Sustainable and Digital Building: Proceedings of the International Conference, 2022 3031257944, 9783031257940

Citation preview

Florindo Gaspar Artur Mateus   Editors

Sustainable and Digital Building Proceedings of the International Conference, 2022

Sustainable and Digital Building

Florindo Gaspar  •  Artur Mateus Editors

Sustainable and Digital Building Proceedings of the International Conference, 2022

Editors Florindo Gaspar Centre for Rapid and Sustainable Product Development Escola Superior de Tecnologia e Gestão Polytechnic of Leiria Leiria, Portugal

Artur Mateus Centre for Rapid and Sustainable Product Development Polytechnic of Leiria Leiria, Portugal

ISBN 978-3-031-25794-0    ISBN 978-3-031-25795-7 (eBook) https://doi.org/10.1007/978-3-031-25795-7 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed 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

Introduction

Considerable challenges are put nowadays on the improvement of the construction industry efficiency, which has been widely recognised as an industry that faces many challenges. A big focus is nowadays put on green buildings throughout their lifecycle, from planning to design, construction, operation, maintenance, renovation and demolition. In addition, this industry is currently making the transition to digital working, creating new opportunities. The digital transformation of buildings is a key point to achieve the European climate goals, and to reach net-zero carbon buildings by 2050, the building industry needs to search for the optimal performance that relies on the use of sustainable materials and new building processes, such as additive manufacturing, BIM and digital twin methodologies. Given the relevancy and necessity of these subjects, the Sustainable and Digital Building Conference had the objective to create a forum of discussion, covering different topics on this broad area, having the contribution of some experts in the field. These proceedings are composed of chapters covering topics about building energy efficiency, digital construction, sustainable materials, construction systems and building modelling, which give a great contribution to the future needs of the construction sector. The keynote lectures highlighted the importance of digital tools on the construction site, showing the actual challenges on the safety of the workers and on the machinery operation towards green construction achievement. Also, innovative sustainable mineral-bonded composites for digital construction were showed. The conference speakers gave a clear picture of the challenges on additive manufacturing, the development of new sustainable materials and the use of digital technologies in the construction process and also in the planning stage. The editors acknowledge all participants, keynote speakers, authors, members of the scientific committee, sponsors, session chairs and administrative assistants for their contribution to the success of this conference.   Florindo Gaspar   Artur Mateus v

Contents

Part I Digital Construction Web Application for Visualizing Emission Data from Construction Equipment������������������������������������������������������������������������    3 Lylian M. Andrade and Jochen Teizer  ransforming the Civil Engineering Surveyor����������������������������������������������   17 T Andrew Evans, Genna Rourke, Ivor Barbrook, Ian Heaphy, Abigail Tomkins, Marek Suchocki, Sangeetha Senthil Kumar, and Matt Haigh  imes with Hydraulic Properties for 3D Printing Mortars ������������������������   41 L B. D. Dias, D. Rocha, P. Faria, S. S. Lucas, V. A. Silva, B. Lobo, and A. Reaes Pinto Comparison of Exhaust Gas Emissions Between Autonomous and Human Operator Excavator��������������������������������������������������������������������   51 Tanja Kolli, Mikko Hiltunen, Ilpo Niskanen, Pekka Tyni, Matti Immonen, and Rauno Heikkilä Additive Manufacturing Earth-Based Composite: Strategical and Computational Methodology for Building Shell Geometries ��������������   61 Mohamad Fouad Hanifa, Bruno Figueiredo, and Paulo Mendonca Incorporation of Forest Biomass-Based Fly Ash in Cement for 3D Printing ������������������������������������������������������������������������������������������������   73 Arpan Joshi, Tomás Archer de Carvalho, and Florindo Gaspar Digitally Enabled Quality Assessment of In Situ Concrete Works: A Case Study from Norway����������������������������������������������������������������������������   89 Halvard L. Pedersen and Christoph Merschbrock  D Printing for Construction: A Systematic Review of Its Sustainability��  103 3 F. Simioni, B. Rangel, N. Campos, and J. Teixeira

vii

viii

Contents

Part II Sustainable Materials  oplar as an Alternative Species for Load Bearing Structures ������������������  117 P Carlos Martins, Cláudio Ferreira, João Negrão, and Alfredo M. P. G. Dias Structure-Forming Composition of a Mixture of Rice Husk and Wheat Straw for Thermal Insulation������������������������������������������������������  127 Aliaksandr Bakatovich, Florindo Gaspar, Nadezhda Bakatovich, and Zhang Yi  eopolymer Cement for Sustainable Construction: A Review ������������������  149 G Tomás Archer de Carvalho, Florindo Gaspar, Artur Mateus, and Ana Marques Part III Construction Systems Mountable and Demountable Construction Systems of Interior Building Partitions: Ecology and Sustainability in the Ephemeral Use of Space������������������������������������������������������������������������������������������������������  169 Pedro Fonseca Jorge and Sérgio Gomes Pires Gonçalves Application of a Prefabricated Wooden-­Based System for Collective Buildings in a Four-Storey Portuguese Building������������������  183 Marina Tenório, Jorge M. Branco, and Sandra M. Silva Bioretention System: Conception, Implementation, and Instrumentation of Three Different Models in São Paulo, Brazil���������������  195 M. C. S. Pereira, J. R. S. Martins, S. C. M. Gonzaga, and P. R. M. Pellegrino A New Inclusive Housing Model for Sustainable Actions in Recycling Buildings ������������������������������������������������������������������������������������  207 Martina Nobili and Eugenio Arbizzani Vegetation Roofs for Sponge Cities: A Vision from Research to Practice ��������������������������������������������������������������������������������������������������������  219 Zuzana Vranayová, Alena Vargová, Marián Vertaľ, and Katarína Čákyová  ifferentiating Factors in Customer Experience Between Off-Site D Manufacturing and Conventional Construction ������������������������������������������  231 David Schafft, Zakaria Dakhli, and Mohamed Zaki Sustainable Apartment Hotel with Autonomous Water and Electricity Systems������������������������������������������������������������������������������������  241 Myroslava Horlo and Pavol Purcz

Contents

ix

Part IV Building Modeling Improving Sustainability of Building Operation and Maintenance (O&M) Process Through Ontologies: An Introductory Framework����������  251 Francesco Livio Rossini, Gabriele Novembri, and Edoardo De Santis Analysis of the Diffusion of BIM in the Brazilian Research Segment Using the Lattes Platform����������������������������������������������������������������  261 Clézio Rogério dos Santos Júnior, Josyanne Pinto Giesta, and Alfredo Costa Neto A Review of Building Information Modelling Applications for Disaster Resilience Assessment ����������������������������������������������������������������  269 Rossella Marmo, Federica Pascale, and Enrico Sicignano Modeling of Behavior of the Bending Reinforced Concrete Structures Under Load������������������������������������������������������������������������������������  279 D. Lazouski, D. Glukhov, Y. Lazouski, and A. Hil Part V Building Energy Efficiency Building Thermal Modelling Used in DSF Design Applied in Ventilated Spaces ����������������������������������������������������������������������������������������  293 Eusébio Conceição, João Gomes, Mª. Inês Conceição, Mª. Manuela Lúcio, and Hazim Awbi Occupant Three-Dimensional Aero-­Thermal Design Using a Coupling Methodology ��������������������������������������������������������������������������������  303 Eusébio Conceição, Mª. Inês Conceição, João Gomes, Mª. Manuela Lúcio, and Hazim Awbi Impact of Automated Roof Shading on Building Energy Performance in Warm and Humid Climates of India����������������������������������  311 Kuladeep Kumar Sadevi and Avlokita Agrawal Raising Awareness of Climate Change by Building a Green Roof in Technical University of Kosice’s Campus��������������������������������������������������  321 Martina Zelenakova, Maria Hlinkova, and Maria Manuela Portela Index������������������������������������������������������������������������������������������������������������������  331

Part I

Digital Construction

Web Application for Visualizing Emission Data from Construction Equipment Lylian M. Andrade

and Jochen Teizer

1 Introduction According to the World Business Council for Sustainable Development [1], the construction industry accounts for approximately 38% of global greenhouse gas (GHG) emissions. At least half of all emissions in a building derive from embodied carbon (caused by material production and the construction process). At the same time, roughly 30% of this is emitted during the construction phase, accounting for emissions mainly associated with material transportation, material waste, and equipment operation. In line with the new European Green Deal [2], the European Union (EU) aims to be climate-neutral and reach net-zero greenhouse gas emissions by 2050. As part of this plan, the European Commission has a target to reduce emissions by 55% by 2030 and accordingly has established five EU missions, among which are the delivery of 100 climate-neutral and smart cities by 2030 [3]. To achieve this goal, construction and its building and infrastructure sectors will have to commit to rapid change and to approach assessing, monitoring, and improving the construction’s carbon footprint significantly. For the past years, significant effort has been put into digitalizing the construction industry, and the use of technologies such as Building Information Modelling (BIM) and the Internet of Things (IoT) has grown exponentially. While each comes with benefits, they also have limitations when joined. For example, integrating BIM and IoT can provide several applications such as monitoring, analysing, predicting, L. M. Andrade Aarhus University, Department of Civil and Architectural Engineering, Aarhus, Denmark J. Teizer (*) Technical University of Denmark, Department of Civil and Mechanical Engineering, Lyngby, Denmark e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 F. Gaspar, A. Mateus (eds.), Sustainable and Digital Building, https://doi.org/10.1007/978-3-031-25795-7_1

3

4

L. M. Andrade and J. Teizer

and optimizing construction and building performances [4]. The connection of data from sensors to high-fidelity BIM models also represents a strong paradigm in the creation of the so-called DTs, of which some are virtual models of a physical asset updated from real-time data throughout its project phase or facility asset life cycle [5]. Although the DT concept has gained notoriety in the past years, research addressing DTs in the architectural, engineering, construction, and facility management (AEC/FM) domains is rather limited and has firstly focused on monitoring building use or performance measurement during the facility management stage [6]. While in construction management, the integration of BIM and IoT has been primarily studied for productivity and safety purposes [7]; however, there is a lack of studies exploring DTs in applications that monitor emissions during the construction stage. As for construction emissions, a considerable amount of these originate from fuel consumed by construction equipment. Existing EU regulations include standards for emissions caused by heavy construction equipment, such as carbon monoxide (CO), nitrogen oxides (NOx), and particulate matter (PM). However, not only are these emissions hard to estimate, but they are harder to control so that standards are met. Recent studies have explored means of measuring and monitoring emissions caused by construction equipment by using, for instance, Portable and Smart Emission Measurement Systems (PEMS, SEMS) [8]. While such systems have proven effective in collecting and transmitting data through IoT, there has not been much research on how data can be integrated and visualized for end-users in a meaningful way in BIM as part of a DT. Despite the application of DT technology in construction being promising for controlling and reducing construction emissions, many challenges remain regarding its development and implementation. The process of creating a construction DT is complex and comprehensive, and there is not a commonly defined framework for it [9]. To contribute to the recent advancements in DTs and emissions monitoring and control, this work aims to develop a BIM-based web application for visualizing emission data from heavy construction equipment. The goal is to test the methodology and demonstrate its application, while understanding benefits, limitations, and next steps.

2 Background 2.1 Internet of Things in the Construction Industry Since the emergence of Industry 4.0, the Internet of Things (IoT) has become crucial to the digital transformation of the construction sector. The International Organization for Standardization [10] defines IoT as “an infrastructure of interconnected objects, people, systems and information resources, coupled with intelligent

Web Application for Visualizing Emission Data from Construction Equipment

5

services that allow them to handle and react to information from the real and virtual environment”. Typical Internet-enabled technologies include sensing, identification and position technologies, hardware, software, cloud platforms, communication technologies, etc. In the construction industry, IoT typically relates to telematics devices and sensors installed in job sites and buildings to monitor activity, physical states, and operation conditions [5]. Some of the benefits associated with the use of IoT in construction are higher productivity, safety, and better control of quality, schedule, and cost of projects, due to enabling effective performance monitoring and faster decision-making [11, 12]. Few studies so far focused on integrating environmental and localization data in BIM [7]. Notwithstanding, a few barriers prevent the widespread adoption of IoT in construction projects. Reference [13] named a few: security and privacy issues, documented standards, benefit awareness, and robustness in signal connectivity given in the harsh working environment.

2.2 BIM and IoT Integration for Digital Twins An additional method that has significantly changed how information is produced and exchanged in standardized formats is BIM. BIM encloses both the workflows and the technology for virtual object-oriented modelling of construction products and processes. By containing both geometric and semantic information about the building elements, BIM has been widely applied for building design and life cycle management [14]. However, despite facilitating the sharing and management of information, BIM refers to static data and less capable of updating models with real-­ time information [15]. With the applications of IoT in the AEC/FM industry, the integration of real-time data and BIM data became a promising solution and enabled the emergence of the DT. Likewise is conceptualization of a DT as a digital representation of a physical asset, constantly exchanging information with each other throughout the asset’s life cycle [16]. The exchange and analysis of data between the physical and virtual counterparts is enabled by technologies such as IoT and machine learning, respectively [17]. A DT can be used for several purposes such as real-time project monitoring and management, automated model updating, analysing, predicting, and optimizing performance [4]. According to [18], the workflow of a DT operating at its full potential initiates at the early project stage with data collection and design of a BIM model. Data should then be continuously collected and updated in the model throughout the construction project life cycle combining both project information and data from different sensors to obtain a complete as-built model. Data is stored, processed, and integrated through cloud computing, and the virtual model of the physical asset is updated in real time with essential data, allowing end-users to make analysis and informed decisions [18].

6

L. M. Andrade and J. Teizer

Several recent studies have also explored integrating BIM and IoT systems with BIM models for developing digital building twins. References [6, 9, 19, 20] have all created web-based platforms for visualizing real-time indoor climate conditions of building facilities connecting sensor data and BIM models. Reference [21] demonstrated a cloud-based data management framework for monitoring environmental data from sensors in construction sites.

2.3 Cloud Computing Services for Digital Twins Cloud computing is responsible for a massive part of the digital space of a DT. In simple terms, it comprises the delivery of IT services by third-party providers through the Internet, such as storing and accessing data and applications. There are three main types of cloud computing services: Infrastructure-as-a-Service (IaaS), Platforms-as-a-Service (PaaS), and Software-as-a-Service (SaaS), which differ according to levels of flexibility and management by the customer and the cloud provider [22]. For the creation of a DT, it is important to choose a cloud computing service that enables the development of a customizable application that multiple users can access over the Internet [6]. PaaS services are currently the most popular choice among developers since they provide platforms for building, deploying, and managing flexible and scalable applications over the Internet more quickly and cost-­ effectively without handling the whole IT infrastructure [22]. Commercial PaaS providers are Heroku, AWS Elastic Beanstalk, Microsoft Azure App Services, Salesforce, and Autodesk Forge. In connection to BIM and IoT integration, Autodesk Forge is a cloud-based development PaaS that offers a platform with a set of application programming interfaces (APIs). These allow developing further web applications that facilitate the integration between BIM models and field data sources. Forge is already used in the development of DT solutions for real-time data visualization and other purposes [23].

2.4 Heavy Construction Equipment Emissions and Regulations According to [24], heavy construction machinery, also called Non-Road Mobile Machinery (NRMM), accounts for more than 50% of emissions originating from construction operations. NRMM typically uses powerful diesel engines that consume a large amount of fuel and produces different types of pollutants, such as nitrogen oxides (NOx), hydrocarbon (HC), carbon monoxide (CO), particulate matter (PM), and carbon dioxide (CO2) [25]. While the electrification of on-road vehicles (cars, busses, etc.) has increased over years, this is not the case for electric NRMM [26].

Web Application for Visualizing Emission Data from Construction Equipment

7

Emission standards for non-road vehicles have been implemented since the 1990s to control emissions from construction machinery (e.g. EPA Tier I of the USA in 1994 or EU Stage I in 1999). The European standards have been narrowed several times over the years (Stages I–V) and are currently regulated by EU regulation 2016/1628, containing threshold values of carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NOx), and particulate matter (PM) that an NRMM engine must comply with. These thresholds are based on laboratory tests made on several engines [27]. Different methods for measuring and predicting construction machines’ emissions have appeared in the past years. One of these is in-lab engine tests conducted by testing the engine with a dynamometer on a test bench operating in test duty cycles to simulate operating conditions. These are mainly used for emission certification approvals and generally have high costs [28]. A widely used model to estimate emissions from non-road engine tests is the NONROAD model from Ref. [29]. Another approach is on-board measurement instruments such as the Portable Emissions Measurement System (PEMS). PEMS is mounted on vehicles and can measure concentrations of several gases and particles in the exhaust [30]. PEMS has been supported by EPA and EU regulations for monitoring emission levels of non-­road machines. Compared to the in-lab engine test, results are considered closer to real-world operation conditions [28]. Studies like [31, 32] used PEMS to measure emissions of several non-road diesel mobile machinery in real work environments in comparison to emission standard thresholds. In all cases, emission levels measured with PEMS were higher than the thresholds. Telematics solutions offer alternatives to PEMS. PEMS technology is, however, expensive and large, weighting nearly 100  kg, which makes its installation complex and not practical [30]. For this reason, other board measurement systems have been gaining attention, such as the Smart Emissions Measurement System (SEMS). Reference [33] compared SEMS and PEMS when measuring NOx emissions in real driving conditions and found that emission values measured by both systems were highly similar. Reference [34] also presented and tested a small-scale sensor called Simplified Emission Measurement System (aka SEMS), which can measure emissions from vehicles in work environments. Despite being in its early stages of research, the adoption of the technology for measuring NRMM emissions was considered feasible.

3 Methodology This study aims to demonstrate a web-based application for integrating and visualizing emission data from NRMM in a construction site model. The application intends to display emission levels of NOx (gkW/h), PM (mg/m3), and CO2 (%) in different working areas over time. A dashboard displays graphs and heatmaps for each type of emission, showing values measured in each area, and, accordingly, highlights the threshold or any extension of the EU standard for comparison. A cloud-based development platform facilitates the integration of IoT data with a

8

L. M. Andrade and J. Teizer

Fig. 1  Simplified Emission Measurement System (SEMS) for data gathering (left) and flowchart for application development (right)

construction site information model. Existing BIM-tools and application programming interface (API) services assisted in developing a customized application. Sensor data from NRMM (Fig.  1, left image) collected in a previous study [34] assisted in the integration of data in the application. The realization of the proposed application consisted of five steps, as shown in Fig. 1 (right image), as described in the following.

3.1 Gathering Emission Data The starting point is gathering data from NRMM in operation, such as position, speed, temperature, pressure, fuel consumption, levels of O2, NOx, and particulate matter, among others. These can be collected in different ways, as explained earlier, such as installing Emission Measurement Systems (PEMS, SEMS, etc.) in the machine engine. Data measured by such systems are, in most cases, sent to computing devices owned by the system provider and stored in cloud databases, where processing occurs afterwards. A more detailed explanation of the data collection process is outside the scope of this paper. However, the emission data sample being used is explained in Ref. [34]. In brief, the data sample originates from a field test conducted with SEMS technology by Techno-Matic A/S installed in a Volvo wheel loader L90G (Stage III) performing different activities at a construction laydown yard in Aarhus, Denmark, in May 2021. Each data point collected at 1 Hz contains the parameters: timestamp, O2 (%), pressure (kPa), temperature (°C), NOx (ppm), and PM (mg/m3). A Global Navigation Satellite System (GNSS) adds the location, speed, and direction to every measurement.

3.2 Data Processing Raw datasets obtained from sensors are usually unfiltered and have no immediate value to users without processing. This involves cleaning, sorting, understanding, and transforming the data into useful formats. The purpose of this project’s

Web Application for Visualizing Emission Data from Construction Equipment

9

application is to show NOx (g/kWh) PM (mg/m3) and CO2 (%) emission values. Since the gathered data did not include CO2 values and NOx was given in ppm, thus, a few mathematical operations are necessary. CO2 (%) is calculated based on the O2 (%), and NOx values were converted from ppm into g/kWh using the formulas suggested in the study by Ref. [34]. Then, emission data from equipment is visualized in a web application. First, the site is (currently manually) divided into equally sized areas that have reference nodes in the respective centre of gravities. The nodes appear as grey circles in road intersections and accordingly, at locations that divide up longer straight paths that the equipment drove (Fig. 2). Python’s open-source library GeoPandas correlates all emission data points to the respective areas, which creates eventually a separate dataset for each node. Finally, the generated information is ready for application using database services such as Azure, MongoDB, or, in this case, local CSV files. The Forge APIs connect the datasets to the sensor devices (here: nodes that represent the (emission) areas in BIM).

3.3 Modelling Construction Site Layout The building information model of the construction site layout, created using Autodesk Revit 2022, is based on actual aerial images and spatial terrain data obtained from Google Earth Pro (containing latitude, longitude, and altitude values). Utilizing the QGIS software creates a CSV file that is imported into Revit, which automatically generates a topographical surface. This facilitated the seamless posterior integration with the equipment positioning data (of the same data format). As seen in Fig. 2, other elements located on the site, such as buildings, containers,

Fig. 2  Plan view of construction site layout model with equipment trajectory, separated, among other relevant site objects, into observation areas and corresponding nodes

10

L. M. Andrade and J. Teizer

and materials, were manually modelled as simple generic objects and for visualization purposes only. The IoT-BIM integration using the Autodesk Forge APIs depends on the inclusion of objects into the model that represent sensors. These objects contain specific parameters of identification and emission properties that are posteriorly mapped and connected to the data in the model. Even though there are no real fixed sensor devices on the site (only on the equipment), these need to be added to the Revit model by placing (virtual) nodes. This produces the function that a user later will call to select among the different areas and retrieve their emission values. A sensor device family with unique IDs for each area was created containing parameter types for CO2, NOx, and PM.  The areas are modelled as Room objects in Revit and named as (Area 1, Area 2, etc.). The Forge APIs obtain the room information from the corresponding model object, then map each of the given device objects into these rooms based on their known coordinates (position), and, finally, create heatmaps for each room that contains at least once device.

3.4 Setting Up the Application The application uses the Autodesk Forge cloud and API services and Visual Studio Code as the Integrated Development Environment (IDE). When registering the Forge platform, a user receives the client ID and password, the services necessary for the application development. This includes cloud storage and access to APIs for different purposes, e.g. (a) Viewer API to upload and render 3D models from several formats (IFC, RVT, NWC, etc.) within a browser and (b) the Data Visualization API to visualize custom data in models with sprites, heatmaps, and other features. While Forge APIs are available in several programming languages [23], this work uses JavaScript as development language and CSS and HTML for web page customization. In connection with the Data Visualization API, Forge provides the Hyperion Reference Application as an open toolkit to assist with integrating sensor data from different database services into a BIM model [23]. The Reference Application is only used as starting point in this work. A Node Package Manager (NPM) and Node.js are used to run the application. The environment configuration file is modified to include the Forge client’s credentials (ID, password, etc.) so the user’s custom models and data can be added. The upload of the building information model to the Forge cloud occurs through the upload.html file and the client’s credentials. Once the viewer visualizes the model, the process of integrating the data starts. First, the sensor devices previously modelled in Revit were identified in a device-­ models file, which describes the type of data measured (e.g. CO2, NOx, etc.) and properties such as units and range values, among others. The property types inserted here must match the properties of the device in the model. Secondly, all devices are listed in a devices file, with the IDs, names, and coordinates previously defined in the model.

Web Application for Visualizing Emission Data from Construction Equipment

11

The next step is adding the data. By default, application allows for Azure IoTHub or CSV files to be added as time series data sources. The CSV adapter is selected in the .env file of the application, and the properties of the dataset are defined. All CSV files are added to the server CSV folder. The name of the CSV files must match the unique IDs of the sensor devices, and the title of the data columns (e.g. CO2, NOX, etc.) must match the property types defined in the model and devices files. The final step is setting up the heatmap and other visual configurations. Room and device information as defined in the building information model are added to the heatmaps extension file. Other visual configurations, such as colours, visual aspects of graphs, etc., are also modified in the application’s CSS files.

4 Results The resulting web application is a viewer with a dashboard containing several features where the user can interact with the construction site model and visualize emission data through graphs and heatmaps. The application is currently accessed locally, but it can be deployed online as well, for example, using Heroku. Figure 3 and embedded markers show the application view and indicates its main elements described in this section. The BIM model can be navigated in the viewer using the mouse buttons, similarly to Autodesk software, or through the toolbar (marked with an “A”). A few functionalities of the toolbar are, e.g. choosing different camera

Fig. 3  Web-based application dashboard

12

L. M. Andrade and J. Teizer

perspectives, walking the model in first person, sectioning the model’s view, and drawing distance measurements. The model browser and properties buttons allow the user to find any element in the model and visualize all its BIM properties and information. Sensor nodes are indicated in the model through grey dots that, when scrolled over, show the last recorded data values in that area (“B”). The left buttons (“C”) allow turning the dots on and off and displaying a list of all sensors, highlighting their respective area in the model. The dashboard on the right (“D”) also displays a list of sensor areas with a search function. An area selected shows graphs of NOx, CO2, and PM emission levels over time. For NOx, a line in the graphs indicate the standard thresholds regulated by the EU (3.81 g/kWh for Stage III machine). Marker “E” shows NOx and CO2 graphs for Area 5, where NOx levels were above thresholds several times. A timeline located on the top (“F”) allows for visualizing data in different periods in time. This is mostly useful if the user wishes to see data from the past. Finally, heatmaps of emission measurements can be visualized in the model for each emission type. A gradient bar shows the range of values according to colour and contains buttons for alternating between heatmaps and time periods. Marker “G” links to a heatmap of NOx emissions in a period of 1 hour, where areas coloured in green have low values, yellow is near in the threshold, and red are levels above limit. It can be seen that most areas had exceeded levels (note: for reasons see Ref. [34]).

5 Conclusions This paper presented a web application as an initial concept for visualizing emission levels from heavy construction equipment on construction sites. Autodesk Forge was used to build the application, allowing the interaction of sensor data with the construction site layout model. Historical data from a previous study collected with a Simplified Emission Measurement System (SEMS) was processed again and used for validation. The application is able to show levels of CO2, PM, and NOx in different areas of the construction site over time, allowing a user to easily visualize graphs and heatmaps by interacting with the model. This work allows quick identification of areas of high emission levels compared to EU standard thresholds for NOx levels. Moreover, viewer functions such as the measurement of dimensions, model browsing, and element properties offer helpful tools for easy access to and understanding of relevant information. Overall, this work proved to be effective in building an application that integrates and visualizes IoT data with BIM, but the adopted method has several shortcomings:

Web Application for Visualizing Emission Data from Construction Equipment

13

1. The study was limited to visualizing data from one construction equipment only. The usability of the application when connecting data from different types of equipment (see example in Ref. [35]) simultaneously needs to be further explored. 2. The method found for now processes the historical data only. Additional research is needed to scale the method of processing the data in run time. 3. The method shows data from moving equipment utilizing fixed virtual sensors, meaning that sensor devices were strategically added to the model, even though they do not exist on the actual site. Ideally, a run-time visualization is able to show dynamic sensors without the need to model them in fixed places. This is currently not possible in Forge and its APIs. Nonetheless, this first-of-a-kind study confirms the possibility and usability of analysing and visualizing emission data from SEMS installed on construction equipment in a BIM-based real-time data visualization environment. The integration of IoT and BIM is essential for developing useful DTs for the construction purposes. Progress in this field will eventually lead to fully operational DTs that will help monitor, predict, and reduce emissions in live construction activities due to, for example, improvements in equipment operator behaviour or temporary modification of site logistics.

References 1. World Business Council for Sustainable Development (WBCSD). Net-zero buildings Where do we stand? (2021), https://www.wbcsd.org/contentwbc/download/12446/185553/1 2. European Union. Communication from the Commission to the European Parliament and the Council on the European Green Deal (2019), https://eur-­lex.europa.eu/legal-­content/EN/TXT/ ?uri=COM%3A2019%3A640%3AFIN 3. European Commission, Directorate-General for Research and Innovation. EU missions: 100 climate-neutral and smart cities (2022), https://data.europa.eu/doi/10.2777/191876 4. M. Kaur et al., The convergence of digital twin, IoT, and machine learning: transforming data into action, in Digital Twin Technologies and Smart Cities. Internet of Things, ed. by M. Farsi, A. Daneshkhah, A. Hosseinian-Far, H. Jahankhani, (Springer, Cham, 2020), pp. 3–17. https:// doi.org/10.1007/978-­3-­030-­18732-­3_1 5. S. Tang et al., A review of building information modeling (BIM) and the internet of things (IoT) devices integration: Present status and future trends. Autom. Constr. 101, 127–139 (2019). https://doi.org/10.1016/j.autcon.2019.01.020 6. A. Schweigkofler et al., Digital Twin as energy management tool through IoT and BIM data integration, in CLIMA Conference 2022 (2022), https://doi.org/10.34641/clima.2022.46 7. J.  Teizer, M.  Wolf, O.  Golovina, M.  Perschewski, M.  Neges, M.  König, Internet of Things (IoT) for integrating environmental and localization data in Building Information Modeling (BIM), in 34th International Symposium on Automation and Robotics in Construction (2017), https://doi.org/10.22260/ISARC2017/0084

14

L. M. Andrade and J. Teizer

8. N.D.  Bokde, K.W.  Johansen, S.  Wandahl, J.  Teizer, A Digital Twin framework for emissions from construction site operations, in 21st International Conference on Construction Application of Virtual Reality (CONVR), Middlesbrough, UK (2021), pp. 31–42 9. A. Relekar, P. Smolira, E. Petrova, K. Svidt, Enabling Digital Twins with advanced visualization and contextualization of sensor data with BIM and web technologies, in Proceedings of the 38th CIB W78 conference on Information and Communication Technologies for AECO, 11–15 October 2021 (2021) 10. International Organization for Standardization. Internet of Things (IoT): Preliminary report ISO/IEC JTC 1 (ISO/DIS Standard No. 45001) (2015) 11. J. Teizer, D. Lao, M. Sofer, Rapid automated monitoring of construction site activities using ultra-wideband, in 24th International Symposium on Automation and Robotics in Construction (2007), pp. 23–28, https://doi.org/10.22260/ISARC2007/0008 12. B.  Dave et  al., Opportunities for enhanced lean construction management using internet of things standards. Autom. Constr. 61, 86–97 (2016) 13. Y. Gamil et al., Internet of things in construction industry revolution 4.0: Recent trends and challenges in the Malaysian context. J. Eng. Des. Technol. 18, 1091–1102 (2020). https://doi. org/10.1108/JEDT-­06-­2019-­0164 14. R. Sacks, C.M. Eastman, P. Teicholz, G. Lee, BIM Handbook: A Guide to Building Information Modeling for Owners, Designers, Engineers, Contractors, and Facility Managers, 3rd edn. (Wiley, 2018) ISBN: 978-1-119-28755 15. C. Boje, A. Guerriero, S. Kubicki, Y. Rezgui, Towards a semantic Construction Digital Twin: Directions for future research. Autom. Constr. 114, 103179 (2020) 16. BuildingSMART International. Enabling an ecosystem of digital twins. (2020) [Online] 17. F. Tao et al., Digital twin-driven product design framework. Int. J. Prod. Res. 57, 3935–3953 (2019). https://doi.org/10.1080/00207543.2018.1443229 18. M.  El Jazzar et  al., Digital Twin in construction: An empirical analysis, in EG-ICE 2020 Workshop on Intelligent Computng in Engineering, Berlin (2020) 19. V. Villa et al., IoT open-source architecture for the maintenance of building facilities. Appl. Sci. 11, 5374 (2021). https://doi.org/10.3390/app11125374 20. Q. Vivi et al., Developing a dynamic digital twin at a building level, in International Conference on Smart Infrastructure and Construction 2019, ICSIC 2019: Driving Data-Informed Decision-­ Making (2019), https://doi.org/10.1680/icsic.64669.067 21. C.M. Lee et al., Government open data and sensing data integration framework for smart construction site management, in Proceedings of the 36th ISARC, Banff, Canada (2019), https:// doi.org/10.22260/ISARC2019/0169 22. IBM. IaaS versus PaaS versus SaaS (2021), https://www.ibm.com/cloud/learn/iaas-­paas-­saas 23. Autodesk. Forge developer documentation (2022), https://forge.autodesk.com/ 24. H. Jassim et al., Predicting energy consumption and CO2 emissions of excavators in earthwork operations: An artificial neural network model. Sustainability 9, 1257 (2017) 25. F. Shahnavaz, R. Akhavian, Automated estimation of construction equipment emission using inertial sensors and machine learning models. Sustainability 14, 2750 (2022) 26. A.  Lajunen et  al., Overview of powertrain electrification and future scenarios for non-road mobile machinery. Energies 11(5), 1184 (2018). https://doi.org/10.3390/en11051184 27. European Union. Regulation (EU) 2016/1628 of the European Parliament and of the Council of 14 September 2016 on requirements relating to gaseous and particulate pollutant emission limits and type-approval for internal combustion engines for non-road mobile machinery (2016), https://eur-­lex.europa.eu/legal-­content/EN/TXT/?uri=CELEX:32016R1628 28. B. Hong, L. Lü, Assessment of emissions and energy consumption for construction machinery in earthwork activities by incorporating real-world measurement and discrete-event simulation. Sustainability 14, 5326 (2022). https://doi.org/10.3390/su14095326 29. B.  Heidari, L.C.  Marr, Real-time emissions from construction equipment compared with model predictions. J. Air Waste Manage. Assoc. 65, 115–125 (2015)

Web Application for Visualizing Emission Data from Construction Equipment

15

30. S. Sato et al., Real-world emission analysis methods using sensor-based emission measurement system. SAE Technical Papers (2020), https://doi.org/10.4271/2020-­01-­0381 31. P. Bie et al., A review and evaluation of nonroad diesel mobile machinery emission control in China. J. Environ. Sci. 123, 30–40 (2022). https://doi.org/10.1016/j.jes.2021.12.041 32. R. Tu et al., Real-world emissions of construction mobile machines and comparison to a nonroad emission model. Sci. Total Environ. 771, 145365 (2021) 33. Y.S. Yu et al., NOx emission of a correlation between the PEMS and SEMS over different test modes and real driving emission. Energies 14, 7250 (2021) 34. J.  Teizer, S.  Wandahl, Simplified emissions measurement system for construction equipment, in Construction Research Congress 2022, (American Society of Civil Engineers, 2022), pp. 474–482. https://doi.org/10.1061/9780784483961.050 35. A. Artenian, F. Sadeghpour, J. Teizer, Using a GIS framework for reducing GHG emissions in concrete transportation, in Proceedings of the Construction Research Congress, Banff, Canada, May 8–11, 2010 (2010), pp. 1557–1566, https://doi.org/10.1061/41109(373)156

Transforming the Civil Engineering Surveyor Andrew Evans, Genna Rourke, Ivor Barbrook, Ian Heaphy, Abigail Tomkins, Marek Suchocki, Sangeetha Senthil Kumar, and Matt Haigh

1 Introduction 1.1 Embracing Digital Engineering and Information Management Digital transformation is key to delivering a construction industry that is fit for 2050 and beyond. In this paper, the Chartered Institution of Civil Engineering Surveyors (CICES) considers the changing nature of the surveying professions amid the development of digital engineering, encompassing information management, data sharing and building information modelling (BIM) during the full infrastructure asset lifecycle.

A. Evans Digital Construction Works, Chester, UK G. Rourke Costain, Maidenhead, UK I. Barbrook BAM Nuttall Ltd, Camberley, UK I. Heaphy IN Construction Consulting, Huddersfield, UK A. Tomkins · M. Haigh (*) Chartered Institution of Civil Engineering Surveyors, Sale, UK e-mail: [email protected] M. Suchocki Autodesk Ltd, London, UK S. S. Kumar Balfour Beatty, Woking, UK © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 F. Gaspar, A. Mateus (eds.), Sustainable and Digital Building, https://doi.org/10.1007/978-3-031-25795-7_2

17

18

A. Evans et al.

The pace of technology development, particularly artificial intelligence, machine learning and data management, means surveying roles will change, requiring different skills on top of those honed in their rich history of being the key suppliers and curators of geospatial information throughout the civil engineering plan of work. All the engineering professions are facing change, some more than others. The UK government mandate for the use of BIM on all centrally procured projects by 2016 instigated change in many contractors and consultancy firms. The ‘BIM4’ groups sprang up under the BIM Task Group and the BS1192 series of standards developed as the precursor to the international BS EN ISO 19650 series we have today. Throughout these early days, the challenge lay in demonstrating the relevance of information management to surveyors. Geospatial surveyors have witnessed lost opportunities because of a lack of awareness of their expertise and understanding of location data and data capture methods. Commercial managers have faced new ways of working using software platforms that they could not interact with to reflect the true progress on a project, which has exacerbated the ‘silo mentality’ information management has tried to counter. Two factors since 2016 have accelerated the pace of digital transformation. The first is the growing awareness of climate change and the commitments that governments globally are making to mitigate its effects in a timeframe of just a few decades. The second is the COVID-19 pandemic which led to an increase in digital communications, reduced site visits and brought remote technologies such as automated monitoring and drone (also known as unmanned aerial vehicles/UAV, or small unmanned aircraft/SUA) progress reporting to the fore. ‘Agility’ and ‘pivot’ have become terms that businesses take pride in achieving. The information management trailblazers of the 2010s are now sharing their successes and lessons with their supply chains. The remit of the BIM Task Group was taken forward by the Centre for Digital Built Britain and now by the Construction Innovation Hub, British Standards Institution and UK BIM Alliance, within the UK BIM Framework. The National Digital Twin Programme is underway, with the underground currently being digitally mapped through the National Underground Asset Register (NUAR). The Centre for the Protection of National Infrastructure has been engaged to protect all that is digital in the digital twin, demonstrating that data about infrastructure is as critical as the infrastructure itself and is supporting the development of a standard interoperable approach to asset information through the Government & Industry Interoperability Group (GIIG). The pace of change shows no sign of slowing. As emerging technology drives surveyors to acquire new capabilities and competencies, their expertise is essential in realising the efficiencies of digital engineering. In 2021, CICES supported the global study Accelerating Digital Transformation Through BIM [1]. The study showed that 70% of civil engineers have adopted BIM since 2016, demonstrating the rapidly growing use of information management for infrastructure work. Contractors deploying information management on at least 50% of their projects reported significant benefits in areas such as bid efficiency,

Transforming the Civil Engineering Surveyor

19

fewer defects, cost control, forecast accuracy, schedule control, reduced rework and fewer on-site challenges. CICES was established in 1969 and has as its Latin motto, omnia metimur quae videmus, we measure all that we see. The fashion for having a Latin motto may have gone, but the principle is relevant today and will be in 2050 and beyond. Measurement equals accuracy. Accuracy equals efficiency. Transforming the civil engineering surveyor simply reshapes that function for the future. Key to this transformation is a better understanding of the expertise of geospatial engineers and commercial managers and how they can inform decision-making on infrastructure projects. This paper recommends a shift in the traditional timing of when civil engineering surveyors are engaged in projects, identifying that they will have more impact in the planning phase. Knowing what data will be needed when and to what accuracy and how this data will be used in scenario planning, costing, scheduling and monitoring will realise efficiencies and make full use of the surveyor’s expertise. While the majority of papers and initiatives referred to in this paper are from the UK, digital transformation of civil engineering surveying is global. We recognise that each country faces its own unique challenges and hope that lessons learned and shared here will benefit our colleagues overseas.

2 Perceptions and Purpose Throughout the Phases of a Project Transforming the civil engineering surveyor also means transforming the perception of the civil engineering surveyor. Better understanding of the expertise of geospatial surveyors and commercial managers and how they can inform decision-making at all phases of a project is a relatively simple step that can have a large impact. For geospatial surveyors this was an issue tackled in 2016 by Survey4BIM [2], a specialist group under the UK government’s BIM Task Group umbrella. Survey4BIM published Survey and the Digital Plan of Works [3] to address a gap in the published UK BIM Level 2 standards for the role and responsibilities of the surveyor. The guidance followed a series of eight (0–7) work phases broadly aligned to those within PAS1192-2:2013 describing survey activities and recommendations for each phase. The past few years has seen the move to the UK BIM Framework [4]. The framework is intended to be applicable to all types of appointment and project, under any procurement route and for all participants. Consequently, it has framed guidance around a simplified set of phases focused on information management: design, build, operate and integrate.

20

A. Evans et al.

2.1 Design, Build, Operate, and Integrate The role of the surveyor within the UK BIM Framework remains critical to correctly specifying geospatial requirements at the outset of a capital delivery project to how survey data is used in asset operation and connected to other datasets. Obligations within the UK BIM Framework are described as: • Design: Where digital techniques are deployed to design better performing infrastructure. Information management should be secure by default and managed in a way that gets data right from the start. • Build: Where new and emerging digital construction and manufacturing technologies, processes and techniques should be exploited. Secure, shared information should enable clients, design teams, construction teams and the supply chain to work more closely together to improve safety, quality and productivity during construction. • Operate: Where real-time information should be used to transform the performance of the built environment and its social and economic infrastructure. Smart asset management should predict and avoid disruption of services, while existing assets and infrastructure should be digitalised. • Integrate: Where it is understood how spaces and services can improve quality of life. That information should be fed into the design and build of economic and social infrastructure and the operation and integration of services they deliver. These phases are entirely applicable to the surveyor, whose role in the project and asset lifecycle needs to be better appreciated and integrated. The obligation of the surveyor is to align to standardised information management processes, identify and embrace appropriate technologies and commit to trusting the data they receive from other participants. The risk-averse nature of the construction sector, reliance on inefficient legacy procedures and limited investment in technology and people need to be retired in order for effective change to happen.

2.2 Geospatial Considerations By considering the standards and guidance for the phases within the UK BIM Framework, coupled with the still applicable recommendations in Survey and the Digital Plan of Works, geospatial surveyors can better demonstrate the criticality of their role in the asset lifecycle and ensure their data needs and outputs are integral to successful project outcomes. Information management solutions and processes have become familiar to many professionals and organisations over the past few years. Moreover, the pace of technology innovation has introduced new solutions and opportunities to increase productivity, improve quality and challenge traditional thinking. For example, surveyors are able to undertake unmanned aerial surveying, set out directly from models,

Transforming the Civil Engineering Surveyor

21

leverage sensor data for real-time information, drive machinery remotely and many other options to improve their work and collaboration with other project participants. The Transforming Infrastructure Performance: Roadmap to 2030 (TIP) [5] from the Infrastructure and Projects Authority notes that there are technical capabilities that are not yet being asked for or applied on government projects. It particularly highlights 5G networks, artificial intelligence, wireless sensors, monitoring, fixed and mobile sensors, photogrammetry, 3D laser scanning robotics and augmented reality and calls for improvement and acceleration of their adoption. Such innovations need to be introduced with consideration for the value they bring to a project and wider downstream operational and service provision. Technology for technology’s sake is not worth adopting without both a resulting material improvement and an assurance of no unintended negative consequences. The geospatial surveyor is the expert on this technology and as an appointed consultant will be able to advise on the most appropriate technology and data requirements for every stage of the project. The geospatial surveyor can assist in the specification of requirements, advise on where coordination is missing and what is required and plan how information quality will be developed over the design, construction, handover, operation, maintenance and decommissioning of an asset. The emergence of geospatial project execution plans shows that with the right data capture and management methods in place, other project team members can focus on their specialist contribution, using technology as an enabler, not a distraction.

2.3 Commercial Management Considerations The commercial manager and quantity surveyor roles are transforming to ones of proactive data management to drive value and monitor project progress. The TIP highlights the increasing use of information management as a planning tool to coordinate construction to a critical path and undertake clash detection in line with resource management, capacity planning and scheduling. Taking this further to cost modelling, some software already has the capability to incorporate costed components and materials in the information model, alongside linked availability and access. This can then drive bills of quantities and optimise resources whether work is on site or during offsite manufacturing. The key message in TIP is that embracing information management and a multidimensional approach starts in the planning phase with highly detailed information and better integration that can then inform the work packages. By establishing the core contribution of the commercial team early and with regular engagement throughout the project to ascertain how data can be used to drive efficiencies, the data measurement role of the commercial civil engineering surveyor can be fully exploited. As cost modelling becomes more mainstream, now is the time for

22

A. Evans et al.

commercial surveyors to reaffirm the key role they play in ensuring project efficiencies, with a focus on data and value, as well as cost.

2.4 Planning: All About Timing The timing of when to engage a surveyor needs to be rethought. Early engagement with both commercial managers and geospatial engineers is key to releasing efficiencies. The first step is to determine what data the project needs throughout its lifecycle. Engage Early, Plan for Life  Engineering surveyors are often called to provide professional services within a very narrow window of requirements by the project stakeholders to meet an immediate need. However, by working with clients, as an appointed consultant, they are best placed to specify, procure and manage geospatial information throughout the planning phase through to operation of an asset. This holistic approach enables clients and appointed parties access to geospatial information at an appropriate level of need in the lifecycle of the project. The geospatial engineer is a custodian of location data. This kind of data has until now been managed in appointed party silos through the phases of an asset’s lifetime. Geospatial information needs to be managed through a balanced and structured approach throughout each phase. Engaging a geospatial engineer as an appointed consultant is key to unlocking the transformation from individual stakeholders managing and setting their own requirements for geospatial information to a collective plan of project needs embracing specification, collection, added value and handover of geospatial data between stakeholders. This adds value to design integrity and provides as-built information to aid and inform asset management and monitoring. Survey4BIM’s Survey and the Digital Plan of Works [3] can help pinpoint what survey data is essential at what stage of a project and is a useful resource when commissioning and planning geospatial data requirements. Ask and You Shall Receive  Our focus groups revealed some commercial managers still struggle to see the benefit of information management. One quantity surveyor commented: ‘The 3D models I’m told to use present a pretty picture but the data behind them is often unusable’. The perception persists that planners and BIM managers provide data they think the commercial team needs without talking to them first. This can lead to mistrust and the contractor’s commercial team commissioning its own data and working on that independently in a silo. To get over this mismatch of presumed usage and actual take-up, a combined data/commercial cost plan is needed. Monitoring integrated cost models, data levels and reports needs to be a key activity on the programme, with all involved responsible for driving it forward.

Transforming the Civil Engineering Surveyor

23

Commercial teams have to step up in adopting new work practices that leverage the opportunities from information management. Reliance on traditional trusted, but actually inaccurate, methods has to go, or the efficiencies of digitalisation will never be realised. Within a project controls team, this shift is naturally facilitated, but on smaller projects where commercial, planning and design teams sit separately, it is imperative that these teams no longer see each other as stumbling blocks. The commercial management team should be fully engaged and asked at the start what their information requirements are and how they need to see information presented. By integrating commercial, planning, design and BIM specialists – or at the very least, having weekly interdisciplinary meetings – information requirements can be clear from the outset and processes around sharing and management defined. When data and information deliverables are agreed, they should be recorded in task information delivery plans. These are amalgamated into a master information delivery plan, together with the geospatial project execution plan encompassing the data requirements, and the technologies it has been agreed will manage the process. This will provide a foundational framework to maximise data efficiencies. Skills – Custodians of Accuracy  Engineering knowledge is no longer a prerequisite to working in construction. Data analysts, information managers and gaming/ visualisation specialists are increasingly regular appointments. These new roles work hand in hand with surveyors, and the skills of each should complement each other in the digital engineering team. The Construction Innovation Hub’s Digital Capabilities: A Framework for early career professionals across built environment disciplines1 set out six digital capabilities required in construction: • • • • • •

Data collection and instrumentation Information management Data interpretation and analysis Data governance Data visualisation Software development

The current civil engineering surveyor could lay claim to involvement in the first five of those six, with many contributing to all six with their involvement in software development through bespoke systems and early adopter relationships with developers. While project teams do not centre their career on software development, they have to embrace new technology as a digital capability. The skill set of the commercial manager in particular is in danger of not developing in line with the systems being used and not fulfilling the potential it has to transform projects. For the geospatial surveyor, the fast pace of technological development over the last half century has resulted in an agile profession at remarkable ease with new tools. However, its chief concern is the lack of entrants to the profession.

24

A. Evans et al.

New Skills  The commercial manager and quantity surveyor roles are transforming. Commercial and planning teams are increasingly coming together under the joint banner of project controls. They no longer stand in silo functions; this is about bringing together their expertise to give a full picture of a project’s health and progress. While measuring cost continues to be a key commercial role, especially in the post-pandemic and post-Brexit UK, this is just a part of one of the capitals that need to be measured under the UK government’s focus on value. The Value Toolkit [6] from the Construction Innovation Hub aligns with HM Treasury’s Green Book [7], against which public sector investment decisions are made. Value is measured over four capitals: • Natural capital: valuing the natural environment and addressing solutions to climate impacts • Social capital: valuing engagement and consultation, equality and diversity and the positive impact of the built asset on society • Human capital: valuing employment opportunities and skills development • Produced capital: valuing a combination of capital cost, operational cost and revenue, taking a whole-life approach to efficiency and quality of design, construction and operational processes The commercial manager is a specialist at measuring produced capital. Transformation will involve acquiring skills in measuring the other three capitals as well. Clients have to think differently about their long-term plans. Balancing affordability and the four capitals will naturally change tender specifications. This shift is a challenge, and the Construction Innovation Hub recognises that it ‘demands considerable rigour in defining the outcomes to be delivered and understanding the client’s approach to project delivery and risk’.4 Again, success will lie in early and regular engagement between the commercial, design and planning specialists.

2.5 Tackling a Skills Shortage: The Role of CICES When looking at skills in civil engineering surveying, one has to consider both the shortage of digital skills in the current surveyor and the shortage of skilled new surveyors. As a professional qualifying body, CICES has a role to play in addressing both issues. For new entrants, CICES needs to ensure it continues its collaboration with organisations involved in schools engagement, including Construction STEM Ambassadors, Get Kids into Survey and Class of Your Own (the organisation behind the Design Engineer Construct! curriculum). CICES must maintain its involvement with steering groups for the Geospatial Survey Technician, Geospatial Mapping and Science Specialist, Construction Quantity Surveying Technician and Construction Quantity Surveyor apprenticeships and build on its successful university

Transforming the Civil Engineering Surveyor

25

accreditation programme. Involvement with the Construction Leadership Council Skills Plan is a necessity to avoid a fragmented approach to career promotion. The image of the surveyor as ‘data custodian’ needs to be better promoted. Protocols and standards focus on quality process, while surveyors focus on quality data – this and the technology and expertise required to capture and define quality are rarely recognised by the wider project team and almost never in schools’ careers departments. Civil engineering surveying is rightly proud of its openness to all as a career. Many industry leaders talk about joining the construction industry straight from school and progressing to attain company directorships with professional, rather than academic, qualifications. Historically, construction is seen as a male-oriented career, and with CICES female membership sitting at just over 10%, CICES has a duty to build on that socially mobile heritage and ensure that the profession is open to a diverse range of talent. CICES plays a vital role in linking industry requirements with education and apprentice providers. For this to be effective, course accreditation and re-­ accreditation need to reflect the digital astuteness necessary for civil engineering surveying. As this area develops and the standards around it grow, regular engagement between professional and academic institutions is crucial. To upskill its existing membership, CICES has already committed to embedding digitalisation within its membership competencies. However, the award of membership is a point in time. Professional bodies need to look at how they engage existing qualified members to upskill through their continuing professional development requirements. The Construction Innovation Hub calls on professional bodies to develop a common understanding of sector-wide core digital capabilities and to work with members to determine what digital capabilities they need in their work.5 Answering this call rests with both individual institutions and the UK BIM Alliance, whose Affiliates Programme can assist in providing a forum for professional bodies to share experiences and best practice. Professional bodies should be ‘safe spaces’ for the sharing of lessons learned and mistakes overcome in digital transformation. Members need to be aware of their own professional accountability to upskill and should be encouraged to assess their own digital maturity to gauge where they need further development. CICES and other professional bodies need to play a nonjudgmental role in signposting to further information and knowledge banks, providing time for discussion at events – rather than rushing Q&A at the end of webinars and seminars  – and they must promote support from specialist technical committees and regions.

3 Data: Navigating a New Currency The Construction Playbook [8] stresses that: ‘A critical success factor for the effective completion and transition of a project or programme is the sharing of high-­ quality, robust data and information between parties during the project lifecycle and

26

A. Evans et al.

into operation’ [3]. A few years earlier in 2018, the Gemini Principles [9] around data sharing for the forthcoming National Digital Twin valued this assumption, stating that greater data sharing could release an additional £7bn per year of benefits across UK infrastructure, which is equivalent to 25% of total spend [9]. Establishing protocols and processes around data sharing is essential for the transformation of construction. While data sharing practices have yet to be fully established and normalised, they will happen  – and civil engineering surveyors should be enacting best practice and ensuring their continuing professional development factors in skills in data management. While protocols and standards focus on quality processes, surveyors focus on quality data and therefore are natural leaders in managing and specifying data requirements.

3.1 The Information Delivery Lifecycle Information is developed and built up through the lifecycle of a project, commonly referred to as the digital plan of work (DPoW). The unified CIC/APM digital plan of work consists of eight generic stages: • • • • • • • •

Strategy Brief Concept Definition Design Construct and commission Handover and close-out Operation and end of life

The level of information need (formally known as the ‘level of definition’) is defined for each stage gateway and is the aggregate of level of detail and level of information. The ‘level of detail’ is the description of graphical content required to address the decisions at each stage gateway. And the ‘level of information’ is the description of non-graphical content required for this. As information progressively develops at each stage throughout the project delivery, it collectively forms the Project Information Model. The graphical representation may not change at each stage, but ‘information’ will be added at each stage. For example, at concept stage graphical detail may look very realistic but spatially inaccurate, plus information is likely to be low grade with a lot of unknowns, whereas at handover and close-out, graphical detail will accurately reflect the as-­ built position of the works, and information delivered will be sufficient to maintain and operate it. The production and delivery of information on a project is assigned to specific Task Teams (Disciplines)  – for example, civil, mechanical and electrical. These

Transforming the Civil Engineering Surveyor

27

‘own’ the information they are responsible for producing, and only they can create or edit that data. All information, regardless of the work stage it is developed at, can be assigned one of three states: • Work-in-progress (the only state in which files can be edited by the discipline/ task team that ‘owns’ that output) • Shared (noncontractual, used for collaboration) • Published (contractual  – such as client deliverables or instruction to fabricate or build) The work-in-progress state is used for information while it is being developed by its task team/discipline. Information in this state is not visible or accessible to any other discipline. When the discipline is ready to share its information, it must pass through a check, review and approval workflow and is given a status code (often referred to as a suitability code). This is necessary so the receiving party can have confidence in the information shared and has some understanding of the purpose for which it was shared. The status codes that can be assigned are: • S1: suitable for geometrical and/or non-geometrical coordination within a delivery team • S2: suitable for information or reference by other disciplines within a delivery team • S3: suitable for review and comment within a delivery team • S4: suitable for review and authorisation by a lead appointed party • S5: suitable for review and acceptance by an appointing party (client) The purpose of the shared state is to enable constructive and collaborative development of the Information Model within a delivery team. When a discipline promotes information to the published state, it must pass through a further review and authorisation workflow. The published status codes assigned – A0, A1, A2, A3, A4, A5, A6 and A7 – all indicate the stage gateway of the digital plan of work they refer to. The information at shared and published states is visible and accessible by other disciplines within a delivery team but is not editable by them. If the information requires editing, it is returned to the work-in-progress state for amendment and resubmission by the discipline that owns it. This process of information development and exchange is defined by BS EN ISO 19650-2:2018 and is undertaken within a common data environment (CDE). A CDE is the single source of information for a project, used to collect, manage and disseminate all relevant project information through a managed process. A critical function of the CDE is to provide a clear and secure audit trail or journal of all changes and amendments to that information, including who created it, who read it, who edited it, who shared it (and for what purpose), who checked and reviewed it, who approved it, who authorised it to be ‘published’ and when all these activities took place.

28

A. Evans et al.

At the end of Stage 6, the as-built information represents the as-built asset in content and dimensional accuracy and is submitted to the client for acceptance, along with the commissioning and handover documentation. The complete PIM is handed over at the end of the project and culminates in the transfer of relevant information from the PIM to the asset information model (AIM), for use in asset management and potentially within a digital twin. Leading up to this state of high-quality and robust information requires a careful and structured approach, which includes adherence to strict processes and standards and an element of risk management.

3.2 Standards and Standardisation The UK government’s National Data Strategy [10] of December 2020 stated that while the standards were ‘well recognised’, SMEs generally do not use information management. The key hurdles to be overcome included software licensing and cost, lack of in-house training and skills, interoperability, a perception that BIM was only for larger construction projects and a lack of demand from clients. Since then, the Construction Playbook has clearly set out to ensure that client demand is there (at least in the public sector), the Government and Industry Interoperability Group (CIIG) has been established to support interoperability, software houses and market forces are addressing licensing costs and training is filtering through the supply chain from the major contractors. Perception will change in time, and professional bodies have a role to play in providing learning opportunities around specification requirements and standards and the importance of a balanced and structured approach to data management throughout the lifetime of an asset. Standardisation of data is necessary for collaboration. The Construction Playbook is very clear about government expectations of contractors around data management, explicitly saying they should use the UK BIM Framework to standardise the approach to generating and classifying data, data security and data exchange and to support the adoption of the Information Management Framework and the creation of the National Digital Twin. Naming protocols for information containers for objects and layers should be established early in a project and align to the needs of the client. It is imperative that these requirements are communicated to the project delivery team via the BIM Execution Plan (BEP) and that everyone adheres to them. The Geospatial Commission uses FAIR terminology [11] to assess the fitness for purpose of data, with data that is: • • • •

Findable Accessible Interoperable Reusable

Transforming the Civil Engineering Surveyor

29

The term Q-FAIR is also used by the commission and adds ‘quality’ to the data ideal. Civil engineering surveyors – both commercial and geospatial – should keep the Q-FAIR principle in mind when commissioning, capturing and managing data. The role of the surveyor in determining quality is key to the success of projects and will cover the currency, accuracy level, verification and suitability of data – addressing concerns around how much the data can be trusted and how it will be used with other data. This relates to the ‘level of information need’, which might require a higher level of detail and accuracy at DPoW Stage 4 (detail design), than at DPoW Stage 2 (concept design), for example. Another initiative that will aid data standardisation is the International Cost Measurement Standard (ICMS) [12]. ICMS provides a high-level structure and format for classifying, defining, measuring, recording, analysing and presenting lifecycle costs and carbon emissions associated with construction projects. CICES is one of 49 global bodies in the coalition steering the development of the standard.

3.3 Sharing Securely Geospatial surveyors should be mindful of the adage, capture once, use many times. The geospatial project execution plan should be developed as part of early engagement with the client and address what existing data is known about and available and ensure that new data capture is carried out with the whole project lifecycle in mind. The potential for sharing data in future projects needs to be addressed in the contract. The surveyor is best placed to comment on how the data could be used in future projects for other clients. Surveyors have access to a huge range of data and need to be mindful of their responsibility to keep that data secure, especially on national infrastructure projects. Clients will increasingly specify data security requirements, such as Cyber Essentials [13] accreditation, in tender documents. The Centre for the Protection of National Infrastructure (CPNI) has a wealth of guidance material on developing a security-­ mindedness approach [14] and assessing the security of data management systems. The National Cyber Security Centre (NCSC) has developed guidance on cybersecurity for construction businesses [15]. For underground utility surveys, the cross-­ industry-­endorsed Secure Data Management for Utility Surveys [16] published by CICES is also useful.

3.4 Facing the Risks Data sharing can appear highly risky to those whose careers have been shaped though the traditional adversarial culture of construction. This leads to a reluctance to share between stakeholders, particularly where added value has been embedded based on personal judgments and interpretation of information.

30

A. Evans et al.

Further work needs to be carried out to determine the most effective processes for data validation. Currently, the recipient of data expects it to have been validated by the sender. However, there is a chain of thought that turns the table on this expectation and recommends that the recipient verifies the data it receives. Recipient verification transfers risk from the sender and has a commercial implication around who is paying for verification and the actions that may need to be managed stemming from the outcome of verification and any resulting change management. This model is outlined in the Construction Playbook where in a list of dos and don’ts, one is: ‘Don’t… hold incoming suppliers responsible for errors in data (excluding forecasts) where they are unable to complete due diligence. Where data turns out to be incorrect, there should be a contractual mechanism for reflecting this adjusting for errors’ [17]. However data validation is carried out, the process should be collaborative with a structure in place to notify parties of any discrepancies and clashes. Who is in charge of the truth and when needs to be thought about right at the start of a project. In the Construction Playbook, the second step in the delivery model assessment for public works projects and programmes is to identify data inputs. This sits right after framing the challenge of what type of sponsor and governance approach is being taken and before considering the delivery model. With data thought about early and often and an accurate and reliable pipeline of information flowing through a project, the natural progression is to put it to further work. Good data should be used as a benchmark to aid decisions in forthcoming projects. Ensuring the quality of this data as it is used in future evaluation is a further role where the skills of the commercial manager will be beneficial. Machine learning programs are already being used by public sector clients to manage risks on mega-projects by assessing historical data. As machine learning and AI become more developed and familiar tools, this kind of analysis will become more common. We Cannot Not Share  Open data initiatives, where non-sensitive data is made available without constraint for transparency, engagement and innovation purposes, are increasingly encouraged by the UK government. Surveyors need to take care that legal and security liabilities are considered when sharing data for the public good. Commercial barriers to data sharing were addressed in Data for the Public Good [18] from the National Infrastructure Commission in December 2017, where perceived commercial risk was studied under the glare of overall industry efficiencies. Putting it simply, the report stated that: ‘By refusing to share data, a private company or organisation keeps control of that data as it grows… as the volume of data increases and machine learning techniques are applied, the quality of the data improves and so becomes more valuable. Thus there are increasing returns to data, which if retained in the private sphere, will remain as narrow returns to the private company rather than wider returns to the economy as a whole’ [19]. Professional civil engineering surveyors are bound by the royal charter that governs them to benefit society. That narrow view of protecting commercial returns has to widen.

Transforming the Civil Engineering Surveyor

31

4 Contracts and Protocols: Carefully Enabling the Digitalisation Journey Contracts should enable, and not constrain or conflict, with the digitalisation journey. Data sharing and collaboration need to be carefully supported. This can be addressed either through conditions of contract or dealt with in a protocol that overlays contracts. Data takes the form of outputs and deliverables identified as part of the scope of works or service that the supplier is to provide, the format in which it is to be provided and when. Data will in many ways be the same as any other deliverable under the contract; however, there are issues that need to be considered due to the fact digital information will be shared with others and combined and developed in an integrated or federated information model. The timing of information releases, the liability and responsibility for the information provided and the development and use of this in an integrated or federated model have to be thought about carefully. Ultimately, the end product will be a model that combines information provided by the parties that the client will use to manage the completed asset. In order for the information model to meet the client’s overall requirements, there will be a need for each party to have a guiding hand on its development, following requirements which may need to change as the project develops. There may be clashes with the requirements in individual biparty contracts, and commercial managers should be prepared for this. Traditional biparty contracting creates a hierarchical structure with risk and responsibilities split across the different parties, including responsibility for the creation, sharing and development of data which can be ultimately used in an information model. This way of contracting creates multiple interfaces that need to be effectively managed. However, due to the individual allocation of risk to each party, the approach can drive a silo mentality in which each party seeks to protect its own position, instead of collaborating on the basis of what is best for the project. To overcome this silo approach, clients and their suppliers are moving to more collaborative engagement models such as alliancing.

4.1 Alliancing In practice, there is a sliding scale of alliancing from simply having some form of partnering charter or nonbinding agreement overlaying another engagement model, all the way through to the creation of a formal contractual alliance. In all cases, the parties are encouraged to work together on a best-for-project basis and are incentivised to do so via shared performance measures. When a contractual alliance is created, the parties sign up to the same contract and share the majority of risk and reward.

32

A. Evans et al.

There is support for alliancing from government in the Construction Playbook [17], which states that while alliancing arrangements are not always appropriate, ‘they should be considered on more complex programmes of work as the effective alignment of commercial objectives is likely to improve intended outcomes as well as drive greater value for money’ [17].

4.2 Enterprise Project 13 [20] from the Institution of Civil Engineers is an illustration of what currently constitutes ‘good’. Described as an enterprise model for infrastructure delivery, Project 13 brings together numerous partners and suppliers who integrate their capabilities, processes and information under incentives and long-term relationships. The asset owner, or client, is the central driver of change, and the parties are rewarded based on their value to the overall project outcome – not on a transaction of time or volume of work. Risk is aligned with capability and is not cascaded down the supply chain. Coming from an adversarial and competitive approach to contracting, the shift to enterprise and alliancing is immense, but it is doable. Success lies in the hands of the client, or ‘capable owner’ as Project 13 calls them. However, many owners will take time to become capable. Contractors need ways to transform their methods of working that can be driven by themselves in the meantime, while forming those long-term relationships with the supply chain that will be called upon in the future.

4.3 Change Takes Time While the use of alliancing and enterprise ways of contracting may be the way forward, we need to consider how to deal with the more traditional biparty contracts that pervade the industry. Even in a move to alliancing, not all members of the supply chain will form part of the alliance, and there will still be biparty contracts at subcontract and subsubcontract level. We therefore need to consider the digital maturity of all parties and recognise that the expertise and ability to transform will vary, and yet each part of the chain has a part to play in the move to a more digitally enabled industry. The wider supply chain needs to be engaged in information management; however, the level of their involvement, the data they supply and the format of this needs to be proportionate to their role and their level of digital maturity. The approach adopted across contracts should be scalable to reflect the differing levels of maturity. Levels of IT literacy will vary and Tier 1 contractors have a duty to engage with their supply chains and train them on the systems they are employing on projects at an appropriate level of detail to ensure the project’s security. While the wider supply chain may need an incentive to ‘do BIM’, to contribute to the collaborative

Transforming the Civil Engineering Surveyor

33

information management of a project and to work with that information themselves, whether accessing the model interface or inputting data, everyone must take responsibility for their part in the information delivery process.

4.4 Protocols Protocols allow a consistent set of requirements to be used for all parties that contribute to the information model; however, this can lead to clashes between the terms of the protocol and the contract it overlays. Careful consideration has to be given as to how protocols and contracts interact and the interfaces between them need to be actively managed. Where alliancing approaches are adopted, the need for protocols to manage the interfaces between the parties contributing to the information model is reduced or removed as the parties share in the performance risk of the information model. The Construction Industry Council (CIC) BIM Protocol was the first to guide information sharing and collaboration as responsibility for the design model changed on a project. A second edition was released in 2018. These have since been developed into two information protocols within the UK BIM Framework [21] (for ISO 19650-2 and ISO 19650-3). While there is a wealth of helpful processes and procedures, parties will still need to find a way to ‘talk to each other’ digitally and trustfully. Protocols are ‘points in time’ and do not address the wider behavioural change that needs to occur. Ways of working with protocols and standards in general need to be addressed by contractors. While there has been a government information management mandate since 2016, neither clauses nor protocols can be forced onto parties arranging a contract outside of the mandate. The only persuasive argument will be demonstrative. Contractors and clients need to share case studies and experiences, facilitated by professional bodies and their knowledge sharing platforms, highlighting reduced rework and reduced disputes on projects. Whatever contracting model is adopted, successful information management requires the parties to work collaboratively, and this should be made a contractual obligation, such as the requirement in the NEC4 suite of contracts for the parties to act in a spirit of mutual trust and cooperation. The Question of Responsibility  One of the largest questions that will need to be addressed contractually is around responsibility for the information model and the data within it. This issue needs to be considered both during the development of the model and upon its completion. This is unfortunately a common objection to collaboration in information management. In alliancing, depending on the specific form of contract used, the parties share in the risk of the creation of the digital information, removing the need for each party to protect its own position and have this addressed in the contract or protocol. Such an approach is adopted in the NEC4 Alliance Contract in which the alliance as

34

A. Evans et al.

a whole is responsible for updating or creating the information model and correcting any errors within it. With this kind of contract, there is no requirement to allocate responsibility and risk for elements of the model that each party creates or inputs into, with all parties sharing the risk to the extent of their liability under the contract. This allows them to work collaboratively, without the need to protect their individual position, and the information within the model becomes the property of the client on completion. However, this flow does not work with multi-party contracts. If the client holds a federated model, it needs to consider at the earliest planning stages how it will provide secure, relevant and proportionate access and how it will manage the information contributions of others. In some contracting models, such as design, build and operate, the responsibility for the creation or modification of the federated model may be passed to the first tier supplier, who will coordinate the inputs into the model from the supply chain and then pass the federated model back to the client at the end of the contract. Planning for the transferral of responsibility should take in soft landings guidance [22] and the Line of Sight [23] methodology from the Centre for Smart Infrastructure and Construction, which echoes the principle of keeping the end use of the asset constantly in mind. As the National Digital Twin programme ramps up, the information model has to be put to use. Asset management objectives and any client-operated information management platforms [24] have to be considered at the time of contract formation. Contracts should enforce the principle that the client is ultimately paying for the information model and hence owns the delivered data. This does not preclude intellectual property or technical responsibility of those who have contributed to it. In general, while the output is project specific, the skills to create it reside within the professionals employed on the project. The ‘golden thread’ philosophy, set out in the Hackitt Report [25], supports this ideal of being able to go back in time to determine who made what decision, when and why, by having a robust history of decision-­making within an information model. A properly BS EN ISO 19650 compliant common data environment (CDE) archive should provide this. In BS EN ISO 19650:2018, the archive state is used to hold a journal of all files that have been shared and published during the information management process as well as an audit trail of their development and any revisions. This should not be confused with an IT archive, which usually refers to a process where a file is removed from a live computer system to an offline environment where it is archived for subsequent retrieval.

4.5 Reducing Disputes Better information management should in theory lead to fewer disputes, as design and scheduling clashes are spotted before work begins on site, and an audit trail – or golden thread – of digital information should support change management, and also mediation and arbitration should a dispute fully develop.

Transforming the Civil Engineering Surveyor

35

In 2016, the Centre of Construction Law and Dispute Resolution at King’s College London released its research report Enabling BIM Through Procurement and Contracts [26]. While almost 6 years old, it highlights many considerations for contract drafters and managers, notably that most contract forms in use are unsuitable alone for good information management. More recently in 2021, Constructing the Gold Standard: An Independent Review of Public Sector Construction Frameworks [27] was published by the Cabinet Office to aid government clients in adoption of the Construction Playbook. While not highlighting digitalisation specifically, the Conflict Avoidance Pledge [28], supported by CICES as a member of the Conflict Avoidance Coalition Steering Group, demonstrates that signatories have committed to deliver value for money and work collaboratively. The behavioural changes that come with digital transformation will help signatories in fulfilling the pledge, which has been recognised by government in the Construction Playbook. Another initiative supported by CICES and a good example of industry-wide collaboration is the Multidisciplinary Steering Group for Cost Assurance and Audits on Infrastructure Projects and Contracts [29]. This brings together construction lawyers, contractors, clients and finance advisors to address issues around cost assurance. The 2018 Winfield Rock Report: Overcoming the Legal and Contractual Barriers of BIM [30] is also imperative reading. The report gives a good overview of legal professionals’ understanding of the contractual issues around information management. The Future  Contractual arrangements that enable data sharing to truly transform civil engineering surveying and construction itself are yet to be fully realised. The commercial component of projects has to mature to allow industry to exploit the potential of information management to deliver benefits during the capital and operational phases of assets. In a nutshell, if contracting carries on as normal, then information management will always be pushing water uphill. Progress is being made. The UK government is very clear on that, saying: ‘We will ensure that contracts are structured to support an exchange of data, drive collaboration, improve value and manage risk’ [17].

4.6 Trusting and Being Trusted It is understandable that any mention of change in the construction industry is met with scepticism. A few civil engineering surveyors will remember the Banwell Report [31] of 1964, more will remember the Latham Report [32] of 1994 the Egan Report [33] of 1998 and even early career surveyors will be aware of the Farmer Review [34] from 2016. All incredibly sensible, but the change these reports called for was never fully realised. In 2009, the Wolstenholme Report [35] assessed the lack of progress since the earlier reports. The key reason for little change was the acceptance of the status quo by investors and suppliers.

36

A. Evans et al.

There are signs that things are different now, and mechanisms are starting to drive change. The first real enabler of transformation was the 2011 UK government’s mandate for centrally procured construction projects to be delivered using BIM by 2016. This was followed in 2020 by the Construction Playbook [17], which specifically calls on contracting authorities to use the UK BIM Framework [4] of standards and guidance and to support the adoption of the forthcoming Information Management Framework, which will sit behind the National Digital Twin. These requirements need change to happen. The Infrastructure and Projects Authority’s Transforming Infrastructure Performance: Roadmap to 2030 (TIP) [5] calls for a ‘step change in productivity and efficiency in the ways we plan, design, manufacture, construct and operate infrastructure’. For this step change, ‘successful delivery will require clients and suppliers to develop and adopt new ways of working across the board; to share information and embrace new technologies that deliver better performance and more balanced outcomes across the asset lifecycle. Project leaders will need to steer innovative delivery in line with the government’s complex policy objectives, and embrace responsibility for the delivery of outcomes as well as outputs’ [36]. Added to these industry and government movements are two societal impacts: the COVID-19 pandemic and climate change. The pandemic brought the benefits of autonomous and remote technology on site to the fore, with video communications and augmented reality replacing site visits, while further minimising the associated safety risks of being on site. The UK government’s Build Back Better commitments are centred on sustainability and carbon economy. It is impossible to achieve change using traditional approaches. Increased digitalisation, offsite assembly and manufacture and modern methods of construction are seen as key to reducing carbon emissions. Balfour Beatty, Costain, Laing O’Rourke, Skanska, Kier, Galliford Try, BAM, Amey and many other major contractors all have net zero pledges with dates ranging from 2030 to 2050 requiring them to embrace digitalisation as a carbon cutting benefit. All these things are happening now. There is no room for scepticism as change is finally underway.

4.7 Fitting Into a Changing Landscape Where does the civil engineering surveyor fit in this changing landscape? As civil engineering is chiefly from public funds for public good, change is largely going to be driven by government mandates, policies and procedures. This doesn’t mean it will be without its challenges – as the TIP states, the government’s policy requirements are ‘complex’. One common theme that came through workshops with geospatial surveyors was that clients don’t always know what to ask for. For example, a client will ask for a ‘drone survey’, without any prior discussion with the surveyor over what the purpose for the survey is and what data and accuracy is actually needed. One surveyor used the term ‘digital handholding’ to describe the client/ surveyor relationship throughout this transformational period. The geospatial

Transforming the Civil Engineering Surveyor

37

surveyor is ideally placed to offer advice on the most efficient survey method to get the data that is needed and can ‘hold the hand’ of the client as they become more familiar with data-driven construction and asset management. This kind of early communication is called for in the Construction Playbook, which stresses the need for early supply chain involvement when developing the business case for projects. Civil engineering surveyors, both commercial and geospatial, must be a part of this. Within civil engineering surveying, as within construction as a whole, there is a huge variability in size and digital capability throughout the supply chain. There is a wealth of expertise and experience in some of the smaller links in the construction chain that should not be overlooked. The risks and responsibilities of information management need to be carefully managed by those higher up the supply chain to ensure the contributions of smaller, less digitally astute and equipped businesses are transformed to fit the world of digital engineering. In a joint report [37] from the Centre for Digital Built Britain and KPMG in 2021, the importance of SMEs in realising the productivity gains and cost savings of information management was highlighted. According to the analysis, direct labour productivity gains are potentially between £5.10 and £6.00 for every £1 invested in information management, and direct cost savings are between £6.90 and £7.40 from reductions in delivery time, labour time and materials. However, the report states: ‘The wider economic returns we have estimated rely on the productivity gains of IM [information management] being realised by organisations of all sizes, including the sector’s “long tail” of SMEs… there are particular barriers for smaller firms adopting IM which still need to be overcome’ [37]. Tier 1 contractors can play a part in overcoming this hurdle as role models and by providing training on data management software to their supply chains. The interfaces of software systems should be clear, and tasks should mirror those in widely used systems such as Microsoft Excel, to reassure those who have worked on these systems all their working lives and encourage them as they move to more collaborative and interoperable platforms. Expectations need to be realistic, and many will employ dual systems for a short time while they build up trust in new systems. Commercial surveyors are by their nature suspicious – that questioning and fact checking trait is one of the chief skills that they are employed for and will play a key quality assurance role in the construction team of the future. However, telling a commercial team to use a new system without any prior engagement and understanding of their concerns will delay change and could build resentment. Leaders need to play a role in giving their teams time to explore new systems and become familiar with them. Contracting is incredibly fast paced, and while it may be quicker for a quantity surveyor to download data into a spreadsheet and work on it independently, it is not an efficient use of that data. In this changing world, contractors cannot lose sight of the fact that data efficiency is as, if not more, important than cost.

38

A. Evans et al.

Acknowledgement  Special thanks to the UK BIM Alliance, Ian Bush Msc Construct IT, FCInstCES, Chris Hallam FCInstCES, Alexandra Luck and David Philp FCInstCES for their valued comments and feedback. The authors also thank the contributions of Bernhard Becker (FCInstCES, Director, Geolearn), Mark Brueton (CInstCES, Chief Surveying Engineer, BAM Nuttall), Paul Bryan (Geospatial Survey Manager (retired), Historic England), Phanuel Chirimuuta (Principal Planner, BAM Nuttall), Mark Coates (Director of Strategic Industry Engagements, Bentley Systems), Charlie Cropp (Reality Capture Specialist, Survey Max, and Survey4BIM), Rebecca De Cicco (Principal, Digital Operations, Aurecon, and Women in BIM), Cecelia Fadipe (Cost Assurance Auditor, CF Business Links), Garry Fannon (Director, exi, and UK BIM Alliance), Rob Hubbard (FCInstCES, Director, Corderoy), Edonis Jesus (BIM Leader, Europe, Lendlease, and BIM4Heritage), William Kelly (MCInstCES, Geomatics Programme Lead, University of Glasgow), Cathryn Lees (Senior Quantity Surveyor, Skanska), Donny Mackinnon (FCInstCES, Arbitrator and Adjudicator, Mackinnon Consult), Stewart Murrell (FCInstCES, Managing Director, Twoplustwo Commercial Services), Martin Penney (FCInstCES, Consultant, Adjuvo Chartered Land Surveyors), David Philp (FCInstCES, Director – Digital Consulting, Strategy & Innovation Europe, AECOM), Vicki Reynolds (Chief Technology Officer, i3PT, and Women in BIM), Nnenna Roberto (Postgraduate, Cranfield University, and Women in Geospatial), Akriti Sharma (Postgraduate, University of Melbourne, and Women in Geospatial), Jason Smith (FCInstCES, Commercial Director, Costain), Djurdjica Stanojkovic (MCInstCES, Commercial Lead, Balfour Beatty), Jason Underwood (MCInstCES, Programme Director, University of Salford) and BIM Academic Forum.

References 1. B.  Buckley, K.  Logan, D.  McCarthy, S.  Jones, Accelerating digital transformation through BIM. SmartMarket Report (2021) 2. Survey4bim, SURVEY4BIM (Survey4bim, 2021), https://survey4bim.wordpress.com/. Accessed 9 Dec 2022 3. I. Bush, Survey and the digital plan of works (2016) [Online]. Available: https://survey4bim. files.wordpress.com/2017/08/survey-­and-­the-­digital-­plan-­of-­works.pdf 4. UK BIM, The overarching approach to implementing BIM in the UK (UK BIM Framework, 2022), https://www.ukbimframework.org/. Accessed 9 Dec 2022 5. Infrastructure and Projects Authority (IPA), Transforming infrastructure performance: Roadmap to 2030 (2021) [Online]. Available: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1016726/IPA_TIP_Roadmap_to_2030_ v6__1_.pdf 6. K. Waller, Value toolkit (Construction Innovation Hub, 2022). https://constructioninnovationhub.org.uk/value-­toolkit/ 7. GoV UK, The green book: Central government guidance on appraisal (2020) (edition 2022) [Online]. Available: www.gov.uk/official-­documents 8. J.  Stephen, L.-C.  Donna, Accelerating digital transformation through BIM (2021) [Online]. Available: https://www.construction.com/toolkit/reports/ Digital-­Transformation-­Through-­BIM 9. Centre for Digital Built Britain, The Gemini Principles (CDBB, 2020) [Online]. Available: https://doi.org/10.17863/CAM.32260 10. GoV UK, UK national data strategy (Department for Digital, Culture, Media & Sport, 2020) [Online]. Available: https://www.gov.uk/government/publications/uk-­national-­data-­strategy/ national-­data-­strategy

Transforming the Civil Engineering Surveyor

39

11. GoV UK, Best practice guidance and tools for managing geospatial data (GoV.UK, 2022), https://www.gov.uk/government/collections/best-­practice-­guidance-­and-­tools-­for-­geospatial-­ data-­managers. Accessed 9 Dec 2022 12. ICMS Coalition, ICMS: Global Consistency in Presenting Construction Life Cycle Costs and Carbon Emissions, 3rd edn. (ICMS, 2021) [Online]. Available: https://www.rics.org/uk/ upholding-­professional-­standards/sector-­standards/construction/icms3/ 13. NCSC, About cyber essentials (Cyber Essentials, 2022), https://www.ncsc.gov.uk/cyberessentials/overview. Accessed 9 Dec 2022 14. CPNI, Developing a security-mindedness approach (Centre for the Protection of National Infrastructure, 2021), https://www.cpni.gov.uk/developing-­security-­mindedness-­approach. Accessed 9 Dec 2022 15. NCSC, Cyber security for construction businesses (National Cyber Security Centre, 2022), https://www.ncsc.gov.uk/guidance/cyber-­security-­for-­construction-­businesses. Accessed 9 Dec 2022 16. CICES, Secure data management for utility surveys (Chartered Institution of Civil Engineering Surveyors, 2022), https://www.cices.org/content/uploads/2022/03/Secure-­Data-­Management-­ for-­Utility-­Surveys.pdf. Accessed 9 Dec 2022 17. HM Government, The Construction Playbook: Government Guidance on Sourcing and Contracting Public Works Projects and Programmes, vol 22, no 4 (Cabinet Office, 2022). https://doi.org/10.2307/25294531 18. National Infrastructure Commission, Data for the public good (National Infrastructure Commission, 2017), p.  76 [Online]. Available: https://nic.org.uk/app/uploads/Data-­for-­the-­ Public-­Good-­NIC-­Report.pdf 19. National Infrastructure Commission, Sharing data, in Data for the Public Good, (National Infrastructure Commission, 2017) [Online]. Available: https://nic.org.uk/app/uploads/Data-­ for-­the-­Public-­Good-­NIC-­Report.pdf 20. M. Zanocco, Does a Project 13 Enterprise model help with the current complex environment? (Project13, 2022), https://www.project13.info/news/does-­a-­project-­13-­enterprise-­model-­help-­ with-­the-­current-­complex-­environment-­r41/. Accessed 9 Dec 2022 21. UK BIM Framework, Transition to the UK BIM framework (UK BIM Framework, 2022), https://www.ukbimframework.org/resources/ 22. D.  Philip, D.  Churcher, S.  Davidson, Government soft landings (2019) [Online]. Available: https://ukbimframework.org/wp-­content/uploads/2019/11/GSL_Report_PrintVersion.pdf 23. A.  Parlikad, J.  Schooling, J.  Heaton, T.  Embley, H.  Baker, Line of sight: An asset management methodology to support organisational objectives (2017) [Online]. Available: https://www-­smartinfrastructure.eng.cam.ac.uk/projects-­and-­case-­studies/ line-­sight-­asset-­management-­methodology-­support-­organisational-­objectives 24. J. Liu, H. Men, J. Han, Information management platform (2010) [Online]. Available: https:// www.cpni.gov.uk/system/files/documents/eb/2a/cpnigiigimp-­guidance-­document.pdf 25. D. Hackitt, Building a safer future: Independent review of the building regulations and fire safety: Final report (2018) [Online]. Available: https://www.cpni.gov.uk/system/files/documents/eb/2a/cpnigiigimp-­guidance-­document.pdf 26. D. Mosey, D. Bahram, C. Howard, R. Dartnell, C. Hallam, C. Howard, A. Maqbool, K. Murray, S. Rawlinson, M. Winfield, Enabling BIM through procurement and contracts (2016) 27. D. Mosey, Constructing the gold standard: An independent review of public sector construction frameworks (2021) [Online]. Available: https://www.gov.uk/ 28. RICS, Conflict avoidance pledge (RICS, 2022), https://www.rics.org/uk/products/ dispute-­resolution-­service/conflict-­avoidance-­pledge/ 29. K. Hannon, C. Fadipe, Cost assurance and audit in practice (2021) [Online]. Available: https:// www.cfbusinesslinks.com/steering-­group-­csr 30. M. Winfield, S. Rock, The winfield rock report: Overcoming the legal and contractual barriers of BIM (2018) [Online]. Available: https://www.ukbimalliance.org/winfield-­rock-­report-­2/

40

A. Evans et al.

31. C. Hardcastle, P. Kennedy, J. Tookey, The placing and management of contracts for building and civil engineering work: The Banwell report (1964), in Construction Reports 1944–98, ed. by M. Murray, D. Langford, (Wiley, 2008), pp. 55–68 32. S.M. Latham, Constructing the team: Joint review of procurement and contractual arrangements in the United Kingdom construction industry (1994) [Online]. Available: https:// constructingexcellence.org.uk/wp-­content/uploads/2014/10/Constructing-­the-­team-­The-­ Latham-­Report.pdf 33. S.J. Egan, Rethinking construction. The report of the Construction Task Force (1998), p. 38 [Online]. Available: http://constructingexcellence.org.uk/wp-­content/uploads/2014/10/ rethinking_construction_report.pdf 34. M. Farmer, The farmer review of the UK construction labour model (Construction Leadership Council, 2016), p.  76 [Online]. Available: https://www.gov.uk/government/publications/ constructionlabour-­%0Amarket-­in-­the-­uk-­farmer-­review 35. A. Wolstenholme, S. Austin, M. Bairstow, A. Blumenthal, J. Lorimer, S. McGuckin, Never waste a good crisis: A review of progress since rethinking construction and thoughts for our future. Constr. Excell. 42(4–5), 282–286 (2020). https://doi.org/10.1108/LM-­11-­2020-­0165 36. Infrastructure and Projects Authority (IPA), Purpose and vision, in Transforming Infrastructure Performance: Roadmap to 2030 (2021), p.  64 [Online]. Available: https://www.gov.uk/ government/publications/transforming-­infrastructure-­performance-­roadmap-­to-­2030 37. Atkins, The value of information management in the construction and infrastructure sector: A report commissioned by the University of Cambridge’s Centre for Digital Built Britain (CDBB) (June 2021) [Online]. Available: https://www.cdbb.cam.ac.uk/files/cdbb_econ_ value_of_im_report.pdf

Limes with Hydraulic Properties for 3D Printing Mortars B. D. Dias , D. Rocha and A. Reaes Pinto

, P. Faria

, S. S. Lucas

, V. A. Silva, B. Lobo,

1 Introduction Additive manufacturing is a technique for fabricating three-dimensional structures directly from a digital model. When the technology is fully developed and adopted, the aim is to optimize the use of resources, reduce construction cost and execution time, and increase the level of safety and design freedom [1]. Integrating 3D printing with the BIM (building information modeling) method can optimize structural design, use of material, and installation of several systems in a building [2]. Mortars for 3D printing using a layer deposition process can have two types of behavior: fast hardening behavior and rheology-modified behavior. The first behavior allows more freedom of design and faster layer buildup. However, this fast hardening can lead to blockage issues, mainly if accelerated at the beginning of the pumping line. Also, this acceleration can lead to layers’ delamination causing anomalies, especially in structural elements. A rheology-modified mortar behaves B. D. Dias (*) · A. Reaes Pinto CITAD – Lusíada University, Lisbon, Portugal e-mail: [email protected] D. Rocha · P. Faria CERIS – Civil Engineering Research and Innovation for Sustainability, Department of Civil Engineering, NOVA School of Science and Technology, NOVA University of Lisbon, Caparica, Portugal S. S. Lucas Built Environment, Eindhoven University of Technology, Eindhoven, The Netherlands V. A. Silva Department of Civil Engineering, NOVA School of Science and Technology, NOVA University of Lisbon, Caparica, Portugal B. Lobo Saint-Gobain Weber Beamix, Eindhoven, Netherlands © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 F. Gaspar, A. Mateus (eds.), Sustainable and Digital Building, https://doi.org/10.1007/978-3-031-25795-7_3

41

42

B. D. Dias et al.

as a fluid while energy from the pumping process is being supplied and gains stiffness as soon as this energy ends. This strategy provides a good compromise between layer buildup/printing speed and final element homogeneity. The ability to print a monolithic structure is essential for structural elements, such as houses, bridges, and other structures. To be suitable for these applications, a mortar must have high strength at an early age, fast setting, cohesion, and sufficient yielding stress to be extrudable [3]. One of the first discussions in this study was the type of binder to use: lime with hydraulic properties or air lime. Both have good rheological properties, but attention should be paid to the speed of carbonatation. Most 3D printing mortars are made with cement as the main binder [4]. Cement curing is fast, and mortars have high compression strength. On the other hand, limes have a lower ecological impact [5] because they are produced at a lower temperature, and energy for milling is lower in comparison to clinker, fissures can self-heal [6], and the mortars absorb carbon dioxide from the atmosphere while carbonating. The main disadvantages of using 3D lime-based mortars can be the lower compression strength and the long time to achieve it. This can make it difficult to transport printed elements from a production facility to the building site. Probably these limitations justify the lower amount of research work available. There are several types of building limes [7]: air limes and limes with hydraulic properties. The latter can be natural hydraulic limes (NHLs), hydraulic limes (HLs), or formulated limes (FL). The NHL results from the direct firing of limestone which is available in nature together with clay inclusions, while the HL and FL may have additional materials added to the production and formulation, respectively. There are three classes for NHL and HL limes: 2, 3.5, and 5, with decreased Ca(OH)2 content and increased potential strength. To design a 3D printable mortar, it is fundamental to use the right admixtures and optimize the contents. Admixtures allow to reduce water content while maintaining a good flowability, regulate the homogeneity and consistency of a mortar, and make them cure fast enough to move printed elements a few hours after printing. The main goal of this study, within a larger project, was to develop and test lime-­ based mortar compositions that can be used to 3D print nonstructural elements. For comparison and to validate how a 3D printing mortar should work, a premixed 3D printable cement mortar was used to run printing tests and to tune the equipment.

2 3D Printing Setup The equipment to test mortar compositions for 3D printing was composed of an auger extruder device, developed to attach to a Fanuc 420i Robotic harm which has a 2.5 m radius reach and six axes. It gives the possibility to test small amounts of material, reducing waste. The screw is 100  mm in diameter, and a Nema17 step motor was applied to rotate, with a gearbox controlled with an Arduino board that allows setting the RPM needed. The nozzle was 3D printed with PLA filament, and

Limes with Hydraulic Properties for 3D Printing Mortars

43

the exit was 20 mm in diameter. When the composition of the tested mortars presents low fluidity and high viscosity, two things can happen: the step motor stops, or the nozzle can break, close to the flange. When printing, the robot’s speed can vary between 30 and 50  mm/s. During printing, the extrusion revolution per minute (rpm) can vary between 6 and 12 rpm.

3 Materials and Mortars Two limes with hydraulic properties were chosen and used to formulate printable mortars: a natural hydraulic lime classified as NHL5 based on EN 459-1 [7] (NHL) and a hydraulic lime classified as HL5 (HL) also based on the same standard for building limes. Both binders were made available by Secil Martingança company, Portugal. A siliceous sand (S) was used in all lime mortars. A limestone powder (LP) was used as filler. The loose bulk density of all these materials was determined according to the EN 1097-3 [8] and results are presented in Table 1. The particle size distribution of the sand and the limestone was assessed following the EN 1015-1 [9] with results presented in Fig. 1. To reduce the water content needed for the mortars, a polycarboxylate-based superplasticizer (SP), Viscoflow-30PT from Sika, was incorporated into the formulations. To improve cohesion and viscosity, a small dosage of a viscosity-modifying admixture (VMA), Estabilizador-VP1 from Sika, was used. SikaRapid-1 from Sika was used as a curing accelerator (A). To achieve the needed workability to extrude the mortars, the amount of added water was optimized, after successive trials. As the mortars formulated are not for common applications, to optimize the proportions of water/solid components, many tentative extrusions were performed to optimize the water content. When a cylinder with 15 layers was printed, the mortar was considered successful. For comparison, a commercial pre-dosed 3D mortar W-160 from Weber, the Netherlands, was chosen as a reference. The composition of the reference mortar is not available, but it is cement-based and contains microfibers in its composition. The amount of water for the reference mortar mixing was already defined by the manufacturer. Table 2 shows the proportions of the mortars’ different materials. For the formulated mortars, all materials’ specific proportions were measured by the weight of the binder mass. For the admixtures, the mass ratio was the same for both mortars. To prepare the three mortars, a handheld electric mixer with two speeds (Rubimix-9 N, 1200 W) was used. Before mixing, all admixtures were diluted with the total water. First, the dry components were homogenized, mixing at low speed Table 1  Loose bulk density of the limes NHL and HL, the sand, and the limestone Loose bulk density (kg/m3)

Sand 2803

Limestone powder 973

NHL 848

HL 761

44

B. D. Dias et al.

Cumulative passing by weight (%)

100

Limestone powder

80

Sand

60 40 20 0

0.01

0.1

Particle size (mm)

1

10

Fig. 1  Particle size distribution of the sand and the limestone powder used in the mortars Table 2  3D print mortar materials by percent of binder mass Mortar NHL HL W160

W-160 (wt%)

HL

100

NHL

LP

100

10 10

Sand (wt%) 90 90

100

Water (wt%) 27 32 12

SP (wt%) 0.86 0.86

VMA (wt%) 0.1 0.1

A (wt%) 0.4 0.4

(650 rpm) for 1 min, and then 80% of the liquids were included in the mixing and mixed at low speed for 5 min. To ensure the homogeneity of the mortars, before adding the remaining liquid suspension, the bucket was scraped. After the addition of the 20% remaining liquids, mixing proceeded at high speed (850 rpm) for 10 min, considering the period of time needed to obtain the necessary consistency. The time zero for this study was defined when the initial liquids were added. The commercial mortar preparation had just two steps: mixing with low speed for 1 min with total water, followed by mixing with fast speed for 4 min.

4 Test Procedures 4.1 Mini-Slump and Flowability Test The consistence flow test followed the standard EN 1015-3 [10]; the mold had internal diameters of 70 and 100 mm, upper and bottom dimensions, respectively, and a height of 50 mm. The mold was filled at half height and rammed with a metallic stick 15 times to eliminate air, then the other half was filled and rammed for equal times, and the remaining excess material was scraped. The mold is removed, and the table was dropped 15 times within 15 s. The diameter after the drops was measured in four perpendicular directions and the average provides the test result.

Limes with Hydraulic Properties for 3D Printing Mortars

45

The mini-slump test was a simple evaluation of shape retention after the removal of the mold. The height of the sample was measured just after the removal of the flow table test mold and before the drops. To evaluate changes with time, the tests were performed in sequence for 90 min with a time gap of 15 min. The mortar used for a test was homogenized with the remaining mortar of the same batch before the following test. The laboratory conditions during the tests were 16 ± 2 °C and 70 ± 5% HR.

4.2 Air Content of Fresh Mortar The quantification of air volume in the fresh mortar was performed as it is also linked with the hardening properties [11–13]. The test procedure followed the EN 1015-7 [14]. A calibrated mold was filled in with two layers of mortar, each layer compacted with four perpendicular strokes at a distance from the table of 10 mm. The excess mortar was removed, and the interface for the equipment with the calibrated manometer was cleaned. The holder and the equipment were sealed and filled with pressurized water, penetrating the air voids. The percentage of voids was registered using the manometer.

4.3 Buildability Test The printability is not only linked with the flowability, but the buildability is also an important criterion. Only with the flowability, it is not possible to predict the buildability performance [15, 16]. The construction of multiple layers and their behavior is the only method to evaluate fresh performance printable mortars. To evaluate the buildability of printing mortars, different types of tests have been reported in literature. The most common are the “settlement” and the “hallow column/cylinder” tests. Both evaluate the deformation of a mortar when successive layers are printed. The main deformation of a fresh mortar is associated with the capacity to self-­ weight, weight of following layers, and printing pressure applied [17]. This test does not have standards or international protocols; it is a simple quantitative evaluation of the mortar performance. The main purpose of the test is to measure the height of the printed sample. For this test samples with 320 × 320 × 50 mm3 were printed. A continuous linear flow was performed. The interlayer time gap of 0  min was considered. The test started 30 min after the addition of water to the mixing process. The programmed height for each layer was defined as 10 mm. For the samples production, all layers are printed with the same conditions, and at the end of the printing, the height of the samples was measured with a graduated ruler. Considering the non-deformation of the printing mortar the height of the

B. D. Dias et al.

46

printed sample should be 50 mm. After the measurement, it is possible to quantify the real deformation.

5 Results 5.1 Mini-Slump and Flowability Test Figure 2a shows the height after the removal of the flow table mold and before the drops in the flow table. The commercial mortar maintains the shape performance during the 90 min of the test; consistency in properties over time is good for printing technologies. A large open time ensures that the mortar can be pumped and printed without blocking the hose or the print head [18]. The printing window is the main a)

60

W-160 NHL HL

50

Height (mm)

40 30 20 10 0 b)

0

10

20

30

40 50 Time (min)

60

70

80

90

100

30

40 50 Time (min)

60

70

80

90

100

230 220 210

Diameter (mm)

200 190 180 170

W-160 NHL HL

160 150 140

0

10

20

Fig. 2  Flowability test: (a) mini-slump test height before dropping the table; (b) flow test results, spread diameter after the dropping the table 15 times

Limes with Hydraulic Properties for 3D Printing Mortars

47

problem, but this is already being studied, and technology for mixing the mortar only in the printer head may probably overcome this problem [19]. The test stopped at 90 min when a cracking texture of the mortar started to be noticed, and a considerable reduction of workability occurred. Analyzing the two lime-based mortars, the slump performance was similar during the first 60 min. The HL mortars have the lowest height at 30 min and the NHL mortar at 45 min after adding the water. After that, the HL mortar has a higher change, with a lower height (less slump). This slump deformation after some minutes can be related to the SP effect. The ability of SP to disperse the cement particles and the consistency of the mortar can change over time as the SP reacts with the materials [20]. For the HL mortar, the vertical deformation gradually decreases with time. It is reported that VMA in high dosages could contribute to stabilizing shape retention [21]. All the mixtures include VMA in their composition, which is probably influencing their workability. It is expected for interlayer bonding to improve when the open time is compatible with the print speed [22]. Figure 2b presents the flow table results. The commercial mortar presents nonlinear values for the spreads during the time. After 30 min, the diameter variation is less than 5% for each measurement. Looking at the results of the lime-based mortars, during the test the mortars started to lose the flow. The HL mortar decreased 22% of flow since the beginning of the test. The NHL mortar also decreased but only 13% since the first measurement. This higher stability of the NHL mortar may be related to the higher Ca(OH)2 content of the NHL in comparison to the HL and a slower hardening of the previous. In comparison with the commercial mortar, it is noticeable that formulated mortars presented a more homogeneous performance, although the loss of consistency is higher.

5.2 Air Void Content of Fresh Mortar For the commercial mortal, the percentage of air voids was 4.5%. The NHL and HL mortars presented 7% and 27% of air void content, respectively. Comparatively, with the flow table test, the air void content does not show a direct influence on the slump performance. The higher content of air voids is not proportional to the slump and flow results.

5.3 Buildability Test The results of the buildability test can be seen in Fig. 3 and are just for one printed sample per mortar, although an average height is taken at two points of the sample. The HL mortar presents an average value of 47.75  mm, corresponding to 5% of deformation. Looking at Fig. 3a, the HL mortar has a rough texture, and the layers

48

B. D. Dias et al.

Fig. 3  Buildability test of mortars: (a) HL, (b) NHL, and (c) W-160

are not pronounced. After five layers, the NHL mortar had 45.50 mm, representing a deformation of 9%. As shown in Fig. 3b, the layers have a similar dimension, the surface is smooth, and the borders have an accentuated deformation due to the viscosity of the plaster. The commercial mortar has higher stability, and the average value is 50.50 mm; in percentage, this is 1%. Visually, the printed quality of each layer is smoother than for formulated mortars, and also the width of extrusion is very regular. The results for W-160 mortar prove that there is not a good correlation between the flowability test and the buildability for pre-dosed mortar. Better understanding of the fresh properties is recommended to run rheology tests [23]. The incorporation of microfibers into the composition can probably improve the strength of the fresh mortar and therefore the buildability results [15, 18]. As the lime-based mortars do not have microfibers, the self-weight and support weight are not similar to the cement-based mortar.

6 Conclusions The fresh properties are definitely important for the printing and hardening performance of 3D printed mortars. The flow test associated with time can guide the open time and the changes in workability. The NHL- and HL-based formulated mortars showed considerable changes in workability during the 90 min of the test. The flow table and the mini-slump tests did not prove to be realistic tests to evaluate the buildability performance. The flowability results of commercial mortar are not congruent with the buildability test.

Limes with Hydraulic Properties for 3D Printing Mortars

49

The pumpability is shortened by the workability, and the pressure to keep the same rate flow is difficult to predict. This changes the quality of the printed mortar products and can create a blockage of the hose. The substitution of cement with lime as a binder material seems to be possible for additive manufacturing. The HL mortar seemed to have better buildability compared with the NHL mortar. However, a visual analysis of the quality of the printed layers showed that the HL mortar presents a rougher surface. Therefore, further research is needed, namely, to study the influence of the SP and VMA separately, using complementary tests to investigate the fresh properties of printed mortars and the influence it has on hardened mortar properties and using fibers to improve the buildability. Acknowledgments The authors acknowledge the Portuguese Foundation for Science and Technology (FCT) for the financial support within Douglas Rocha’s scholarship (2021.05371.BD), and the support provided by CITAD (UIDB/04026/2020) and CERIS (UIDB/04625/2020).

References 1. M.  Xia, J.  Sanjayan, Method of formulating geopolymer for 3D printing for construction applications. Mater. Des. 110, 382–390 (2016). https://doi.org/10.1016/j.matdes.2016.07.136 2. M.  Sakin, Y.C.  Kiroglu, 3D printing of buildings: Construction of the sustainable houses of the future by BIM.  Energy Procedia 134, 702–711 (2017). https://doi.org/10.1016/j. egypro.2017.09.562 3. L. Reiter, T. Wangler, A. Anton, R.J. Flatt, Setting on demand for digital concrete – Principles, measurements, chemistry, validation. Cem. Concr. Res. 132, 106047 (2020). https://doi. org/10.1016/j.cemconres.2020.106047 4. S.C. Paul, G.P.A.G. van Zijl, M.J. Tan, I. Gibson, A review of 3D concrete printing systems and materials properties: Current status and future research prospects. Rapid Prototyp. J. 24(4), 784–798 (2018). https://doi.org/10.1108/RPJ-­09-­2016-­0154 5. M.  Sinka, G.  Sahmenko, A.  Korjakins, L.  Upeniece, Artificial hydraulic lime binder and its impact on properties of hemp-lime compositions, in Proceedings of the International Conference, Innovative Materials, Structures and Technologies (2014). https://doi.org/10.7250/ iscconstrs.2014.27 6. B.  Lubelli, T.  Nijland, R.P.J.  Hees, Self-healing of lime-based mortars: Microscopy observations on case studies. Heron 56(1/2), 1574–4078 (2011) http://resolver.tudelft.nl/ uuid:ff226ad0-­ffb2-­4b4c-­bdb6-­9881961bc7f1 7. EN 459-1:2010 – Building lime – Part 1: Definitions, specifications and conformity criteria. Brussels (2010) 8. EN 1097-3:1998  – Tests for mechanical and physical properties of aggregates  – Part 3: Determination of loose bulk density and voids. Brussels (1998) 9. EN 1015-1:1998 – Methods of test for mortars for masonry – Part 1: Determination of particle size distribution (by sieve analysis). Brussels (1998) 10. EN 1015-3:1999 – Methods of test for mortar for masonry. Determination of consistence of fresh mortar (by flow table). Brussels (1999) 11. P.C.  Fonseca, G.W.  Scherer, An image analysis procedure to quantify the air void system of mortar and concrete. Mater. Struct. 48, 3087–3098 (2015). https://doi.org/10.1617/ s11527-­014-­0381-­9

50

B. D. Dias et al.

12. X. Zeng, X. Lan, H. Zhu, G. Long, Y. Xie, Investigation on air-voids structure and compressive strength of concrete at low atmospheric pressure. Cem. Concr. Compos. 122, 104139 (2021). https://doi.org/10.1016/j.cemconcomp.2021.104139 13. N. Kabashi, C. Krasniqi, H. Morina, A. Dautaj, Effect of air voids in fresh and hardening properties of concrete, in 3rd International Balkans Conference on Challenges of Civil Engineering, 3-BCCCE, Epoka University, Albania, 19–21 May 2016 14. EN 1015-7:1998 – Methods of test for mortar for masonry – Part 7: Determination of air content of fresh mortar. Brussels (1998) 15. T.T. Le, S.A. Austin, S. Lim, et al., Mix design and fresh properties for high-performance printing concrete. Mater. Struct. 45, 1221–1232 (2012). https://doi.org/10.1617/s11527-­012-­9828-­z 16. V.  Mechtcherine, V.N.  Nerella, K.  Kasten, Testing pumpability of concrete using Sliding Pipe Rheometer. Constr. Build. Mater. 53, 312–323 (2014). https://doi.org/10.1016/j. conbuildmat.2013.11.037 17. A. Kazemian, X. Yuan, E. Cochran, B. Khoshnevis, Cementitious materials for construction-­ scale 3D printing: Laboratory testing of fresh printing mixture. Constr. Build. Mater. 145, 639–647 (2017). https://doi.org/10.1016/j.conbuildmat.2017.04.015 18. R.A. Buswell, W.R. Leal de Silva, S.Z. Jones, J. Dirrenberger, 3D printing using concrete extrusion: A roadmap for research. Cem. Concr. Res. 112, 37–49 (2018). https://doi.org/10.1016/j. cemconres.2018.05.006 19. S.  Muthukrishnan, S.  Ramakrishnan, J.  Sanjayan, Set on demand geopolymer using print head mixing for 3D concrete printing. Cem. Concr. Compos. 128, 104451 (2022). https://doi. org/10.1016/j.cemconcomp.2022.104451 20. M. Adjoudj, K. Ezziane, E.H. Kadri, T.-T. Ngo, A. Kaci, Evaluation of rheological parameters of mortar containing various amounts of mineral addition with polycarboxylate superplasticizer. Constr. Build. Mater. 70, 549–559 (2014). https://doi.org/10.1016/j.conbuildmat.2014.07.111 21. Y. Chen, S.C. Figueredo, Z. Li, Z. Chang, K. Jansen, O. Çopuroğlu, E. Schlangen, Improving printability of limestone-calcined clay-based cementitious materials by using viscosity-­ modifying admixture. Cem. Concr. Res. 132, 106040 (2020). https://doi.org/10.1016/j. cemconres.2020.106040 22. T.T. Le, S.A. Austin, S. Lim, et al., Hardened properties of high-performance printing concrete. Cem. Concr. Res. 42(3), 558–566 (2012). https://doi.org/10.1016/j.cemconres.2011.12.003 23. V.N. Nerella, M. Krause, V. Mechtcherine, Direct printing test for buildability of 3D-printable concrete considering economic viability. Autom. Constr. 109, 102986 (2020). https://doi. org/10.1016/j.autcon.2019.102986

Comparison of Exhaust Gas Emissions Between Autonomous and Human Operator Excavator Tanja Kolli, Mikko Hiltunen, Ilpo Niskanen, Pekka Tyni, Matti Immonen, and Rauno Heikkilä

1 Introduction In Finland, the content of greenhouse gases (GHGs) such as carbon dioxide (CO2) was 48.1 million tons of CO2-eq, of which working machines contributed 2.4 million tons of CO2-eq. Even though the total GHGs have decreased by 23% in 7 years (from 2013 to 2020), the content of GHGs in the case of working machines has not changed [1]. Although Finland’s GHG emissions represent 0.1% of the world’s GHG emissions, concerns about global climate change and global warming have pushed the construction sites to act more to decrease the GHG values. The emissions of working machines or non-road mobile machines (NRMM), such as nitrous oxides (NOx), carbon monoxide (CO), hydrocarbons (CHs) and particulate matter (PM), have been regulated by the European Union (EU) since 1997, and the emission limits are tightening [2]. However, the formation of CO2, which is currently a major concern, is not yet regulated. Therefore, optional EU Green Deal agreement has been reached between the Finnish government and some construction companies to have fossil-free construction sites so that by the end of 2030, 50% of working machines would run on electricity, hydrogen or biogas [3]. In addition, many infrastructures companies have carried out environmental assessments and adopted rating schemes such as CEEQUAL [4] as part of their sustainability strategy. Nowadays, life cycle assessment (LCA) methodology is used as a calculation tool to estimate GHG emissions. To harmonize the LCA calculation results between projects, a specific guideline has been done to infra sector, for instance, by the NordFoU organization [5]. To calculate the GHG emissions of machines used for the mass transfer process, the data presented in the Technical Research Centre of Finland (VTT) LIPASTO TYKO 2017 database [6], and the machine power, the T. Kolli (*) · M. Hiltunen · I. Niskanen · P. Tyni · M. Immonen · R. Heikkilä Faculty of Technology, Civil Engineering Research Unit, University of Oulu, Oulu, Finland e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 F. Gaspar, A. Mateus (eds.), Sustainable and Digital Building, https://doi.org/10.1007/978-3-031-25795-7_4

51

52

T. Kolli et al.

working hours and fuel consumption for working machines are needed. Since 90% of the NRMM are still running on diesel, research work is still needed in different working or engine scenarios. Therefore, NRMM emissions have been studied in many ways. For example, engine laboratory studies have been conducted with different bio-based fuels and/or after-treatment systems, such as selective catalytic reduction (SCR) unit [7–11] real-world tailpipe emissions of NMMM have been analysed using portable emission measurements (PEMS) equipment [12–15] in chilly weather conditions (2–12 °C) [16]. A mobile laboratory van “sniffer” has also been used [11]. There are also studies in which calculation models, such as EPA NONROAD2008 [17], are used to estimate and compared to the PEMS results of the machine. Since calculation methods have some uncertainties, the discrete-event simulation [18] and even an artificial neural network [19] are also used to assess emissions from the construction process. The automation of working machines to help human operators has been studied for many years. To integrate machines as an integral part of intelligent systems, an autonomous excavator has been equipped with different sensor systems [20]. In addition, a soil surface shape and a large-scale construction site can be monitored from an excavator by using a solid-state 2D pulsed time-of-flight (TOF) laser profilometer and commercial mechanically spinning pulsed time-of-flight multi-echo Lidar [21, 22]. A part of this system is emission monitoring, which plays a significant role in sustainable development in construction sites. However, there is still a high potential to study how automation and robotic technologies can promote sustainability in infrastructure projects as Hoeft et al. (2021) pointed out their literature review article [23]. In this article, the goal of the research work is to determine whether automation can help to decrease harmful emissions formation compared with the human operated excavator. For this purpose, the emissions of a smart excavator system were measured and analysed in real-time conditions using a simple bucket move.

2 Experimental 2.1 Smart (Autonomous) Excavator System In this study, the Bobcat E85 commercial excavator (8.5 tons) was used, which was modified for autonomous excavation purposes [21, 22, 24]. The excavator has a diesel engine with EPA 2012 emission regulations rules (Tier 4final/Stage IIIB) and an engine power of 44.3 kW at an engine speed of 2100 rpm. In addition, it has various devices, such as exhaust gas recirculation (EGR) and diesel particle filters (DPF) to reduce the engine-out emissions. Figure 1 illustrates the configuration of the excavator system used in the test. The exhaust pipe of the excavator was connected to the emission measuring equipment using a heated probe. The smart excavator was equipped with GNSS (Global

Comparison of Exhaust Gas Emissions Between Autonomous and Human Operator…

53

Fig. 1  Smart Bobcat E85 excavator equipped with machine control system as well as emission measurement equipment. In addition, the bucket movement is presented

Navigation Satellite System), CAN bus 6 DOF IMUs and rotary encoder, 4 IP cameras and stereo cameras for the VR remote control. The basis of the sensor system is the Novatron IMU G2 sensor. The excavator is equipped with Novatron Xsite machine control system (MCS), which uses GNSS localization and the IMU sensors from boom, arm and bucket (red line in Fig. 1) to guide the operator in reference to machine control models (MCM). The orientation of the machine, its position and GNSS data with the MCM can be seen from the machine control interface displayed on the tablet size monitor in the cabin. IMU and GNSS data was used as feedback on automation control. The excavator has engine control unit (ECU) that controls the excavator’s electrical systems including the electro-hydraulics (blue line in Fig. 1). The control signals of remote control and automation are routed from control the PC to the ECU via the automation unit. The excavator was equipped with both a radio receiver and a wireless data connection, so, depending on the worksite, both methods of receiving a real-time kinematic (RTK) correction were enabled. The RTK-corrected GNSS positioning data should reach close to centimetre accuracy.

2.2 Bucket Movement During the Autonomous and Human Operator Experiments Several different trajectories for the emissions between autonomous and human operated excavator were compared. This article focuses on the trajectory in which only the boom was raised up and lowered down. Figure 1 presents the simple bucket movement used in the experiments, as well. The operations of the examined

54

T. Kolli et al.

trajectory were as follows: 5 min with 0% engine speed, 5 min with 50% engine speed and 5 min with 100% engine speed. A 0% engine speed is equal to an idle speed. The task of the human operator was to mimic the automatic trajectory joint angles and speed as much as possible. In autonomous driving, automatic trajectories were generated in the Rhino Grasshopper environment, and the generated trajectories were then fed into the excavator control system. The automatic control system was created in a MATLAB Simulink environment. In Rhino Grasshopper, the digital twin of the smart excavator was created, and the desired trajectories were tested before the trajectory data were fed to the excavator control system. Pressure transmitters with digital output and G2 6DOF IMU by Novatron were used to check the pressure and angular variations on each link, respectively.

2.3 Exhaust Gas Emissions from the Excavator The excavator was running motor/heating oil for winter-quality diesel during the emission exhaust gas experiments conducted in winter (December 2021). The weather conditions during the human operator and automation experiments were snowing, the temperature was around +2 °C and ambient pressure was 1004 and 999 mbar. Thermal imaging of the exhaust gas of the excavator was carried out using the FLIR E60 IR Camera. The sensor is obtained images having a resolution of 320 × 240 pixels, and a thermal sensitivity of which was 0.05 °C at 30 °C. It was equipped with a 15 mm lens supplying a field of view (FOV) of 25° and 29°. The emission measurement equipment used in the experiments is presented in Fig.  1. The emissions of the exhaust gas from the tailpipe of the excavator were measured as a function of time every 20 s using a Gasmet DX4000 FTIR gas analyser. The volume of oxygen (O2) was measured by using a Portable Sampling System (PPS) with ZrO2 sensor. The 50-cm-long unheated stainless steel tube was insulated with a layer of tin paper to prevent water condensation to the exhaust pipe. This was then connected to the heated probe (180 °C), which was used to take undiluted and wet exhaust gas emission from the excavator pipe in where it was pumped to PSS via a 5-m-long heated line (180  °C). From the PSS the gases were directed into Gasmet FTIR gas analyser (180 °C) via a 1-m-long heated line (180 °C). There was a two-stage particulate filtration (particle size 2 mm): the first one was the sampling probe (PTFE), and the second one was in the PSS (stainless steel, RST). Calcmet software was used to collect, store and visualize the FTIR spectra of wet sample gas and to analyse the concentrations of gas components: NO, N2O, NO2, NH3, CO, CO2, CH4, C2H4, C3H8, benzene (C6H14), formaldehyde (CHOH), acetic acid (CH3COOH), dodecane (C12H26), SO2 and water (H2O).

Comparison of Exhaust Gas Emissions Between Autonomous and Human Operator…

55

3 Results and Discussion The exhaust gas emission experiments of the excavator were studied under engine running conditions using thermal IR and photograph images. The visualization of exhaust gas is not very prominent in engine running conditions, as can be seen in Fig. 2a. This may be because the exhaust gas temperature rapidly reaches the ambient temperature. However, it seems that the tin layer insulation of the stainless steel tube between the heated probe and the exhaust pipe was prevented unwanted water condensation (Fig. 2b). Therefore, it can be assumed that the analysed exhaust gas stream was undiluted. The measured results of the Gasmet DX4000 FTIR gas analyser are both qualitative and quantitative. Based on the literature, the results of Gasmet FTIR are suitable for exhaust gas measurement on a laboratory scale [9]. Table  1 shows all measured gases and the maximum concentrations or volumes between autonomous driving and human operator experiments for 0%, 50% and 100% engine speed (rpm), for the boom up experiment, as an example. Fuel-based hydrocarbons (HCs), in other words, methane (CH4), ethylene (C2H4), propane (C3H8), hexane (C6H14), formaldehyde (CHOH), acetic acid (CH3COOH) and dodecane (C12H26), were measured to determine the content of carcinogenic compounds. The concentrations of the HC components were analysed to be all under 10 ppm. In addition, the formation of CO was low, under 2 ppm. This means that diesel was almost completely combusted in the cylinder to CO2 and H2O, as was expected. In addition, the concentrations of ammonium (NH3) and sulphur dioxide (SO2) are under 3 ppm. The reason NH3 was analysed is that the role of NH3 emission is to be the precursor of PM and sulphate (SO42−) formation [25]. In our experiments the particulates were not measured since the excavator has DPF. The emitted SO2 is originated from used diesel fuel with a maximum value of 10  mg/kg (or 10 ppm) of sulphur. Therefore, in this article, the formation of CO2 and H2O emissions, the consumption of oxygen and the formation of NOx, which is a sum of the N2O, NO2 and NO emissions from the fuel combustion process, are studied in more detail.

Fig. 2  The thermal IR image (a) and photograph image (b) of excavator exhaust gas during engine running condition

56

T. Kolli et al.

Table 1  The comparison of Gasmet DX4000 FTIR gas analyser results for autonomous and human operator experiments Autonomous driving (rpm) Analysed compound (volume or concentration unit) 0% 50% 100% H2O (vol-%) 4.0 3.9 3.8 CO2 (vol-%) 3.8 3.6 3.5 O2 (vol-%) 5.7 5.8 5.8 CO (ppm)