (Mt/a) 5.70 13.50 3.20 10.10 5.00 7.80 13.20 15.33 122.72

Social Effects Progress in Petroleum Refining

In 1936, the first fixed-bed catalytic cracking unit was put into operation, which marked the beginning of the catalytic cracking process entering the ‘stage’ of oil refining technology. Then, it was followed by the brilliant new ideas and designs, like moving bed, fluidized bed, equal-diameter riser and DTFB reactor [11, 12]. The evolution of catalytic cracking reactors shown in Fig. 5.31. The invention of DTFB reactor originates from the research of a new catalytic cracking process. The DTFB reactor which has many different reaction zones, can optimize the conversion and selectivity of some complex gas-solid catalytic reactions at the same time, and dissolve the inherent defect of the contradiction between conversion and selectivity exists in a single fluidized bed reactor with complex gas-solid catalytic reactions. It provides a more reliable catalytic reaction engineering for complex gas-solid catalytic reactions, which promotes the further development of gas-solid fluidization science and technology research. In 2016, the State Intellectual Property Office (SIPO) and the World Intellectual Property Organization (WIPO) awarded the Chinese Patent Gold Award for ‘A Riser (DTFB) Reactor for Fluidized Catalytic Conversion (ZL99105903.4, Mother patent of reactor)’. In 2003, SIPO has awarded the ‘A Catalytic Conversion Method for the Production of Iso-butane and Iso-butane Rich Gasoline (ZL99105904.2, MIP processing patent)’ a Chinese Excellence Patent Award. It is expected to develop more efficient petroleum refining, petrochemical and other chemical technologies on the technology platform of DTFB reactor, which can promote the construction and development of the disciplines of petroleum refining and chemical engineering.

5.7 Social Effects

5.7.2

225

Efficient on Utilization of Heavy Petroleum and Diversifying Chemical RAW Materials Sources

High selectivity catalytic cracking with DTFB reactor and hydrogenation integrated technology (IHCC) is the first heavy oil processing route in the world. It greatly improves the utilization rate of petroleum resources. Commercial test results show that IHCC process can increase the yield of liquid products by more than 10%. This means that once IHCC technology is widely used, the yield of liquid product will be greatly increased. According to calculation, when Chinese refining capacity reaches 600 million ton/year, the amount of heavy oil is about 360 million tons. If all the heavy oils processed by IHCC, the output of liquid product can increase by about 36 million ton/year, which is close to the amount of crude oil produced by Daqing Oil field every year. IHCC process is in line with the Chinese conditions which gasoline consumption is the main factor, and has great competitive advantages. The comparison with other heavy oil processing routes is listed in Table 5.22. DCR process can reduce the yield of dry gas and coke, and also increase the utilization rate of petroleum resources by a small margin. LTG technology can partly reduce the yield of diesel oil, while increasing the yield of gasoline. The highselective catalytic cracking technology can even not produce diesel oil, so as to optimize the product structure. MCC process can produce more low-carbon olefins, while greatly reducing the yield of dry gas, thereby improving the utilization rate of petroleum resources. The process of producing olefins from coal to methanol instead of petroleum can reduce the dependence of petroleum resources and achieve sustainable development, which is of great significance [13]. For the same liquid product yield, the coke yield of MIP process decreases, and CO2 emission is reduced accordingly. The coke yield of inferior heavy oil processed by IHCC technology decreases significantly, so that CO2 emission gets reduced more, which achieves the low carbon, green and sustainable development.

Table 5.22 IHCC process compared with other heavy oil processing routes Item Crude oil Main products Liquid product yield Technical maturity

Fixed bed + FCC Conventional heavy oil Gasoline Low

Boiling bed Inferior heavy oil Diesel oil Middle

Slurry bed Inferior heavy oil Diesel oil Middle

Fixed bed + IHCC Inferior heavy oil Gasoline High

Mature

More mature

Developing

More mature

226

5.7.3

5 Engineering Aspects and Application of DTFB

Development of Key Technologies for Motor Gasoline Production

After nearly 20 years research, several technologies for reducing olefin and sulfur content in FCC gasoline have been developed. These technologies have been repeatedly competed and eliminated in the market, forming two basic technical routes for motor gasoline production in China: one is the combination of MIP and S Zorb/gasoline hydrodesulfurization; the other is the combination of FCC and gasoline hydrodesulfurization/light gasoline etherification, in which the combination process of MIP and S Zorb has become the most competitive technical route for motor gasoline production in China.

5.7.3.1

Euro III to Euro V of Motor Gasoline

The aim of developing MIP process is to reduce the olefin content in gasoline to less than 35%. Then, the quantitative relationship of the influence of process parameters on olefin content in gasoline is determined by analyzing the data gathered in several industrial units with MIP process. The application of proprietary catalysts further make it possible to reduce the olefin content in the gasoline produced from MIP process. The olefin content can be controlled more precisely according to the requirement of enterprises to produce motor gasoline, so as to maximize the economic benefit. When olefin content of MIP gasoline is greatly reduced, RON increases (except for several units), and MON goes up significantly as well. RON and MON of MIP gasoline increase by nearly two units, especially in the case of producing more propylene and gasoline. The sulfur transfer coefficient STC (the ratio of sulfur in gasoline to sulfur in raw materials) decreases by about 30%-50%. The ratio of benzene content to aromatic content in gasoline (benzene-aromatics ratio, RBA) is quite low. The reason for the obvious improvement of gasoline properties is that the composition of gasoline has changed. The composition of gasoline produced by MIP process and FCC process is listed in Table 5.23 [14]. From Table 5.23, it can be seen that compared with FCC gasoline composition, MIP process gasoline has high iso-alkane content, low olefin content, high aromatic content, low benzene content, low benzene-aromatic ratio, n-alkane content and cycloalkane content are comparable to FCC process gasoline, and the ratio between iso-alkane and n-alkane are relatively high. Additionally, considering the distribution of iso-alkanes, the content of isopentane and iso-hexane in MIP gasoline is higher, the content of iso-heptane and its mono-branched alkanes is lower, and the content of polymethyl-iso-alkanes is also lower. Considering olefin distribution, the content of straight-chain olefins in MIP gasoline is low, especially the content of straight-chain 1-olefins. Although the content of branched-chain olefins is relatively low, the content of branched-chain olefins and straight-chain olefins is higher, and the ratio of branched-chain 2-olefins and branched-chain 1-olefins is higher.

5.7 Social Effects

227

Table 5.23 Properties and composition of gasoline produced by MIP process and FCC process Process types Quality composition/% N-alkanes Iso-alkanes Olefin Naphthenes Aromatic Benzene RON MON Iso-meric/n-alkanes Benzene/aromatic (RBA)

MIP

FCC

4.93 31.18 25.07 7.31 29.61 0.88 92.9 82.0 6.32 2.97

4.74 23.91 40.78 7.31 22.24 0.78 93.0 81.5 5.04 3.51

Process types Olefin composition/% Straight-chain 1-olefins Straight-chain 2-olefins Straight-chain 3+-olefins Branched 1-olefins Branched 2-olefins Multi-branched olefins Cyclic olefins Diene+Triene+acetylene Branch/straight-chain ratio Branch-2/Branch-1 ratio

MIP 25.07 1.16 6.10 1.04 6.05 7.30 0.09 2.85 0.47 1.62 1.20

FCC 40.78 1.93 8.68 2.94 10.30 9.70 0.30 5.89 1.03 1.48 0.94

Table 5.24 Desulfurization rate and RON Loss of MIP and FCC gasoline desulfurization Items Gasoline type FCC Gasoline1 FCC Gasoline2 FCC Gasoline3 MIP Gasoline1 MIP Gasoline2 MIP Gasoline3 MIP Gasoline4

Sulfur/(mg/kg) feedstock Products 942 43

Olefin/% feedstock 38.8

Products 30.7

Desulfurization/ % 95.43

RON loss 1.8

766

36

25.5

22.3

95.30

1.0

770

38

37.0

27.4

95.06

1.6

627

32

28.8

24.7

94.90

0.8

532

44

32.7

28.3

91.73

0.6

14.1

12.8

98.30

0.2

31.0

25.2

95.03

0.7

364 664

6.2 33

The octane number of straight-chain olefin-1 is low and also easy to be saturated by hydrogenation. After saturation, the octane number of n-alkanes is much lower, while the octane number of branched-chain olefins is higher and difficult to be saturated by hydrogenation. Even if it is hydrogen treated, the loss of octane number is relatively less. Because MIP gasoline contains less straight-chain olefin-1 and more iso-olefins, under the same hydrogenation condition, the olefin saturation rate is low and less octane number is lost. Or in other words, at the same desulfurization rate, the olefin saturation rate is low and the octane number loss is less significant. The desulfurization rate and RON loss of FCC and MIP gasoline are listed in Table 5.24. It can be seen that MIP process not only reduces the olefin content of gasoline, increases the octane number of gasoline and reduces the sulfur in gasoline, but also provides a more ideal feeding gasoline for desulfurization process. When MIP

228

5 Engineering Aspects and Application of DTFB

process gasoline was used as the feedstock for the ultra-deep gasoline desulfurization process, the octane loss is much lower than using FCC process gasoline. Thus, it ensures the production of high-grade motor gasoline, which is impossible to achieve by FCC process. Because of the good synergy between MIP process and gasoline desulfurization process, the combination of MIP and RSDS/S Zorb process is the main technical way to upgrade the quality of motor gasoline in China, which also has good economic benefits. It also provides a reliable basis for subsequent upgrade for motor gasoline. In fact, all the major refiners of SINOPEC adopt combination MIP and S Zorb process to produce Euro V motor gasoline.

5.7.3.2

Motor Gasoline and Motor Ethanol Gasoline of Euro VI

With the upcoming implementation of Euro VI standards for motor gasoline and ethanol gasoline, the olefin content is required to be less than 15%. And the addition of oxygenates is not allowed in motor ethanol gasoline, which means that the olefin content of the gasoline distillate produced by the MIP process is also too low. Meanwhile, the olefin etherified oxides in MTBE and light gasoline cannot be used in the motor gasoline. It means that the motor gasoline production technology of China is once again facing great challenges. In order to meet the requirements of Euro VI standard for motor gasoline and ethanol gasoline, it is necessary to make a thorough analysis of the two basic technical routes of motor gasoline production in China. For the production routes with the combined process of FCC and gasoline hydrodesulfurization/etherification of light gasoline, the etherification process of light gasoline is about to be eliminated because the oxide generated by the etherification of olefin in light gasoline is not allowed to be used as the component of motor gasoline. Therefore, this technical route cannot provide proper motor gasoline components in a short period of time. It is necessary to develop gasoline olefin post-processing technology. Even if the gasoline olefin post-processing technology is successfully developed, whether it has market competitiveness still needs to be tested. For the basic technical route of gasoline production by the combined process of MIP and S Zorb, MIP process needs further development because olefin content of gasoline is higher than 20%.The olefin content of gasoline to needs to be reduced less than 20%, or even less than 10%. On the technology platform of DTFB reactor, the high selective hydrogen transfer reaction of olefins in gasoline was strengthened in the second reaction zone from the aspects of process flow, process parameters and catalyst performance. It is to further reduce the olefin content in gasoline, generate more isoalkanes and aromatics. Meanwhile, the corresponding high efficiency regeneration technology is developed to burn the increased coke due to the reduction of olefin content in gasoline. A new generation of FCC process, named FCC for producing gasoline with Ultra Low Olefins (ULO), for producing gasoline with high octane number and ultra-low olefin content was developed, which can reduce the volume fraction of olefin in gasoline to less than 10% [15].

5.7 Social Effects

229

Fig. 5.32 The process flow scheme of SDS process

Although S Zorb process can deeply desulfurize the gasoline, it will still cause the loss of octane number in the process of deep desulfurization, generally loss about 1 unit. To this end, a gasoline flexible adsorption desulfurization process (SDS) has been developed. A two-stage condenser has been installed at the top of the main fractionator of FCC plant. FCC naphtha firstly enters the first stage condenser from the top of the tower, separating heavy gasoline and vapor. Then, the heavy gasoline is directly transported to the subsequent S Zorb unit for adsorption desulfurization. The vapor is sent to the second stage condenser for cooling. The cooled liquid enters the absorption and stabilization system and the rich gas is transported into the gas compressor system. This part of light gasoline is extracted from the bottom of the stabilization tower and is sent into another S Zorb unit for adsorption desulfurization. Due to the low olefin content and the high sulfur content of heavy gasoline, a higher severity can be used to reduce the sulfur content in gasoline. At the same time, light gasoline with high olefin content and low sulfur content can be processed with low severity to minimize the olefin saturation and alleviate the loss of octane number. SDS process principle flow is shown in Fig. 5.32 [16]. On the basis of SDS process, proprietary catalysts and their treatment methods were developed, and the corresponding processes were also proposed. Heavy olefins in gasoline were cracked into light olefins, and some of them were slightly aromatized. Heavy to Lights (HTL) technology was developed to produce gasoline with sulfur content less than 10 ug/g, while the heavy olefin in gasoline is aromatized and upgraded. The olefin aromatization and upgrading can increase the octane number of gasoline, and achieve an efficient use of gasoline hydrocarbons [16]. From producing Euro V motor gasoline to that of Euro VI, it is necessary to re-develop the combination process of MIP + S Zorb for motor gasoline production, and to form a combination route of Ultra LOF + SDS + HTL for motor gasoline

230

5 Engineering Aspects and Application of DTFB

Fig. 5.33 Diagram of basic technological route of existing and future motor gasoline production

production (shown in Fig. 5.33). Based on this combination route, the technologies of producing more blending components of gasoline with high octane number (such as isomerization, alkylation, hydrocarbon superposition, etc.) are integrated to improve the octane number of the front and middle fractions of gasoline. With the increasing demand for alkylated oil, more alkylation units will be put into use. The main raw material of alkylation unit is C4 component, which mainly origins from catalytic cracking LPG. The primary problem of alkylation unit is lack of C4 resource. As the demand for alkylated oil and C5 /C6 isomers continues to increase in the future, more isobutane and isopentane are needed. The new fine catalytic cracking process (fFCC) can provide a significant amount of isobutane and isopentane to meet the requirement. The fFCC process applies polycyclic naphthenes as the feedstock. It can produce more isoparaffin (isobutane, isopentane, etc.) and light aromatic such as xylene through precise reaction pathway control. Thus, it is able to realize the goal of simplification of feed oil composition, precision of reaction process and customization of target products. Since the quality of LCO is getting worse and the content of bicyclic and tricyclic aromatic hydrocarbons in LCO becomes more, LCO is deeply hydrogenated to convert polycyclic aromatic hydrocarbons (PAHs) into polycyclic alkanes, which can meet the requirements of feedstock composition off FCC process [15]. The catalytic cracking process based on the technology platform of DTFB reactor can not only regulate the volume fraction of olefin in gasoline, but also reduce the sulfur content of gasoline. In addition, it can reduce the benzene content in gasoline as well. The reduction of olefin content in gasoline can relief some negative effects, like the excessive olefin content in gasoline could affect the photochemical reactivity of automobile engine sediments, engine emissions and engine exhaust. It improves the combustion performance of gasoline and reduces the emission of photochemical smoke. Due to a variety of sulfur compounds in gasoline which could result in a lot

References

231

of damage, especially the burned sulfur compounds in gasoline will generate sulfur oxide and be discharged into the atmosphere, it will lead to acid rain and other environmental influences. The MIP process can reduce the sulfur content of gasoline by 30% ~ 50%, thereby correspondingly reducing the pollutant emission caused by sulfur combustion by 30% ~ 50%, and also alleviate the engine corrosion. Benzene is the lightest aromatic hydrocarbon in gasoline and volatilizes easily. People living and working near highways and garages are at the highest risk of carcinogenesis. The results show that the vehicle emissions account for 44% of outdoor toxic emissions and 50% of carcinogens. Benzene has the greatest risk of carcinogenesis. Compared with FCC process with more propylene production, benzene content in MIP gasoline decreases by 60%. Compared with FCC process with more gasoline production, benzene content in gasoline decreases by 30% ~ 50%.

References 1. Wang, W., Lu, B., Zhang, N., Shi, Z., Li, J.: A review of multiscale CFD for gas-solid CFB modeling. Int J. Multiphase Flow. 36(2), 109–118 (2010) 2. Chen, J.W., Xu, Y.H. (eds.): Catalytic cracking process and engineering (in Chinese), 3rd edn. China Petrochemical Press, Beijing (2015) 3. Karri, S.B.R., Knowlton, T.M.: In: Yang W.-C (ed.) Gas distributor and plenum design in fluidized beds, in Fluidization, Solids Handling, and Processing, pp. 209–235. William Andrew Publishing, Westwood (1999) 4. Sadeghbeigi, R.: Fluid catalytic cracking handbook, 3rd edn. Elsevier, Amsterdam (2012) 5. Xu, Y.H., Yu, B.D., Zhang, Z.G.: Advance in China fluid catalytic cracking (FCC) process. Scientia Sinica (Chimica). 44(1), 13–24 (2014) 6. Xu, Y.H.: Chemistry and Process of Catalytic Cracking (in Chinese). Science Press, Beijing (2013) 7. Molecular sieve group (Dalian Institute of Chemical Physics C.A.o.S., Zeolite (in Chinese). Science Press, Beijing (1978) 8. Qian, B.Z.: MIP revamping of heavy oil catalytic cracking unit in Fushun petrochemical company of PetroChina. Petroleum Refinery Eng. (in Chinese). 41(02), 56 (2011) 9. Mi, Y.Z.: Study on optimization technology of 1.2Mt/a vacuum residue RFCC unit. Energy Chem. Indust. (in Chinese). 36(2), 35–38 (2015) 10. Sun, S.H., Song, S.K., Shen, Z.F.: Industrial application of MIP series technologies in FCC units. China Petrochemical Press, Beijing (2017) 11. Treese, S.A., Pujadó, P.R., David, S.J.J. (eds.): Handbook of petroleum processing, 2nd edn. Springer, Cham (2015) 12. Dharia, D., Long, J., Xu, Y.H., Zhang, J.S., Yuan, E., Gim, S., Xu, S.: Consider new processes for clean gasoline and olefins production. Hydrocarb. Process. 9, 85–90 (2011) 13. Xie, Z.K., Zhou, X.G., Chen, F.Q.: Light olefins fundamentals of catalytic processes (in Chinese). China Petrochemical Press, Beijing (2013) 14. Xu, Y.H., Qu, J.H., Yang, Y.T., Xu, L.: Composition characteristics and octane number analysis of MIP series technical gasoline. Petroleum Process. Petrochem. (in Chinese). 40(1), 10–14 (2009) 15. Xu, Y.H., Wang, X., Zhang, Y.Y., Liu, T.: Study on fine fluid catalytic cracking technology. Petroleum Process. Petrochem. (in Chinese). 49(10), 1–8 (2018) 16. Xu, Y.H., Xu, L., Wang, X., Xu, G.L.: Key technologies and development of China's vehicle gasoline quality upgrading. Petroleum Process. Petrochem. (in Chinese). 50(2), 1–11 (2019)

Chapter 6

Series of MIP Process

Abstract This Chapter introduces a series of FCC processes based on the DTFB engineering platform. Starting from the FCC process with two reaction zones by creating the cracking and conversion reaction zones in the DTFB reactor, the process for maximizing Iso-paraffins (MIP), process for cleanser gasoline and propylene production (CGP), process for light cycle oil (LCO) to gasoline production (LTG), process for dry gas and coke reduction (DCR), the fine fluidized catalytic cracking (fFCC) process, and catalytic cracking process for producing gasoline with ultra-low olefins (Ultra LOF) have been successfully developed.

6.1

Introduction

The invention of diameter transformed fluidized bed reactor can date back to May 1998, when China was launching the gasoline cleansing programme. In view of the severe challenge of gasoline upgrading faced by catalytic cracking process, the concept of cracking and conversion reaction zones was proposed based on experimental phenomena and hydrocarbon chemical reaction path analysis. It was difficult for the equal-diameter riser reactor to realize cracking and conversion simultaneously, so a single-vessel fluidized bed reactor with multi-temperature zone and multi-flow type was needed to realize the cracking and conversion reaction simultaneously. Thus, the diameter transformed fluidized bed (short for DTFB) reactor technique was developed and had been being widely applied in FCC industry. A series of processes associated with DTFB reactor were developed including the Maximizing Iso-Paraffins (MIP) process, process for Cleanser Gasoline Plus Propylene Production (CGP), process for light cycle oil (LCO) to Gasoline Production (LTG), process for Dry Gas and Coke Reduction (DCR) as well as some processes in research like the fine fluidized catalytic cracking (fFCC) process and catalytic cracking process for producing gasoline with ultra-low olefins (Ultra LOF).

© Springer Nature Switzerland AG 2020 Y. Xu et al., Diameter-Transformed Fluidized Bed, Particle Technology Series 27, https://doi.org/10.1007/978-3-030-47583-3_6

233

234

6.2

6 Series of MIP Process

MIP Process

The development of China’s automobile industry is extremely rapid. By the end of 2015, the population of motor vehicles has reached 310 million, among which the population of automobiles have broken through 160 million. The substantial increase in car ownership has stimulated the demand for motor gasoline greatly. It is estimated that the demand for refined oil products will reach 420 Mt. by 2020, of which more than 140 Mt. is gasoline [1]. The motor gasoline in China mainly comes from FCC units. By the end of twentieth century, FCC gasoline has accounts for about 80% of automotive gasoline. But since the olefin content of FCC gasoline reaches high up to 45% ~ 60% (v), which is the main source of VOC, NOx and other toxic substances [2], the quality standard of motor gasoline that China launched late in 1999 specified for the first time, that the olefin content of gasoline should not exceed 35% (v), thus speeding up the pace of gasoline upgrades. On December 28, 1999, “Standard for Unleaded Motor Gasoline”, the GB179301999, was issued firstly, then the new series of “Standards for Motor Gasoline” came up and were implemented after amendment sequentially from 2006, then 2011 to 2013 and 2016 by the National Quality and Technical Supervision Bureau. Evolution of main indicators of China’s automotive gasoline standards (GB17930) are listed in Table 6.1. Because the structure of petrol refining units used to produce motor gasoline in China significantly differs from those in Europe and America, there would be hundreds of billions of investment on numerous constructions of new reforming and alkylation units if China follows the pattern of America and Europe in the production of clean gasoline. In China, FCC gasoline and reforming gasoline account for 65% and 20% of the gasoline pool respectively, while the gasoline produced by other units only accounts for 15%. Therefore, improving the quality standards of automotive gasoline in China means that the FCC process must provide better gasoline. However, the olefin and sulfur content in conventional FCC gasoline is so high that it sets an obstacle in the way of China’s gasoline upgrading process. Only after a new FCC process is developed to reduce olefin and sulfur content in gasoline, the FCC process can still dominate in refining processes. In another word, FCC process, especially the heavy oil catalytic cracking process, is facing the severe challenge of survival and development. Table 6.1 Main indicators of China’s automotive gasoline standards (GB17930) National Emission standards Issuing time Execution time Sulfur content/(μg/g) Olefin content/% Aromatic content/% Benzene content/% Oxygen content/%

I 1999 ≯1000 – ≯40 ≯2.5 –

II 2005 2006 ≯500 ≯35 ≯40 ≯2.5 ≯2.7

III 2006 2009 ≯150 ≯30 ≯40 ≯1.0 ≯2.7

IV 2011 2014 ≯50 ≯28 ≯40 ≯1.0 ≯2.7

V 2013 2018 ≯10 ≯25 ≯40 ≯1.0 ≯2.7

VI(A/B) 2016 2019/2024 ≯10 ≯18/15 ≯35 ≯0.8 ≯2.7

6.2 MIP Process

235

Table 6.2 The gasoline composition and properties of FCC family processes Parameters Density/(g/cm3) Induction period/min Hydrogen content/% Octane number RON MON Aromatics/% Benzene/% Olefin/% Paraffin/% n-paraffin/% Iso-paraffin /% Naphthene/%

FCC 0.7321 360 – 91.4 80.1 19.55 – 45.4 25.84 3.84 22.00 9.26

FCC 0.7263 380 – 92.4 80.0 18.98 – 46.12 26.97 3.95 23.02 7.92

ARGG 0.7200 535 13.61 91.8 79.7 20.38 1.64 37.78 33.82

MIO 0.7268 300 13.32 94.8 81.4 24.81 – 39.94 28.12

8.02

7.12

DCC-2 0.7378 755 12.44 97.0 82.1 31.67 38.87 22.98 4.42 18.56 6.48

DCC-1 0.7581 210 12.42 97.2 81.7 40.06 1.85 40.31 14.46 4.41 9.95 5.27

In the early 1980s, catalytic cracking technology was driven by the requirement of unleaded gasoline to develop from maximizing gasoline production to producing gasoline with high octane number. This is revealed mainly in variation of process parameters and catalyst types. Changes in the process are realized through measures listed as below: 1. 2. 3. 4.

High conversion High reaction temperature Short contact time Low partial pressure of oil-gas and high injection amount of steam

The research octane number (RON) can be increased by 3 units and the motor octane number (MON) by 1 unit with the help of the optimization of process parameters. In the term of catalysts, main types are listed as below: 1. 2. 3. 4.

Catalyst with REHY type zeolite Catalyst with USY type zeolite Catalyst with REUSY/REHUSY type zeolite Composite catalysts

These catalysts in pursuit of high octane barrel gasoline and high octane gasoline can bring about an increase of 3 units on RON and 1.5 units on MON [3]. The gasoline product produced by using these catalysts can meet the requirement of unleaded gasoline. However, to improve the octane number of gasoline by either the changed process conditions or the new zeolite catalysts was to increase the olefin content in essence, which was about 35%–60% at that time. Table 6.2 shows the gasoline composition of FCC and catalytic cracking family process in China. However, China’s automotive gasoline standard (GB17930-2006) required that the olefin content should not exceed 35% (v), aromatic content should not exceed 40% (v), benzene content should not exceed 2.5% (v) and sulfur content should not exceed 0.08%. According to the data listed in Table 6.2, the aromatic content in

236

6 Series of MIP Process

the composition of FCC gasoline was lower than the quality standard of motor gasoline, while the olefin content was much higher. So how to reduce the olefin content and maintain the high octane number of FCC gasoline was an urgent and difficult task then. A better way to reduce olefins in gasoline is to convert normal iso-olefins to iso-paraffins and aromatics as much as possible. This should start from studying the mechanism of the catalytic cracking reaction and understanding catalytic cracking reaction from an absolute new angle. It is necessary to change the conventional reaction mode and catalyst type to facilitate the cracking of heavy hydrocarbons and the conversion of olefins. By systemically studying the mechanism of catalytic cracking reaction and diagnosing the reaction results of hydrocarbons on different types of reactors, a new idea of MIP process for producing more iso-paraffins was proposed. The MIP process breaks the limitation of the hydrogen transfer and isomerization reaction in existing catalytic cracking process, and makes them take place sequentially with high controllability and selectivity, thus improving the product properties and distribution [4, 5].

6.2.1

Mechanism Analysis on the Cracking Reaction and Hydrogen Transfer Reaction

Using heavy feedstock, the gasoline olefin content obtained from the pilot plant riser reactor is usually high, whereas it is comparatively lower from the bench scale fixed fluidized bed reactor (short for FFB). Table 6.3 lists the results of Daqing atmospheric residue (AR) processed on these two different reactors. From the Table 6.3, it can be seen that there are differences in reaction results when different types of reactors being applied. Not only the product distribution changes, but more importantly, the product properties show great differences. After deep analysis on the chemical reaction system in catalytic cracking process, it can be concluded that parallel sequent reactions take place on the zeolite catalysts and then form a greatly complicated reaction system. The main reaction types are shown in Fig. 6.1 [3]. It indicates that the primary reactions of alkanes, naphthenes or aromatics are the process of C-C bond breaking and olefins formation from Fig. 6.1. A variety of secondary reactions take place sequentially afterward, which includes olefin cracking, cyclization, isomerization, oligmerization, hydrogen transfer, naphthene dehydrogenation, aromatics condensation, alkyl transfer and alkylation etc. It is noteworthy that except for a few secondary reactions (naphthene dehydrogenation, aromatic condensation and alkyl transfer), the above secondary reactions cannot occur without the participation of olefin molecules. The olefin products of the primary reaction basically take part in the secondary reactions as reactants. Reactions to produce iso-paraffins and aromatics are isomerization, hydrogen transfer and alkylation. As shown in Fig. 6.1, olefins are the reactants for all these reactions. In

6.2 MIP Process

237

Table 6.3 Experimental results of Daqing AR on two different reactors Item Operating conditions Temperature/
C WHSV/h1 Product distribution/% Dry gas LPG Gasoline LCO DO Coke Loss Isobutane/% Isobutene/% Gasoline composition/ % Aromatic Olefin n-paraffin Iso-paraffin Naphathene

Bench-scale fixed fluidized bed

Pilot-scale riser with equal diameter

500 10

530 78

3.58 22.59 47.82 11.99 6.02 8.00 – 6.44 1.53

2.95 28.08 40.63 11.69 8.58 7.64 0.43 4.69 4.18

30.04 25.55 5.88 31.79 6.72

25.99 49.20 3.54 15.17 6.10

another word, olefins are the precursors of iso-paraffins and aromatics. Thus, predictions of the possible reaction degree and optimum operation conditions are based on the reaction thermodynamics data of alkylation, which are listed in the Table 6.4 [3]. Table 6.4 shows that cracking is endothermic, while hydrogen transfer, isomerization and alkylation are exothermic. Therefore, based on Van’t Hoff’s isobaric equation, the increased temperature is beneficial to cracking while unfavorable to hydrogen transfer, isomerization and alkylation. As for the detrimental effect of high temperature on exothermic reactions, hydrogen transfer reaction’s equilibrium constant is more susceptible to thermodynamics. At the high temperature like 527
C, the alkylation reaction merely happens. It can be surmised that lower temperature is more beneficial to iso-paraffins formation, but its olefin precursors can only be obtained through the high-temperature catalytic cracking; the above two processes are actually contradictory. Since the olefin precursors for iso-paraffins are the intermediates in the series reactions, it is reasonable to divide the formation and reaction of olefins into two parts, as shown in Fig. 6.2 [4, 5]. In order to achieve the formation of iso-paraffins and aromatics, as shown in Fig. 6.2, the reactions are divided into two parts with olefins as the transition point: in the first reaction zone, olefins are generated under the condition of high temperature, short contact time and high catalyst-to-oil ratio by the heavy feedstock cracking. This makes more olefins with larger molecular weight have no sufficient time to be

238

6 Series of MIP Process

Fig. 6.1 Main reaction types of hydrocarbons occurring on catalysts [3] Table 6.4 Thermodynamics data of hydrogen transfer, isomerization and alkylation reactions Reaction type Cracking Hydrogen transfer Isomerization Alkylation

Reaction chemistry n-C10H22 ! n-C7H16 + C3H6 i-C8H16 ! 2i-C4H8 4C6H12 ! 3C6H14 + C6H6 CycloC6H12 + 3i-C5H10 ! 3C5H12 + C6H6 1-C4H8 ! t- 2-C4H8 1-C4H8 ! i- C4H8 1-C4H8 + i- C4H10 ! i- C8H18

lgKE (equilibrium constant) 454
C 510
C 2.04 2.46 1.68 2.10 12.44 11.09 11.22 10.35

527
C – 2.23 – –

Reaction heat/ (KJ/mol) 510
C 74.55 78.30 255.11 170.37

0.32 – –

0.09 0.236 3.3

11.34 – –

0.25 – –

further cracked; meanwhile high reaction severity can help reduce the production of n-paraffins and naphthenes which are the low-octane gasoline components. It is very advantageous to increase the octane number of gasolines. The olefin conversion

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239

Fig. 6.2 Cracking and conversion reaction paths from hydrocarbons to iso-paraffins

reaction is set in the second reaction zone. Due to the fact that there are both parallel and tandem reactions taking place simultaneously in the course of the olefins’ transition to iso-paraffins and low temperature is favorable for the course, low temperature and long residence time would greatly promote the olefins’ transition to iso-paraffins and aromatics. In general, the formation of iso-paraffins and aromatics from olefins in gasoline which is through hydrogen transfer reaction, is classified into the following two types [3]: Hydrogen transfer reaction type I. 3Cn H2n þ Olefins

Cm H2m ! 3Cn H2nþ2 þ Cm H2m6 Aromatics Paraffins Naphthenes ðOlefinsÞ

Hydrogen transfer reaction type II.

R R

R

R

R R R,R

H Transfer CnH2n-2, + CmH2m-6 Alkylation, R Cyclo-olefins Aromatics Condensation

R

R

Condensed R , ··· , polycycles R

R

Coke precursors

Cn H2n Olefins

H addition

!

Cn H2nþ2 Paraffins

The experiments of hydrogen transfer reaction of light olefins were carried out in FFB unit. The process flow scheme is shown in Fig. 6.3. This bench scale unit consists of the FFB reactor, a feed system, a product collection system and a control system. Gas chromatography was used to analyze the composition of cracking gas;

240

6 Series of MIP Process

6 16 14

15

4 7

12

13

8 3

9

1 2

10

11

5

Fig. 6.3 The process flow scheme of FFB unit 1-oxygen; 2-compressed air; 3-distilled water;4-feedstock pump; 5-water pump; 6-heater; 7-water cooler;8-reactor;9 ~ 11-gasoline collecting bottles; 12-water cooler; 13-air cooler;14-cracking gas; 15-flue gas; 16-the sampling point

off-line chromatograph was used to simulate distillation of liquid products to obtain gasoline, light cycle oil (LCO) and decanted oil (DO) fractions. And gas chromatograph was used to analyze gasoline fractions in detail to obtain PIONA data; mass spectrometry and gas chromatography were combinedly applied to determine the amount of hydrocarbon semi-quantitatively in liquid products by hydrocarbon carbon number distribution method (HCND); the off-line chromatograph was used to analyze the flue gas from catalyst coke burning, and the amount of coke was calculated according to the content of CO and CO2 in the flue gas. Hydrogen transfer reaction of olefins was studied under various operating conditions utilizing FCC gasoline with high olefin content as the feedstock. The experimental results were analyzed and synthesized to determine the difference of process parameters in favor of type I or type II of hydrogen transfer reaction, and to provide reliable control direction for selectively controlling hydrogen transfer reaction type. FCC gasoline feedstock used in the test was gasoline A and B respectively, and their composition was shown in Table 6.5. It can be seen that the olefin content in gasoline A is similar to that in the conventional FCC gasoline, while the olefin content in gasoline B is at a higher level. To depict the composition variation of the FCC gasoline before and after the reaction accurately, the following parameters are defined (it is hypothesized the aromatic and iso-paraffin in the feedstock take no part in the reaction):

6.2 MIP Process Table 6.5 Component of catalytic cracking gasoline used in experiments

241 Component Group composition/% Paraffins n-paraffins iso-paraffins Naphthenes Olefins Aromatics

Gasoline A

Gasoline B

29.6 5.3 24.3 8.3 37.8 24.3

23.1 5.0 18.1 7.5 50.7 18.7

1. Olefin conversion capability (Co) is defined as the olefin content in feedstock (Fo) minus the olefin content in the gasoline product (Po) multiplied by the gasoline yield (YG), simply put as following equation: C o ¼ F o  Po Y G 2. The increase range of aromatics (ΔA) is defined as the aromatics content in the gasoline product (PA) multiplied by the gasoline yield minus aromatics content in the feedstock (FA). This parameter demonstrates the increasing amount of the aromatics caused by the feedstock olefins participation in hydrogen transfer reaction. It can be expressed by the following equation: ΔA ¼ PA Y G  F A 3. The increase range of iso-paraffins (ΔIP) is defined as the iso-paraffins in the gasoline product (PIP) multiplied by the gasoline yield minus iso-paraffins in the feedstock (FIP). This parameter demonstrates the increasing amount of the iso-paraffins caused by the feedstock olefins participation in hydrogen transfer reaction. It can be expressed by the following equation simply: ΔIP ¼ PIP Y G  F IP 4. The increase range of naphathene (ΔN) is defined as the naphathene in the gasoline product (PN) multiplied by the gasoline yield minus naphathene content in the gasoline feedstock (FN). This parameter demonstrates the increasing amount of the naphathene caused by the feedstock olefins participation in hydrogen transfer reaction. It can be expressed by the following equation: ΔN ¼ PN Y G  F N 5. The selectivity of aromatics (SA) is defined as the ratio of its increase range (ΔA) to olefin conversion capability (Co). This parameter reveals the capability of the feedstock olefins converted to aromatics in the hydrogen transfer reaction. It can be expressed by the following equation:

242

6 Series of MIP Process

SA ¼ ΔA =Co 6. The selectivity of iso-paraffins (SIP) is defined as the ratio of the iso-paraffin increase range (ΔIP) to olefin conversion capability (Co). This parameter reveals the capability of the feedstock olefins converted to iso-paraffins in the hydrogen transfer reaction. It can be expressed by the following equation: SIP ¼ ΔIP =C o 7. The selectivity of naphathene (SN) is defined as the ratio of the naphathene increase range (ΔN) to olefin conversion capability (Co). This parameter reveals the capability of the feedstock olefins converted to naphathene in the hydrogen transfer reaction. It can be expressed by the following equation: SN ¼ ΔN =Co 8. The total selectivity is defined as the selectivity sum of aromatics, iso-paraffins and naphthene. This parameter reveals the capability of olefins in the gasoline feed participating in hydrogen transfer reaction to produce aromatics, iso-paraffins and naphthene. It can be simply expressed as the following equation: ST ¼ SA þ SIP þ SN 9. The selectivity of liquefied petroleum gas (SLPG) is defined as the ratio of the LPG yield (YLPG) to the olefin conversion capability. This parameter reveals the capability of feedstock olefins converted to LPG in cracking reaction. It can be simply expressed as the following equation SLPG ¼ Y LPG =Co 10. The ratio of cracking reaction to hydrogen transfer reaction (SLPG/T) is defined as the LPG selectivity (SLPG) to the total hydrocarbon selectivity. The larger this parameter, the greater the probability of the feedstock olefins participation in cracking reaction, vice versa. It can be expressed as the following equation: RLPG=T ¼ SLPG =ST The gasoline A was studied with different types of catalysts including CIP-1, ZCM-7 and CRC-1 under the experiment conditions of the temperature of 300
C, the WHSV of 4 h1 and the mass ratio of catalyst to oil of 5. All the results are listed in Table 6.6. It is shown in Table 6.6 that the total hydrocarbon selectivity ST from high to low is CRC-1 > RAG-1 > CIP-1 > ZCM-7; the iso-paraffin selectivity SIP from high to

6.2 MIP Process

243

Table 6.6 Experimental data of gasoline A with different types of catalysts Item Type of zeolites n(Si)/ n(Al) Product distribution/% Dry gas LPG Gasoline LCO DO Coke Loss Gasoline composition/% n-paraffin Iso-paraffin Olefin Naphathene Aromatics Characteristic parameters Co ΔA ΔIP ΔN SA S IP SN ST SLPG RLPG/T

CRC-1 REY 2.0

ZCM-7 USY 6.5

RAG-1 REY+USY+ZRP 8.0

CIP-1 REUSY+ZRP 12.0

0.46 1.88 88.45 3.85 0.05 5.26 0.05

0.39 2.59 88.45 3.87 0.80 3.83 0.07

0.33 0.97 91.70 4.18 0.30 2.45 0.07

0.56 1.30 92.65 3.19 0 2.25 0.05

9.37 42.85 8.10 11.92 27.76

7.00 38.54 16.68 9.83 27.95

9.20 33.89 16.72 11.42 28.77

8.88 30.91 19.76 11.22 29.23

30.64 0.25 13.60 2.24 0.83 44.40 7.32 52.55 6.13 0.12

23.05 0.42 9.79 0.39 1.83 42.47 1.71 46.02 11.24 0.24

22.47 2.08 6.78 2.17 9.27 30.16 9.67 49.10 4.32 0.09

19.49 2.78 4.34 2.10 14.27 22.26 10.75 47.28 6.67 0.14

low is CRC-1 > ZCM-7 > RAG-1 > CIP-1; and the aromatics selectivity SA from high to low is CIP-1 > RAG-1 > ZC M-7 > CRC-1. Considering the order of coke yield from high to low, it can be deduced that the order of hydrogen transfer reaction type I from high to low is CIP-1 > RAG-1 > ZCM-7 > CRC-1, while the order of hydrogen transfer reaction type II from high to low is just the opposite. In another word, hydrogen transfer reaction type II is prone to occur on catalysts with low Si/Al ratio, while hydrogen transfer reaction type I is prone to occur on catalysts with high Si/Al ratio. The order of LPG selectivity from high to low is ZCM-7 > CIP-1 > CRC1 > RAG-1. The ratio of LPG selectivity to total hydrocarbon selectivity is in the order of ZCM-7 > CIP-1 > CRC-1 > RAG-1. This shows that ZCM-7 catalyst has the best performance on reducing olefin content in gasoline and enhancing LPG yield; CRC-1 catalyst is the best catalyst on reducing olefin content in gasoline and enhancing gasoline yield.

244

6 Series of MIP Process

Table 6.7 Experimental data of gasoline B on the spent and regenerated catalyst LV-23

Item Product distribution/% Dry gas LPG Gasoline LCO DO Coke Loss Sum Gasoline distribution/% n-paraffin Iso-paraffin Olefin Nathaphene Aromatic Characteristic parameters Co ΔA ΔIP ΔN SA SIP SN ST SLPG RLPG/T

LV-23 regenerated catalysts (REUSY) 400
C

LV-23 spent catalysts (REUSY) 450
C 400
C

0.35 5.07 87.65 3. 56 0.77 2.50 0.10 100

0.45 6.36 87.43 3.82 0.21 1.50 0.23 100

0.15 1.88 92.08 3.93 0 1.75 0.21 100

5.39 37.25 26.60 10.48 20.28

5.59 33.10 26.46 8.10 26.75

5.14 32.51 33.96 8.04 20.35

27.39 0.92 14.55 1.69 3.38 53.13 6.16 55.91 18.51 0.33

27.57 4.69 10.84 0.42 17.00 39.32 1.52 54.81 23.07 0.42

19.43 0.04 11.84 0.10 0.20 60.91 0.50 60.61 9.68 0.16

Furthermore, the regenerated and spent LV-23 catalysts were applied with gasoline B as the feedstock. The experiments were carried out at a weight hourly space velocity (WHSV) of 10 h1 and a mass ratio of catalyst to oil of 4. The results are listed in Table 6.7. It is shown in Table 6.7 that under the same reaction conditions, the total selectivity ST by using regenerated catalysts is less than that by using spent catalysts, and both SA and SIP of regenerated catalysts are less than those of spent catalysts. If the coke yield is taken into account, it can be deduced that the type of hydrogen transfer reaction II is prone to occur on regenerated catalysts, and the type of hydrogen transfer reaction I is prone to occur on spent catalysts. Table 6.7 also shows that the total selectivity ST at high reaction temperature is lower than that at low reaction temperature; but SA at high reaction temperature is higher than that at low reaction temperature; while SIP at high reaction temperature is

6.2 MIP Process

245

much lower than that at low reaction temperature. Therefore, it can be deduced that higher temperature is more favorable for hydrogen transfer reactions I while lower temperature is beneficial to hydrogen transfer reaction II. With the same gasoline yield, the total hydrocarbon selectivity ST by using regenerated catalysts is higher than that by using spent catalysts, while the LPG selectivity SLPG of regenerated catalysts is lower than that of the spent catalysts. The sum of ST and SLPG of regenerated catalysts is still lower than that of spent catalysts, while the ratio of SLPG to ST of regenerated catalysts is lower than that of spent catalysts. All these data illustrate that the synergistic effect of the hydrogen transfer reaction and cracking reaction by using spent catalysts is better than that by using regenerated catalysts, especially for increasing the yield of LPG. Under the similar operating conditions, ST by using regenerated catalyst is less than that by using spent catalysts, while SLPG of regenerated catalyst is greater than that of spent catalyst. The total selectivity ST of regenerated catalyst is greater than that of spent catalysts, and the ratio of SLPG to ST of regenerated catalyst is greater than that of spent catalyst. The synergistic effect of hydrogen transfer reaction and cracking reaction is better than that of spent catalyst. Therefore, more aromatics can be produced by the hydrogen transfer reaction type I of olefin on the molecular sieve catalyst with higher Si/Al ratio or at higher reaction temperature or at lower WHSV. More iso-paraffins can be produced by the hydrogen transfer reaction type II of olefin on the molecular sieve catalyst with lower Si/Al ratio or at lower reaction temperature or at higher WHSV. Different types of hydrogen transfer reactions play an important role in product distribution, especially in the composition of products. In a word, by selecting appropriate process parameters and catalyst types, different types of hydrogen transfer reactions of olefins in gasoline can be realized to saturate the olefins meanwhile the coke yield is barely increased or olefins are converted into iso-paraffins as much as possible [6].

6.2.2

Experiment Studies on MIP Process

6.2.2.1

Different Types of Fluidized Bed Experiments

Catalytic cracking of heavy hydrocarbon is carried out on FFB unit at a relatively constant reaction temperature and a longer residence time. In this process, the heavy hydrocarbon is cracked into olefins, while olefins undergo further hydrogen transfer reactions. The first and second reaction zones can be simulated by catalytic cracking of heavy hydrocarbon as feed oil in this device. The second reaction zone can be simulated by catalytic conversion of gasoline enriched olefins as feedstock over a spent catalyst. Firstly, experiments were carried out in FFB unit using catalyst D listed in Table 6.8 and feedstock C listed in Table 6.9. The operating conditions and results are listed in Table 6.10. At the same time, the experimental data obtained on pilot plant riser unit and the performance test run data obtained on industrial catalytic

Properties Type of zeolites Composition/% Al2O3 Na2O Fe3O4 Physical properties Apparent density/(kg/m3) Pore volume/(mL/g) BET area/(m2/g) Attrition index/(%/h) Size composition/% 0 ~ 40 μm 40 ~ 80 μm > 80 μm Reaction activity (790
C,17 h, aging)

Table 6.8 Catalyst properties

48.7 – –

33.0 0.29 1.1

560 0.45 270 3.2

15.2 55.1 29.7 66

26.5 0.19 0.09

– 0.41 400 4.2

12.0 43.7 44.3 66

21.7 39.1 39.2 67

860 0.55 – 2.8

B2

Catalyst type A B1 REY REHY

4.8 47.9 47.3 65

690 0.38 – –

46.4 0.22 0.32

C USY

13.1 54.9 32.0 68

620 0.36 232 2.5

44.6 0.13 –

D REY + USY + ZRP

6.9 65.4 27.7 65

660 0.37 167 2.9

47.0 0.20 0.50

E REY + USY

– – – 51(carbon accounts for 1.2%)

– – – –

51.2 0.32

F The spent catalyst

246 6 Series of MIP Process

6.2 MIP Process

247

Table 6.9 Feedstock Properties

Properties Density(20
C)/ (kg/m3) Kinematic viscosity/(mm2/s) 80
C 100
C CCR/% Condensation point/
C Basic nitrogen/(μg/ g) Nitrogen/% Sulfur/% Carbon/% Hydrogen/% Heavy metal/(μg/ g) Ni V Fe Cu Na Distillation range/
C IBP 10% 30% 50% 70% 90% FBP

Feedstock type Paraffinic CGO VGO A B 873.0 869.6

Atmospheric residue C 897.4

Atmospheric residue D 868.7

Atmospheric residue E 897

13.01 8.04 0.15 50

6.66 4.54 0.84 33

54.20 30.02 4.5 47

11.15 5.0 50

12.79 3.58 42

340

1920

0.10 0.073 86.5 13.24

0.29 0.13 86.55 13.03

0.27 0.14 86.26 12.91

0.12 0.18 86.43 12.92

0.23 0.41 86.30 12.70

1000

>1000

>1000

667

86.46

86.37

86.29

86.36

86.08

13.54

13.63

13.71

13.64

13.92

228

186

174

571

561

26

35

30

60

52

23.8 23.8 52.4

20.2 30.9 48.9

18.3 34.9 46.8

16.5 41.8 41.7

15.4 54.9 29.7

90.3 80.1

89.0 78.7

89.6 78.7

90.9 80.0

90.9 78.7

956.6

927.2

914.0

916.0

920.7

90.81 9.19 0.369 0.073