Post-Earthquake Fire Assessment of Buildings: Evaluation Framework 0784415994, 9780784415993

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Post-Earthquake Fire Assessment of Buildings Evaluation Framework

Post-Earthquake Fire Hazard Task Group Edited by Negar Elhami-Khorasani, Ph.D.

Post-Earthquake Fire Assessment of Buildings

Other Titles of Interest Fire Following Earthquake, edited by Charles Scawthorn, John M. Eidinger, and Anshel Schiff (ASCE/TCLEE 2005). TCLEE Monograph 26 covers the entire range of fire following earthquake issues, from historical fires to twentieth-century fires in Kobe, San Francisco, Oakland, Berkeley, and Northridge. (978-0-7844-0739-4) Performance-Based Structural Fire Design: Exemplar Designs of Four Regionally Diverse Buildings Using ASCE 7-16, Appendix E, by the American Society of Civil Engineers (ASCE/SEI 2020). Performance-Based Structural Fire Design describes concepts and uses real-world analysis that demonstrates the execution and potential benefits of performance-based structural fire design (PBSFD) for structural fire protection as an alternative to traditional prescriptive procedures. (978-0-7844-8269-8) Tohoku, Japan, Earthquake and Tsunami of 2011: Lifeline Performance, edited by Alex K. Tang (ASCE/IRD 2017). TCLEE 42 presents the results of an extensive investigation into the performance of lifeline infrastructure systems following the 2011 earthquake and tsunami that struck northeastern Japan. (978-0-7844-7983-4) Christchurch, New Zealand, Earthquakes of 2010 and 2011: Lifeline Performance, edited by Alex K. Tang (ASCE/IRD 2016). TCLEE 41 discusses in detail the performance of lifeline infrastructure systems following a series of four significant earthquakes in Christchurch, New Zealand, during 2010 and 2011. (978-0-7844-1421-7) Hyogoken-Nanbu (Kobe) Earthquake of January 17, 1995: Lifeline Performance, edited by Anshel J. Schiff (ASCE/TCLEE 1999). TCLEE Monograph 14 reports on the performance of lifeline systems during and after the HyogokenNanbu earthquake that struck the Kobe, Japan, area on January 17, 1995. (978-0-7844-0408-9)

Post-Earthquake Fire Assessment of Buildings Evaluation Framework Prepared by the Post-Earthquake Fire Hazard Task Group Sponsored by Fire Protection Committee of the Structural Engineering Institute of the American Society of Civil Engineers

Edited by Negar Elhami-Khorasani, Ph.D.

Published by the American Society of Civil Engineers

Library of Congress Cataloging-in-Publication Data Names: Elhami-Khorasani, Negar, editor. | American Society of Civil Engineers, author. Title: Post-earthquake fire assessment of buildings : evaluation framework / prepared by the Post-Earthquake Fire Hazard Task Group ; sponsored by the Fire Protection Committee ; edited by Negar Elhami-Khorasani, Ph.D. Description: Reston, Virginia : American Society of Civil Engineers, [2022] | Includes bibliographical references and index. | Summary: “This book provides background for the analysis, design, and assessment of building structural systems under fire following earthquakes”-- Provided by publisher. Identifiers: LCCN 2021051384 | ISBN 9780784415993 (print) | ISBN 9780784483916 (PDF) Subjects: LCSH: Fire investigation. | Earthquake damage. | Building inspection. | Fire risk assessment. | Fire prevention. Classification: LCC TH9180 .P67 2022 | DDC 363.37/65--dc23/eng/20211208 LC record available at https://lccn.loc.gov/2021051384 Published by American Society of Civil Engineers 1801 Alexander Bell Drive Reston, Virginia 20191-4382 www.asce.org/bookstore | ascelibrary.org Any statements expressed in these materials are those of the individual authors and do not necessarily represent the views of ASCE, which takes no responsibility for any statement made herein. No reference made in this publication to any specific method, product, process, or service constitutes or implies an endorsement, recommendation, or warranty thereof by ASCE. The materials are for general information only and do not represent a standard of ASCE, nor are they intended as a reference in purchase specifications, contracts, regulations, statutes, or any other legal document. ASCE makes no representation or warranty of any kind, whether express or implied, concerning the accuracy, completeness, suitability, or utility of any information, apparatus, product, or process discussed in this publication, and assumes no liability therefor. The information contained in these materials should not be used without first securing competent advice with respect to its suitability for any general or specific application. Anyone utilizing such information assumes all liability arising from such use, including but not limited to infringement of any patent or patents. ASCE and American Society of Civil Engineers—Registered in US Patent and Trademark Office. Photocopies and permissions. Permission to photocopy or reproduce material from ASCE publications can be requested by sending an email to [email protected] or by locating a title in the ASCE Library (https://ascelibrary.org) and using the “Permissions” link. Errata: Errata, if any, can be found at https://doi.org/10.1061/9780784415993. Copyright © 2022 by the American Society of Civil Engineers. All Rights Reserved. ISBN 978-0-7844-1599-3 (print) ISBN 978-0-7844-8391-6 (PDF) Manufactured in the United States of America. 27 26 25 24 23 22    1 2 3 4 5

Contents Post-Earthquake Fire Hazard Task Committee............................................................. vii Executive Summary..................................................................................................................ix Chapter 1  Overview..................................................................................... 1 1.1 Introduction..............................................................................................................1 1.2 Historical Events.......................................................................................................2 1.3 What Causes Fire Ignitions Following an Earthquake?..............................4 1.4 Codes and Provisions.............................................................................................7 1.5 Scope and Objectives............................................................................................8 References............................................................................................................................9 Chapter 2  Fire Following Earthquake at the Building Level.................. 11 2.1 Earthquake Hazard Scenario.............................................................................11 2.2 Building Response to Earthquake: Damage to the Structural System................................................................................................. 12 2.3 Building Response to Earthquake: Damage to the Nonstructural Components.............................................................................. 15 2.3.1 Fire Compartmentation....................................................................... 16 2.3.2 Active Fire Protection Systems.......................................................... 18 2.3.3 Egress Routes........................................................................................... 26 2.3.4 Passive Fire Protection for Structural Elements........................... 28 2.4 Fire Hazard Scenario............................................................................................ 29 2.4.1 Sources of Ignition................................................................................. 29 2.4.2 Overview of Predictive Models for Post-Earthquake Fire Ignitions............................................................................................. 31 2.4.3 Design Fire Scenario.............................................................................. 32 2.5 Building Response to Fire.................................................................................. 33 2.5.1 Background.............................................................................................. 34 2.5.2 Performance-Based Structural Fire Engineering........................ 35 2.6 Building Response to Fire Following Earthquake..................................... 38 2.6.1 Numerical Studies.................................................................................. 38 2.6.2 Experimental Studies............................................................................ 41 2.7 Summary................................................................................................................. 42 References......................................................................................................................... 42

v

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Contents

Chapter 3  Fire Following Earthquake at the Community Level............. 51 3.1 Modeling Approach and Available Platforms............................................ 51 3.2 Ignition..................................................................................................................... 53 3.2.1 Data-Driven Models.............................................................................. 53 3.2.2 Physics-Based Models........................................................................... 55 3.3 Spread...................................................................................................................... 56 3.3.1 Data-Driven Models.............................................................................. 57 3.3.2 Physics-Based Models........................................................................... 57 3.4 Suppression............................................................................................................ 59 3.5 Summary................................................................................................................. 61 References......................................................................................................................... 61 Chapter 4  Recommendations...................................................................65 Index...............................................................................................................69

Post-Earthquake Fire Hazard Task Committee This book was prepared by the Post-Earthquake Fire Hazard Task Group of the ASCE Fire Protection Committee. The list of contributing authors is provided as follows.

Prepared and edited by Negar Elhami-Khorasani, Ph.D., University at Buffalo

Contributing Authors Nicole Braxtan, Ph.D., University of North Carolina at Charlotte Aerik Carlton, Lehigh University Maxwell Coar, Princeton University John Dalton, GCP Applied Technologies Pegah Farshadmanesh, Ph.D., University of Illinois at Urbana-Champaign Praveen Kamath, Ph.D., Holmes Fire Mehrshad Ketabdar, S.E., The Southern California Gas Company Kevin LaMalva, P.E., Warringtonfire Mehrdad Memari, Ph.D., American International Group, Inc.

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Executive Summary The likelihood of fire ignitions following an earthquake increases because of potential earthquake damage to utility lines and the shaking of equipment and furniture inside buildings. The active and passive fire protection systems inside buildings may also be compromised. From the structural engineering perspective, ASCE 7 Appendix E is the current industry standard for the performance-based design of structures for fire exposure. However, this standard does not pertain to posthazard (such as post-earthquake) fires. The standard requires consideration of uncontrolled fire exposure and fulfillment of mandatory performance objectives pertaining to occupant life safety. This book presents a background for the analysis, design, and assessment of building structural systems under fire following earthquake and intends to provide guidance based on the current stateof-the-art practices, applicable building codes, and outcomes of experimental and numerical research results. Although this book primarily focuses on design or assessment for fire following earthquake at the building level, characterization of the hazard involves infrastructure at the community level, and, therefore, dependence on relevant discussions at multiple scales is included. This book provides and discusses the documented observations during historic post-earthquake fires, statistics of the number of ignitions following a sample of past earthquakes, causes of ignition, damage to passive and active fire protection systems inside a building, the application of performance-based design methodology to fire following earthquake, the dependency of fire department response on the level of damage to community infrastructure for successful suppression of fires, and the potential for fire spread between buildings. The last chapter summarizes recommendations and factors that should be considered when assessing or designing for fire following earthquake. Practitioners from the fields of structural engineering and the nuclear industry, as well as first responders, building authorities, risk management, and insurance professionals stand to benefit from the provided information in this book. When designing or evaluating a structure for fire following earthquake, probabilistic performance-based methodology can ideally be used to obtain the full spectrum of potential outcomes. An event tree of potential outcomes can also be set up to examine a series of subsequent events considering the performance of fire safety systems. It should be noted that most fire-rated assemblies are only tested and valid under static conditions. Hence, a fire spread through vertical or horizontal fire-rated barriers is conceivable during a fire after an earthquake because of damage to such barriers from racking loads. The control of fire following an earthquake should be considered beyond the design capabilities of sprinklers. Gravity frames in steel structures are typically more vulnerable than heavier ix

x

Executive Summary

systems such as moment-resisting frames, which have some reserved capacity because of a larger section size, a larger thermal mass, and a lower utilization ratio under gravity loads. Mitigation actions at the community level, such as automatic gas shutoff valves and backup water supplies, can reduce the potential for fire ignition and fire spread after an earthquake.

CHAPTER 1

Overview

1.1 INTRODUCTION The built environment has been experiencing more intense and frequent natural and man-made hazards in recent years. Meanwhile, our communities are expected to perform reliably and maintain functionality during such extreme events. This book focuses on post-earthquake fires, as an extreme event and studies how new and existing buildings can be designed or retrofitted for robust performance under fire following earthquake (FFE). According to historical data, ruptured gas lines, electric arcing, and toppled furniture can lead to fire ignitions after an earthquake. Meanwhile, organization disruptions following an earthquake, blocked transportation networks, interruption in communication lines, and reduced water supplies increase the firefighters’ response time and reduce their efficacy, all of which can increase the level of fire spread, and in some cases, result in an urban conflagration. Tall buildings can be at a higher risk of FFE given their higher occupancy loads, lengthier evacuation times, and relatively high level of reliance on active fire protection systems. Notably, the presence of a sprinkler system does not guarantee fire prevention after an earthquake (Taylor 2003), considering that the control of FFE is beyond the design capabilities of sprinklers. For instance, fire sprinkler systems can be damaged during an earthquake, and in the absence of these systems, fire may spread relatively unimpeded within the building. In addition, compartmentation is important for controlling fire spread, and damage to walls and partitions can cause loss of integrity in fire separation systems. In the case of high-rise buildings, occupants could be at a higher risk because potential damage to passive and active fire protection, damage to egress routes or obstacles in the path of egress, and delayed response of firefighters would impede evacuation while the fire spreads within the building. Wind pressures at the upper floors of tall buildings and the potential natural airflow can accelerate fire spread. Vertical fire spread is also possible through the exterior façade (e.g., Grenfell Tower fire in the United Kingdom), and depending on the distance, between openings in the external walls. A few notable scenario studies exist to assess earthquake potential damage to communities from an earthquake in North America, namely, the Shakeout (Scawthorn 2008) and HayWired (USGS 2018) earthquake scenarios 1

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in California; the hazard mitigation plan seismic study of the New York-New Jersey- Connecticut area (NYCEM 2003); and the study prepared for the Institute for Catastrophic Loss Reduction in the Montreal region of Canada (Scawthorn 2019). All three scenarios included post-earthquake fires as a cascading hazard and reported potentially significant losses in terms of the number of damaged structures because of a large number of fires and possible conflagrations. The goal of this book is to put forward a background for analysis, design, and assessment of building structural systems under FFE and to help project stakeholders make proper decisions for enhanced performance, increased capacity, and optimized solutions for new and existing structures subjected to FFE. This book is intended to provide guidance based on current state-of-the-art practices, applicable building codes, and outcomes of experimental and numerical research results. Although the primary focus of the book is at the building level, FFE, in general, involves community-level infrastructure, and therefore, relevant discussions at multiple scales are included.

1.2  HISTORICAL EVENTS Fire following earthquake (FFE) is defined as a fire that cascades an earthquake event, is ignited because of earthquake damage to infrastructure or building contents and requires fire department intervention given that automatic fire suppression measures are rendered ineffective or nonoperative. Fire ignitions have been observed in a number of historical earthquake events. Table 1-1 lists a sample of historical FFE events from different countries. A more comprehensive list is provided in Elhami-Khorasani and Garlock (2017). The 1906 San Francisco earthquake is one of the famous historical cases where a fire caused more damage than the earthquake itself. It has been argued that our communities have evolved since the early 1900s, and similar events would not occur nowadays. Although advancements in construction, backup water resources, and preventive measures such as automatic gas shutoff valves would reduce the risk of post-earthquake fires, Table 1-1 highlights the fact that FFE could still be a problem in modern times as it is evident by the 2011 Great East Japan earthquake, where a large number of fires ignited after the earthquake (not including those caused by the tsunami that followed the earthquake). As another example, the 1999 Marmara earthquake in Turkey caused damage in a petroleum refinery that led to a fire burning for several days. The damage caused by the fire in the refinery led to major economic losses. Figure 1-1 shows the number of ignitions in 19 historic events, grouped based on the year of the event and differentiated based on the country and earthquake magnitude. It can be observed that a relatively large number of ignitions were reported between the years 1970 and 2000 in the United States (including San Fernando, Morgan Hill, Whitter Narrows, Loma Prieta,  and Northridge earthquakes). The lower number of ignitions for earthquakes in the range of 7 to 8 Mw does not necessarily imply that such intensity leads to a lower number

USA

USA

USA

San Francisco

Loma Prieta

Northridge

7.8–8.3

Japan

Tohoku (Great-East Japan)

Source: Elhami-Khorasani and Garlock (2017), Himoto et al. (2014).

9

August 1999 7.4

Turkey

Marmara

March 2011

January 1995 6.9

Hanshin (Kobe) Japan

January 1994 6.7

304

Petroleum refinery fire

108

110

26

52

28,000 buildings destroyed >12.2 km2 of burnt area 3,000 fatalities Severe fire in a 4-story building could potentially lead to conflagration Only backup to the backup water system worked 86% of fires were structural fires The majority of fires were confined to the building of origin Several conflagrations within 1 to 2 h of the earthquake 97% of fires were structural 5,000 buildings were destroyed A total of 17 naphtha tanks were lost during the fire The fire burnt for several days Major economic loss Fire because of earthquake or tsunami that followed the earthquake 188 Fires in the inland area that were not affected by the tsunami 80% of earthquake-related ignitions were structure fires

Magnitude (Mw) No. of ignitions Comments

October 1989 7.1

April 1906

Country Date

Event

Table 1-1.  A Sample List of Historical Earthquake Events Followed by Fire Ignitions.

Overview

3

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Post-Earthquake Fire Assessment of Buildings

Figure 1-1.  Post-earthquake ignitions in historical events grouped based on (a) earthquake year, (b) earthquake magnitude. of ignitions, as there are a limited number of earthquake events for the given magnitude range. No major earthquake has happened in the United States in recent years, and therefore, a comment cannot be made on the effectiveness of implemented mitigation and safety measures for the post-Northridge earthquake.

1.3 WHAT CAUSES FIRE IGNITIONS FOLLOWING AN EARTHQUAKE? A number of workshops and research projects, as well as insurance industry studies, have been completed on the topic of FFE to investigate the major causes

Overview

5

of post-earthquake fires and their consequences for citizens and the communities in general. Short-circuiting in electric systems and rupture of gas distribution systems, either inside buildings or across the infrastructure network within the community, have been recognized as the major causes of ignitions after an earthquake. In addition, damage to sprinkler systems, passive fire protection systems, and various structural and nonstructural building elements lead to fire spread within a structure, whereas damage to the water distribution system disrupts firefighting efforts. During past earthquakes, fire protection systems were unable to prevent fire spread in many cases, primarily because of failed sprinkler piping systems (e.g., inadequate bracing of pipes), inadequate anchorage of tanks and pumps, and loss of compartmentation (Chung et al. 1995). Reports from the Southern California Gas Company (SoCalGas) indicate that post-earthquake natural gas–induced house fires were caused by either failure of natural gas appliances or damaged structures that were detached from their foundations, causing excessive deflections, and leading to gas pipeline failures or gas leaks. Approximately 172 mobile homes were destroyed because of fires caused by natural gas leaks during the Northridge earthquake. In addition, SoCalGas reported about 2,500 water heaters were damaged during the Northridge earthquake. About 35% to 40% of the 47 fires reported in Southern California, which were attributed to natural gas–related structural fires, were due to the failure of water heaters (Chung et  al. 1995). Also, ruptured transmission and distribution gas pipelines can serve as a fuel source for an electric spark from a nearby damaged electrical wiring system causing an ignition. Cracked bottles or open containers of flammable liquids, spilling out during the earthquake, can add to the fuel source if exposed to an open gas flame or an electric spark that ignites the vapors from the spilled liquid (SSC 2002). Apart from natural gas, other sources of fuel may include but not limited to, cooking oils and other kitchen fuels spilling during an earthquake. Table 1-2 lists the number of natural gas–related fires for historic earthquakes compared with the total number of post-earthquake fires. Electrical faults were thought to have been a significant cause of fires following the Kobe earthquake in 1995, whereas approximately 110 structurally significant fires were recorded Table 1-2.  Number of Ignitions as a Result of Natural Gas. Earthquake event and date

Gas-related ignitions out of the total number of ignitions

Anchorage 1964 San Fernando 1971 Palm Springs 1986 Whittier Narrows 1987 Loma Prieta 1989 Northridge 1994 Kobe 1995

0 out of 7 15 out of 109 0 out of 3 3 out of 4 16 out of 67 54 out of 110 36 out of 205

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Post-Earthquake Fire Assessment of Buildings

following the Northridge earthquake, of which 54 fires were associated with gasrelated events (Honegger 1995). It is believed that the Northridge earthquake was one of the few well-documented earthquakes in the United States with regard to post-earthquake fires. In general, statistical analyses show that natural gas accounts for 15% to 50% of post-earthquake fires (Honegger 1995). Based on data obtained from the Los Angeles Fire Department after the Northridge earthquake, 18% of gas-related fires in Los Angeles (5 out of 27) have been caused by gas appliances, whereas 59% of gas-related fires (16 out of 27) were caused by water heaters. Overturning and sliding are two failure modes of water heaters during an earthquake. Mechanical straps mitigate these two failure modes. For an unrestrained water heater, failure is initiated when inertia loads overcome the static friction between the water heater and the base on which it stands. Also, sliding and overturning of gas appliances during an earthquake are the primary causes of gas leaks. Typically, damage occurs when there is a lack of flexibility in the connection between gas appliances and the gas supply pipeline. Relative displacement between the appliance and the attached piping causes the pipes to rupture. During the Northridge earthquake, the volume of gas leakages was lower than the limit required to pose an imminent threat. The gas concentration in the potentially ignitable mixture should be at least 5% to pose an ignition threat. This can occur locally in the presence of an ignition source such as a pilot light. Explosive gas mixtures require gas concentrations in the order of two to three times as high, or at least 10% to −15% gas concentration. Because natural gas is lighter than air and tends to disperse, the rate of gas leakage with the potential to produce a gas explosion is related to the air exchange rate in the area where the leakage is taking place. The degree of correlation between these two flow rates is dependent on whether poor air mixing can cause pockets of gas to accumulate. Recently, the application of earthquake shutoff switches for electrical systems and earthquake shutoff valves for gas lines has become popular and effective in reducing the likelihood of ignition. An earthquake could interrupt the power service and cause a blackout, whereas an electric-powered device inside a building could be displaced, coming into contact with a quantity of fuel. When power is restored to the building, the device can cause the flammable fuel to ignite. An electric shutoff switch de-energizes local electrical systems and thereby reduces or eliminates the potential for ignition. Also, an electric shutoff switch would de-energize local electrical systems allowing for a safe inspection before the system is re-energized. Besides the electric shutoff switches, the seismic gas shutoff valves offer the potential to reduce the number of fire ignitions because of natural gas leaks. The proper stability design of water heaters and gas appliances may also reduce the likelihood of ignition (Chung et al. 1995). A recent study on a 6-story building equipped with appliances has highlighted the potential risk of fuel ignition following an earthquake, as the various appliances placed in the building were prone to large movements, bracing or restraint failure, and tipping in some cases (Wang et al. 2016).

Overview

7

Overall, restraining water heaters, gas appliances, and using shutoff valves can reduce a significant number of fire ignitions because of natural gas. In general, other factors such as unoccupied buildings, areas with high building density, high wind, low humidity, damage to the water system, and reduced firefighter responsiveness can lead to more severe damage and fire spread after an earthquake.

1.4  CODES AND PROVISIONS The structural design for seismic loading is well developed and ubiquitous. However, researchers, stakeholders, and policymakers are still appraising the impact of earthquakes on key nonstructural components. Oftentimes, the severity of FFE and its evolution, once started, are highly influenced by the integrity of nonstructural components. From a fire protection engineering perspective, some specific code provisions exist that pertain to fire hazards posed by seismic events. A fire sprinkler system design is typically governed by the National Fire Protection Association (NFPA 2019) standard: “NFPA 13 Standard for the Installation of Sprinkler Systems.” This standard has prescriptive requirements to satisfactorily brace the sprinkler system piping to protect against pipe rupture during seismic events where required. Such measures, in general, reduce the risk of pipe rupture and an uncontrolled fire after an earthquake, granted that the fire sprinkler system maintains the required hydraulic capacity. However, the hydraulic capacity of sprinkler systems is not influenced by the risk of a seismic event (e.g., large fires and/or fires in multiple locations) but is based on ordinary fire growth/severity within one location. Hence, the prevention of sprinkler pipe rupture does not necessarily equate to control of FFE but rather a mitigation of the risk. Other fire-related code provisions are more subtle, such as the required allowance for fire-rated joint systems to undergo expansion/contraction. Most fire-rated assemblies are only tested and valid under static conditions (i.e., stationary furnace boundaries). For instance, racking loads on fire barriers and associated fire doors is not contemplated implicitly or explicitly. Hence, a fire spread through vertical fire-rated barriers is conceivable during an FFE because of damage to such barriers from racking loads. From a structural engineering perspective, ASCE 7-16, Minimum Design Loads and Associated Criteria for Buildings and Other Structures (ASCE 2017), Appendix E, provides a framework for the performance-based evaluation of structural fire safety. However, this standard does not pertain to posthazard event fires. Specifically, the mandatory performance objectives of this standard address occupant life safety only and require contemplation of uncontrolled fire exposure in isolation, rather than in conjunction or as a result of another hazard event such as a blast or an earthquake. National Fire Protection Association (NFPA) and Society of Fire Protection Engineers (SFPE) standards pertaining to fuel load (NFPA 557), fire exposure (SFPE S.01), and thermal response (SFPE

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Post-Earthquake Fire Assessment of Buildings

S.02) also do not directly address post-earthquake fire exposure. However, there is nothing in these standards that would preclude the analysis of structural response to such a case. Notably, ASCE 7 Appendix E provides a section on discretionary performance objectives, of which post-earthquake fire exposure could be contemplated. Accordingly, the risk associated with post-earthquake fires and the necessity to consider such scenarios should be determined by the project stakeholders, including the building authorities.

1.5  SCOPE AND OBJECTIVES Figure 1-2 provides a schematic overview of FFE elements that are involved at building and community scales, depicting how the interaction between structural and nonstructural building components, lifeline networks, and community-level parameters influence ignition, spread, and suppression of fire. The remaining chapters of this book provide a state-of-the-art review of design and assessment frameworks for FFE, and recommendations are made on the mitigation of FFE risks at the building level. Practitioners from the fields of structural engineering and nuclear industry, as well as first responders, building authorities, risk management, and insurance professionals, stand to benefit from such guidance. The book consists of three main chapters: Chapter 2 focuses on the building response to earthquake and fire and describes the performancebased design for FFE. Chapter 3 describes FFE within a community context and discusses the three phases of ignition, spread, and suppression across a region. Chapter 4 provides design recommendations for improved resilience of buildings to FFE.

Earthquake scenario

Bldg response (e.g. drift)

Dmg to egress routes

Dmg to active fire prevention system

Dmg to fire compartmentation

Dmg to passive fire protection

Availability of fuel source

Fire spread inside bldg

Fire scenario

Power availability

Ignition

Water availability

Spread btw bldgs

Roadway accessibility

Firefighters’ response

Dmg to structural components

Bldg fire response

Natural/built environment Wind

Suppression

Figure 1-2.  Schematic overview of FFE at building and community scales—pink and blue relate to performance at building level for structural and nonstructural components, and green relates to lifeline networks and community-level parameters.

Overview

9

References ASCE. 2017. Minimum design loads and associated criteria for buildings and other structures. ASCE/SEI 7-16. Reston, VA: ASCE. Chung, R. M., N. H. Jason, B. Mohraz, F. W. Mowrer, and W. D. Walton. 1995. Postearthquake fire and lifelines workshop; Long Beach, California January 30–31, 1995. NIST Special Publication 889. Gaithersburg, MD: National Institute of Standards and Technology. Elhami-Khorasani, N., and M. E. Garlock. 2017. “Overview of fire following earthquake: Historical events and community responses.” Int. J. Disaster Resil. Built Environ. 8 (2): 158–174. Himoto, K., M. Yamada, and T. Nishino. 2014. “Analysis of ignitions following 2011 Tohoku earthquake using Kawasumi model.” In Proc., 11th Int. Symp., International Association for Fire Safety Science, 704–717, University of Canterbury, Christchurch, New Zealand. Honegger, D. G. 1995. Automatic gas shutoff device actuation requirements based on damage in the January 17, 1994 Northridge earthquake. Report Prepared for ASCE, EQE International Report 52316.01, Irvine, California. NFPA (National Fire Protection Association). 2019. Standard for the installation of sprinkler systems. NFPA 13. Quincy, MA: NFPA. NYCEM (New York City Area Consortium for Earthquake Loss Mitigation). 2003. Earthquake risks and mitigation in the New York, New Jersey, Connecticut Region. Rep. No. MCEER-03-SP02. New York: NYCEM. Scawthorn, C. R. 2008. The ShakeOut scenario supplemental study—Fire following earthquake. Prepared for US Geological Survey, Pasadena, CA and California Geological Survey, Sacramento, CA. Berkeley, CA: SPA Risk, LLC. Scawthorn, C. R. 2019. Fire following earthquake in the Montreal region. ICLR Research Paper Series Number 63. Prepared for the Institute for Catastrophic Loss Reduction. Toronto: Institute for Catastrophic Loss Reduction. SSC (Seismic Safety Commission). 2002. Improving natural gas safety in earthquake. Prepared by ASCE 25 Task Committee on earthquake safety issues for gas systems, SSC-02-03. Sacramento, CA: SSC. Taylor, J. 2003. Post earthquake fire in tall buildings and the New Zealand building code. Fire Engineering Research Rep. 03/6. Christchurch, New Zealand: University of Canterbury, School of Engineering. USGS (United States Geological Survey). 2018. The HayWired earthquake scenario—We can outsmart disaster. Fact Sheet 2018-3016. Reston, VA: USGS. Wang, X., T. C. Hutchinson, G. Hegemier, S. Gunisetty, P. Kamath, and B. Meacham. 2016. Earthquake and fire performance of a mid-rise cold-formed steel framed building—Test program and test results: Rapid release (preliminary) report. SSRP-2016/07. San Diego, CA: University of California.

CHAPTER 2

Fire Following Earthquake at the Building Level

2.1  EARTHQUAKE HAZARD SCENARIO The response of a building during an earthquake, when/if a structure is damaged because of shaking, will affect building performance under fire following earthquake (FFE). As discussed later in this chapter, damage to structural and nonstructural components (e.g., sprinklers, fire doors, ceiling panels, passive fire protection) is related to the amount of drift or floor acceleration because of the earthquake. Damage to structural systems may compromise fire-rated assemblies of buildings, whereas passive fire protection could delaminate or dislodge during earthquakes, especially when excessive deformations are experienced. It is, therefore, necessary to perform a seismic analysis of the structure to quantify interstory drift, floor acceleration, and potential structural damage before conducting a fire analysis. Provisions and design guidelines offer different analysis procedures to determine the seismic performance of a building. These procedures can be grouped into linear versus nonlinear analysis and static versus dynamic analysis. The two most commonly used methods are the equivalent lateral force and response spectrum analysis, both based on linear methods. The equivalent lateral force method is perhaps the simplest procedure to perform seismic analysis for structures with regular characteristics, where the effect of an earthquake is assumed to be equivalent to transverse static loading. The response spectrum method is also widely used for the design and analysis of structures subjected to an earthquake. This approach provides the maximum structural response, rather than the response for the full duration of the earthquake. This is a linear approximation that is based on a modal analysis of the structure. Alternatively, linear or nonlinear time–history analysis can be conducted where loading and response history are evaluated at time increments for the full duration of the earthquake. The nonlinear behavior of the structure can be captured by adjusting the strength and stiffness properties of structural elements.

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Post-Earthquake Fire Assessment of Buildings

ASCE 7 (ASCE 2017) and the NEHRP Recommended Provisions for Seismic Regulations for New Buildings and Other Structures (FEMA 2015) provide details of seismic design criteria and requirements. ASCE 7 provides the basis for ground motion criteria and site-specific maps of seismic intensity. Alternatively, the performance of a building can be assessed for a set of predefined ground motions that are systemically scaled, as described, for example, in FEMA P695, Quantification of Building Seismic Performance Factors (FEMA 2009c).

2.2 BUILDING RESPONSE TO EARTHQUAKE: DAMAGE TO THE STRUCTURAL SYSTEM Building response to an earthquake is dependent on the characteristics of the structure, including mass, stiffness, size, and shape. Buildings are designed to experience some damage during a strong earthquake event but not collapse. This expected damage is crucial in the understanding of post-earthquake fire performance because the damaged structure is more vulnerable to fire than a similarly undamaged structure. Damage owing to earthquakes can be quantified through an explicit analysis of the structure under earthquake scenarios. Performance-based design (PBD), a well-established framework in earthquake engineering, provides an opportunity for structural engineers to assess the behavior of a structural system subjected to a series of ground motions to meet the target design objectives. The process involves evaluating the performance of alternate design options to meet predefined objectives and identify an efficient solution. PBD aims to achieve a design that satisfies the needs of owners/ stakeholders with regard to performance objectives that are set for different hazard intensities. PBD in earthquake engineering involves four primary domains: • Hazard: This domain studies the annual rate of exceeding various levels of the hazard. In the case of seismic hazard, the recurrence rate of a particular magnitude of ground motion, site conditions, site distance, and fault characteristics near the structure are considered in creating the hazard curve. • System: A numerical model of the structural system is analyzed in this domain under a wide range of hazard intensities. Uncertainties in the response of the structural system to seismic demand are determined. Response parameters (such as interstory drift) that are used to quantify damage in the structural system are characterized as engineering demand parameters (EDPs). • Damage: The EDPs from the system domain are employed to determine the level of damage in the system, represented by the probabilities of various levels of damage for a given level of seismic excitation. • Loss: The probabilistic evaluation of performance is characterized by monetary terms. Decision makers use the loss function to assess the seismic performance of a structure during its service life.

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Equation (2-1) expresses the mathematical form of performance-based earthquake engineering by the Pacific Earthquake Engineering Research (PEER) center, as previously outlined. In the equation, g indicates the annual rate of an event, p denotes the complementary cumulative distribution function of an event, IM is the intensity measure of the earthquake (e.g., spectral acceleration), EDP is the engineering demand parameter (e.g., interstory drift ratio), DM is the damage measure (e.g., 5% interstory drift ratio as the collapse limit state for steel buildings), and DV is the decision variable (e.g., cost in dollar value). The subscript E denotes the earthquake hazard. g (DVE ) = ∫ ∫ ∫ p(DVE | DM E ) ⋅ p(DM E | EDPE ) ⋅ p(EDPE | IM E ) ⋅ d(DM E )d(EDPE ) × d(IM E ) (2-1)  FEMA P-750 (FEMA 2009b) describes target building performance levels based on expected ground motion events for different occupancy categories, as shown in Figure 2-1. The likelihood of ground motion varies from a frequent seismic event to design basis earthquake to the maximum considered earthquake (MCE). Building performance levels are organized based on damage levels: operational (very light damage), immediate occupancy (light damage), life safety (moderate damage), and collapse prevention (severe damage). FEMA 356 (FEMA 2000) further characterizes damage states for both vertical and horizontal elements in lateral force–resisting systems for primary and secondary components

Figure 2-1.  Expected building performance level based on earthquake ground motion and building occupancy type. Source: FEMA (2009b).

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Post-Earthquake Fire Assessment of Buildings

Table 2-1.  Interstory Drifts for Different Structural Systems and Different Building Performance Levels. Element Concrete frames Steel moment frames Braced steel frames Concrete walls Unreinforced masonry infill walls Unreinforced masonry noninfill walls Reinforced masonry walls Wood stud walls

Immediate occupancy 1% Transient negligible permanent 0.7% Transient negligible permanent 0.5% Transient negligible permanent 0.5% Transient negligible permanent 0.1% Transient negligible permanent 0.3% Transient 0.3% permanent

Life safety

Collapse prevention

2% Transient 1% permanent

4% Transient or permanent

2.5% Transient 1% permanent

5% Transient or permanent

1.5% Transient 2% Transient or 0.5% permanent permanent 1% Transient 2% Transient or 0.5% permanent permanent 0.5% Transient 0.6% Transient 0.3% permanent or permanent 0.6% Transient 1% Transient or 0.6% permanent permanent

0.2% Transient 0.6% Transient 1.5% Transient 0.2% permanent 0.6% permanent or permanent 1% Transient 2% Transient 3% Transient or 0.25% 1% permanent permanent permanent

Source: Reproduced from FEMA 356 (FEMA 2000).

and provides typical values for transient and permanent drift. Permanent drift is a major factor for post-earthquake fire assessment because this geometric damage parameter can be related to the fire performance of the structure (Della Corte et al. 2003, 2005). Modern structures are designed to accommodate large deformations during strong earthquake ground motions. These deformations are typically represented as interstory drift. For example, ductile steel moment frame structures may exhibit approximately 5% drift at the collapse prevention damage level. Table 2-1 summarizes typical story drifts associated with various structural systems for different building performance levels. Additional earthquake-induced damage may be present as structures are loaded into the plastic range. This may include yielding and local buckling of components, plastic hinge formation, cracking, or fracture. For example, of particular consideration in concrete structures is spalling, as loss of concrete cover increases fire effects on steel reinforcement, and

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the overall loss of gross reinforced concrete sections leads to the decreased loadcarrying capacity of the members. In addition, repeated plastic deformations may cause a reduction in the mechanical properties of the material.

2.3 BUILDING RESPONSE TO EARTHQUAKE: DAMAGE TO THE NONSTRUCTURAL COMPONENTS In addition to the structural system, nonstructural components in a building may also experience significant damage, potentially increasing the risk of structural fire (e.g., toppled fuel loads, modified compartment characteristics). In general, building fire safety includes (1) passive fire protection, (2) active fire protection systems, and (3) fire safety management (Chow 2005). Passive fire protection systems (e.g., fireproofing materials) are built into the structure and, therefore, do not need to be activated to serve their purpose during a fire. The choice of construction materials and interior linings influences passive fire control, which plays an important role in reducing the growth of preflashover fires (Buchanan and Abu 2017). Once a flashover occurs, structures and assemblies with sufficient fire resistance can potentially control the spread of fire. Active fire protection systems (e.g., smoke detectors, exhaust fans, sprinklers) need to be activated once a fire starts (Buchanan and Abu 2017). An effective building fire safety management should outline warning systems, evacuation procedures, and fire prevention strategies (Chow 2005). Because of potential damage to active and passive fire protection systems, limited availability of fire services, and the increased probability of fire ignition following an earthquake, the likelihood of damage from FFE is more than that of fire during normal conditions (Buchanan and Abu 2017, Spearpoint 2008). The dependency of active fire protection systems on the availability of power and water supplies, along with the potential for disruption because of structural and nonstructural damage within a building, needs to be considered when developing fire risk mitigation strategies for FFE scenarios. Although building codes may require standby/emergency backup power sources to support active fire protection systems (e.g., in high-rise buildings over 75 ft in height), many buildings still require external power for the operation of these fire systems. Consideration of local water tanks or long-duration backup electric power systems at the planning phase for new buildings or during renovations for existing buildings can reduce the risk of FFE. In 2012, the collaboration of industry, government, and five universities completed a series of full-scale experimental tests on a large outdoor shake table at the Englekirk Structural Engineering Center at the University of California, San Diego (Hutchinson et al. 2013). The experiment studied the performance of nonstructural building systems and post-earthquake fire performance of a 5-story reinforced concrete frame. The results of the fire test after shaking showed that automatic sprinkler systems (with appropriate lateral bracing), fire dampers,

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and roll-down fire doors, in general, performed well. However, the separated joint seals and significant gaps between balloon framing and slabs could potentially lead to loss of compartment integrity, and consequently, the spread of fire. Loss of windows could also spread the fire from floor to floor, and jammed doors and detached stairs could potentially hinder occupants from evacuation (Meacham 2016, Meacham et al. 2013). Shaking during the experiment caused the loss of compartmentation, resulting in the spread of smoke during an experimental fire scenario that followed the shaking (Meacham 2016). In general, of interest to FFE risk assessment are the damage to nonstructural components that may impact the spread of fire (through damage to compartmentalization), the fire performance of the structure (through damage to passive fire protection systems), and evacuation strategies for occupants (damage to egress routes). The rest of this section focuses on the potential damage to nonstructural components related to (1) fire compartmentalization, (2) active fire protection systems, (3) egress routes, and (4) passive fire protection systems.

2.3.1  Fire Compartmentation Fire compartmentation divides a building into separate units and is a critical part of the design to confine the fire and prevent fire spread within the building. Components of fire compartmentation include fire barriers, fire doors, firerated floor assemblies, firewalls, fire-rated corridor enclosures, and stairs. Compartmentation is meant to impede the spread of fire and smoke, divide a building into separate manageable areas in terms of fire risk, provide sufficient means of escape, and improve fire and rescue services (Rowan 2012). A fire compartment can be more accurately defined as a building or part of a building comprising one or more rooms, spaces or stories constructed to prevent the spread of fire to or from another part of the same building or an adjoining building. […] a separated part of a building is a form of compartmentation in which part of a building is separated from another part of the same building by a compartment wall. Such walls run the full height of the part and are in one vertical plane. (Ministry of Housing, Communities and Local Government 2010) Buchanan and Abu (2017) list the advantages of compartmentations as isolating a fire and limiting the area of possible loss, reducing potential structural damage caused by fire, increasing time for occupants to escape, protecting escape routes, and separating different occupancies. A collaborative research team, including the University of Canterbury, the Fire Protection Association of New Zealand (FPANZ), and the BRANZ research organization, investigated the post-earthquake fire performance of fire protection systems after the 2010 and 2011 Christchurch, New Zealand, with magnitudes of 7.1 and 6.3, respectively (Baker et al. 2012, Collier 2013). The research focused on both active fire protection systems and compartmentalization, including fire doors and firewalls. Several types of damage to fire doors were identified (e.g., gaps around door leaf, diagonal cracking, and gaps along the frame and lining),

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Figure 2-2.  Damage to a fire door during inspections following the 2011 Christchurch earthquake. Source: Images taken from Baker et al. (2012).

an example of which is shown in Figure 2-2. When inspecting the fire doors, gaps around door jambs were found to have increased from 2 to 3 mm to 4 to 16 mm. In addition, compartmentation damage, including separation of the fire-rated lining from the framing, damage at the junction of stairs and the fire-rated walls, and gaps in fire-rated escape stairwells, were observed (Figure 2-3) (Baker et al. 2012). Two other research projects that found similar types of damage in simulated shake table tests worth reporting are studies by Meacham (2016) and Wang et al. (2016). The former project observed the demerits of balloon framing that lead to the loss of compartmentalization (Meacham 2016). Wang et al. (2016) conducted a series of earthquake tests on a 6-story lightweight cold-formed steelframed building with passive fire protection products such as fire-rated gypsum wallboards, fire doors, and fire stops. The observations from these tests showed significant damage to the passive fire protection products that could lead to a loss of compartmentalization (Kamath and Meacham 2017). Rupture of joint

Figure 2-3.  Damage to (a) fire-rated wall, (b) stair soffit, (c) stairwell, identified during inspections following 2011 Christchurch earthquake. Source: Images are taken from Baker et al. (2012).

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Post-Earthquake Fire Assessment of Buildings

Figure 2-4.  Damage to passive fire protection during an experimental study of a 6-story cold-formed steel building (a) boundary crushing, (b) full-height cracking, (c) paper tape rupture, (d) corner gapping, (e) door frame distortion. compound and paper tape finish at the joints between gypsum boards, full-height cracking, and corner crushing were reported at multiple locations within the building (Figure 2-4). Loss of bond between the gypsum boards and the steel studs was also observed owing to loosening or withdrawal of fasteners (self-drilling, self-tapping screws). Punching of the gypsum wallboard on the upper level was also reported owing to large diaphragm displacement resulting in the snapping of a braced appliance. Any damage to the gypsum board results in compromise of fire protection to the underlying structural framing in the event of a fire. In general, the fire control systems performed well without any damage.

2.3.2  Active Fire Protection Systems Failure of active fire protection systems during an earthquake can endanger the safety of occupants and cause substantial property damage. Therefore, vulnerabilities of these safety systems and their potential failures during an

Percentage of Damages to Fire Safety Systems

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45% 40% 35% 30% 25% 20% 15% 10% 5% 0%

Sprinkler

Fire Doors

Foam Extinguishing System

Indoor Fire Hydrant

Automatic Fire Emergency Halogenated Alarm Generator Unit Extinguishing System

Types of Protection System

Figure 2-5.  Percentages of damage to fire safety systems during the 1995 Kobe earthquake. Sources: Adapted from Behnam (2017), Sekizawa et al. (2003).

earthquake need to be evaluated. To improve coordination between the seismic and fire designs, it is necessary to ensure (1) proper seismic design of active and passive fire protection systems, (2) adequacy of fire protection of seismic components (e.g., joint systems), and (3) availability of water supply after an earthquake (Spearpoint 2008). For example, the New Zealand sprinkler standard, NZS 4541, requires the seismic design of sprinkler systems and the provision of independent water supply for residential buildings (Spearpoint 2008). Rashid et al. (2018) discussed standards for the design and installation of automatic fire sprinkler systems. Figure 2-5 summarizes the percentages of damage to different fire safety systems during the 1995 Kobe earthquake (Behnam 2017, Sekizawa et al. 2003), with the most observed damage in sprinkler piping (41% of inspected piping was damaged). Similarly, investigations after the 2010 and 2011 Christchurch earthquakes identified a series of damage to the active fire protection systems, including water supply, sprinkler piping, and alarm system components, as listed in Table 2-2. Examples of potential solutions for reducing the probability of major losses on account of FFE include provisions of secondary water supplies for sprinkler systems and alternate water supplies for firefighting based on earthquake loads and fire safety design considerations (Spearpoint 2008). Sprinklers can be categorized as wet pipe sprinklers, dry pipe sprinklers, preaction sprinklers, deluge systems, drencher systems (which aim to reduce the probability of fire spread among adjacent buildings), foam water systems, and water mist systems (Spearpoint 2008). Figure 2-6 shows the details of a fire sprinkler system, including the water supply line, sprinkler head, alarm valve, and system piping (Tian et al. 2013). The two primary failure modes of sprinkler systems during an earthquake include sprinkler component failures and/or the

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Post-Earthquake Fire Assessment of Buildings

Table 2-2.  Damage to Active Fire Protection Systems after the 2010 and 2011 Christchurch Earthquakes. Active fire protection systems

Observed damaged after the 2010 Christchurch earthquake

Water Supply

In the central business district (CBD) area: • Temporary disruptions to water supply (2010) • Main water supply to the Christchurch CBD was significantly disrupted (some areas for over a year, some for days or weeks) (2011)

Sprinklers

Alarm systems

In surrounding/rural areas: • Concrete water tanks performed well (popular 0.25 g (m/s2) 0.35–0.9 g (m/s2)

Source: Park et al. (2014).

LeGrone (2004) utilized various data sources to categorize the performance of sprinkler systems during historic earthquakes. The author listed three common failure modes for sprinkler systems during earthquake intensities over M6.0: (1) failure of threaded fittings of the system, (2) failure of longitudinal bracing, and (3) damage owing to contact with the drop-down ceiling system (LeGrone 2004). The longitudinal bracing (parallel to the piping) and transverse bracing (perpendicular to the piping) are, in general, utilized to support pipings against earthquake shaking (Tian et  al. 2013). Figure 2-9 shows seismic braces for restraining sprinkler pipes (Malhotra et al. 2003). Experimental studies also investigated the performance of buildings’ nonstructural components and systems during an earthquake and postearthquake fires (Meacham 2016, Meacham et  al. 2013, Park et  al. 2014). A series of shake table tests were conducted on a full-scale, 5-story building to evaluate the potential smoke and fire spread caused by shaking. According to Meacham (2016), a functional wet-pipe automatic sprinkler system was installed with different pipe materials and layouts to assess the performance of different sprinkler configurations during an earthquake. The authors emphasized that the good performance of sprinkler systems observed during the test could be related to hangers, bracing, and other components that were installed according to current regulatory requirements (Meacham 2016). Tian et al. (2013) conducted experiments at the Structural Engineering and Earthquake Simulation Laboratory (SEESL) of the State University of New York at Buffalo to evaluate the dynamic characteristics of fire sprinkler piping systems subjected to seismic loading (Tian et al. 2013). As part of the study, a simulation methodology for fire sprinkler piping systems was developed (Soroushian et al. 2014). This study covered eight classes of piping with varying braces, weights, joints, and brace locations. It was concluded that piping mains with grooved type joints were more vulnerable compared with threaded joints. The probability of

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Post-Earthquake Fire Assessment of Buildings

Table 2-4.  Observed Damage in Fire Sprinkler Systems During Historic Earthquakes. Earthquake

Damage to fire sprinkler systems

1933 Long Beach

20% of the 150 sprinkler systems in the area, where the earthquake caused major structural damage, experienced serious damage. No damage was observed in the 350 sprinkler systems at areas with lower seismic intensity (LeGrone 2004) 1952 Kern County All 26 sprinkler systems located in high seismic areas were braced to meet the requirements of NFPA 13 (1951 edition). Among those, only one damage was observed because of bracing failure. No leakage was reported (LeGrone 2004) 1964 Alaska About 24 buildings in the primary earthquake region had sprinkler systems installed. Among those, two were destroyed because of building collapse, and one experienced damage because of severe structural damage. Minor damage to structural and nonstructural elements caused slight damage to sprinkler systems in two buildings, while the loss of water service caused sprinkler failure in two other buildings. Additional observations included damage to sprinkler heads and pipe fittings (LeGrone 2004, Rashid et al. 2018) 1971 San Fernando Thirty eight of the estimated 973 sprinkler systems installed in buildings in the primary earthquake region suffered some damage. This was the first earthquake for which earthquake sprinkler leakage (EQSL) data was documented, with 28 of the sprinkler systems experiencing some level of EQSL. Damages to pipe joints were also observed (LeGrone 2004, Rashid et al. 2018) 1989 Loma Prieta No reliable data on EQSL during this earthquake is available. Only 12 claims were filed with FM Global insurance company. The failure rate of installed systems was between 5% and 10% within areas exposed to MMI VII to VIII. The performance of sprinkler systems was suggested to be similar to that of sprinkler systems during the 1971 San Fernando earthquake (LeGrone 2004) (Continued)

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Table 2-4.  Observed Damage in Fire Sprinkler Systems During Historic Earthquakes. (Continued) Earthquake

Damage to fire sprinkler systems

1994 Northridge

Observed damage included fractured threaded joints, leakage of pipes, brace anchorage failure, failure of hangers, ceiling panel-sprinkler heads (because of interaction with ceiling during excessive vertical accelerations) (Rashid et al. 2018). The Northridge earthquake was by far the largest sprinkler system damage event to date. It is stated that substantial sprinkler damage occurred during this earthquake; however, no specific numbers were reported. The main occupancy types with significant damage included retail, office buildings, and hospitals (LeGrone 2004) Not many buildings in the area had sprinkler systems; most losses came from industrial occupancies, where breakage and leakage of sprinkler pipings were observed (LeGrone 2004) Failure of sprinkler systems was reported for industrial occupancies, with limited loss data available (LeGrone 2004) Broken pipes and leakage at grooved pipe coupling joints proportional to the level of shaking were observed (Rashid et al. 2018) Interaction between ceiling panels and sprinkler heads caused damage and flooding (Tian et al. 2013) Interaction between ceiling panels and sprinkler heads, fracture of pipes at joints, permanent rotation of pipe hangers, shearing off braces, or pull out of anchorages caused damage and leakage (Rashid et al. 2018, Tian et al. 2013) Sprinkler heads sheared off because of interaction with ceiling cross-bracing (e.g., in low-rise commercial buildings), sprinkler piping was also damaged (Baker et al. 2012, Rashid et al. 2018) Interaction between ceiling panels and sprinkler heads caused damage and flooding (Rashid et al. 2018) Damaged piping and sprinkler heads caused flooding (Rashid et al. 2018)

1995 Kobe

1999 Chi-Chi 2001 Nisqually 2006 Hawaii 2010 Chile

2011 Christchurch

2013 Cook Strait 2014 Napa

Source: Reproduced from Baker et al. (2012), LeGrone (2004), Rashid et al. (2018), Tian et al. (2013).

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Post-Earthquake Fire Assessment of Buildings

Transverse Brace Longitudinal Brace Hanger-rods

Sprinkler Pipe

Transverse Brace

Figure 2-9.  Sprinkler piping supported by bracing in lateral and longitudinal directions. Sources: Adapted from Malhotra et al. (2003), Tian et al. (2013).

failure in sprinkler components was reduced when removing the water weight from the system (e.g., dry pipe system prior to actuation). Solid braces performed better than cable braces. An armover pipe, defined as a horizontal pipe extending from a branch line to a single sprinkler, performed better during an earthquake when wire restraints were removed. The failure probability of sprinkler systems following an earthquake can be determined by combining the failure probability of each sprinkler component (e.g., water tank, pump, piping, and sprinkler head) using fault tree analysis. Sekizawa et  al. (2003) developed a fault tree for estimating sprinkler system failures. The authors suggested that sprinkler systems may fail owing to either loss of water pressure or mechanical system failure. Based on Sekizawa et al. (2003), loss of water pressure may occur owing to damage to sprinkler heads, horizontal or vertical pipes, or water tanks, whereas mechanical failure may occur owing to failure of pump or loss of electric supply (Sekizawa et al. 2003). It should be noted that the sprinkler system reliability depends on the underlying causal factors affecting sprinkler performance, such as inspection, testing, and maintenance strategies (Budnick 2001). Frank et al. (2013) reviewed previous studies focusing on sprinkler system reliability using component-based analysis (e.g., fault tree analysis) and data-driven techniques.

2.3.3  Egress Routes The poor performance of access and egress components has been observed in experimental studies and previous earthquakes. Meacham (2016) reported distorted elevator doors, disconnection of stair landing from stair slabs, broken handrails, and jammed doors during a shake table test, which could lead to an impeded occupant egress after an earthquake (Figure 2-10).

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Figure 2-10.  Damage to means of egress observed in a 5-story reinforced concrete building shake table tests: (a) distorted elevator door, (b) disjointed egress stair. The collapse of precast stair units was observed in at least four multistory buildings after the 2011 Christchurch earthquake (Figure 2-11), with additional examples of severe damage to these stair types (Figure 2-12). In addition, damage to stairways in steel structures was also observed during the 2011 Christchurch earthquake (Kam and Pampanin 2011).

Figure 2-11.  Collapse of a precast concrete staircase. Source: Image taken from Kam and Pampanin (2011).

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Post-Earthquake Fire Assessment of Buildings

Figure 2-12.  Minor to moderate damage of staircases in the 2011 Christchurch earthquake. Source: Image taken from Kam and Pampanin (2011).

2.3.4  Passive Fire Protection for Structural Elements Examples of passive fire protection systems for structural elements include sprayed fire-resistant materials (SFRMs), intumescent paints, and rigid board products for the insulation of structural elements. The insulation products, such as SFRMs or intumescent paint, thermally insulate underlying structural members in the event of a fire. These materials may become damaged during the strong shaking of an earthquake, whereas the bond between the passive fire protection and the structural member may dislodge as the underlying structure deforms and yields. Damage to the passive fire protection material or loss of adhesion between the fire protection and the structural component leads to a degradation of structural fire performance. Experimental testing confirms the fragility of fire protection materials subjected to seismic loading and indicates their performance as a function of material type, substrate surface, and structural system configuration. Braxtan and Pessiki (2011a) studied the bond performance of two commercially available, medium-density SFRM materials applied to steel plates and found cracking and delamination of the SFRM, especially when strain in the steel plates exceeded yield strain. Braxtan and Pessiki (2011b) tested insulated steel beam–column moment connection assemblies under cyclic loading, and the results showed significant damage to the SFRM in plastic hinge regions of the beam. This damage was initiated at approximately 1% to 2% story drift (cracking and tearing) and became significant at drift levels of approximately 3% to 4% (dislodging). The impact of local damage to SFRM in plastic hinge regions of the beams can affect temperatures in the column and beam assemblies. Chen et  al. (2016) studied damage modes in cementitious coatings and intumescent paints under complex loadings, including monotonic loading up to 9% drift and low-frequency cyclic loading up to approximately 4% drift. The test results showed significant cracking and delamination in the fire protection

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material under moderate and large story drift. Zhang and Li (2014) stated that engineered cementitious composites (ECCs), which are a family of highperformance fiber-reinforced cementitious composites, can be considered as an alternative to unreinforced fireproofing owing to its high tensile ductility (3% to 5%) under static and high rate loading.

2.4  FIRE HAZARD SCENARIO Damage to equipment, furniture, and community lifelines (that are needed for continuous operation of critical government and business functions) during an earthquake can lead to fire ignitions (Zolfaghari et al. 2009). Large structural deformations may cause the failure of utility components within the structure, such as natural gas pipelines or electrical wiring. Equipment and furniture, such as stoves or water heaters, may overturn during an earthquake and cause ignitions. As discussed in Chapter 1, the major causes of FFE in historical events have been electrical and gas system failures. Chapter 1 provided an overview of the sources of FFE according to historical data. Although the consequences of FFE should be evaluated at both building and community levels, this section mainly focuses on sources of ignition within a building, and Chapter 3 reviews post-earthquake ignition models at the community level in more detail.

2.4.1  Sources of Ignition

Growth

Burning

Decay

Flashover

Incipient

Ignition

Temperature

In general, a combination of oxygen, combustible material, and a heat source, collectively known as the “fire triangle,” is needed for a fire to start (Behnam 2017). Figure 2-13 illustrates the process of fire growth over time within a typical room in the absence of a functioning fire suppression system (Buchanan and

Time

Figure 2-13.  Typical time–temperature curve in a compartment and the fire development process. Source: Adapted from Buchanan and Abu (2017).

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Post-Earthquake Fire Assessment of Buildings

Abu 2017). During the incipient period, the temperature of the potential fuel source increases; ignition marks the start of the growth period during which heat accumulates from the burning fuel and warms up other fuel sources (Carlton 2013). A fire would stop growing in case of insufficient oxygen level or depleting fuel source, and as such, the fire does not reach the flashover point. That is, a fire can potentially be controlled by reducing the number of fuel sources. If the fire continues to burn, ceilings, heated by hot gases rising owing to convection, begin radiating heat, which would increase the temperature of the fuel source within the compartment (Buchanan and Abu 2017). When a fire reaches the flashover point at a temperature around 600 °C, it enters the fully developed phase, the duration of which depends on the thermal inertia of the compartment boundaries and the availability of oxygen via ventilation openings. Owing to the potential thermal stresses and strength reductions in structural elements during the fully developed period of a fire, this phase is of utmost interest to structural engineers (Carlton 2013). The thermal contraction of structural elements during the cooling phase is also of concern to structural engineers. The sources of ignition that have been documented during past earthquakes include electrical short circuits (e.g., movement of defective wires and displacement of electrical supports), failure of fuel tanks, rupture of gas and oil pipes (e.g., connection failure owing to overturned water heater), chemical leakage (e.g., container failures lead to chemical fire and industrial processes disturbance), flammable material spills, and overturned ignition sources (e.g., table lamps, or gas grills) (Mohammadi et al. 1992). For this report, only ignitions that become fully developed and require firefighters intervention are considered and referred to as structurally significant fires (Elhami-Khorasani et al. 2017). Recently, Elhami-Khorasani and Garlock (2017) provided a review of primary ignition sources in previous earthquakes, where the literature shows that natural gas is the fuel source for 20% to 50% of post-earthquake fires. Zolfaghari et al. (2009) groups ignition sources within structures into three categories: (1) ignitions owing to failure of utility networks (e.g., gas pipelines); (2) failure of ignitable nonstructural components, braced contents, and equipment owing to structural damage; and (3) failure of unbraced ignitable content and equipment, such as stoves, owing to overturning. The authors state that while structural failure can cause the failure of nonstructural components [i.e., Groups (1) and (2) previously listed], nonstructural failures may occur even if damage to the building is insignificant [Group (2) previously listed]. In addition, the season and time of the earthquake change the likelihood of ignition as related to the usage of equipment and furniture (e.g., heaters). Farshadmanesh and Mohammadi (2019) provides additional details regarding Groups (1) and (3) and categorizes ignition sources into acceleration-sensitive components (e.g., water heater, stove, and portable heating systems), and drift-sensitive components, for which their failures depend on the building deformation, such as interstory drift. To estimate utility-related ignitions, Zolfaghari et al. (2009) used fault tree analysis with the assumption that the failure of utilities can lead to ignition when both fuel and spark exist (Figure 2-14).

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Figure 2-14.  Fault tree of utility-related ignitions after an earthquake. Source: Adapted from Zolfaghari et al. (2009).

2.4.2 Overview of Predictive Models for Post-Earthquake Fire Ignitions Existing FFE models estimate the likelihood of ignition using empirical, hybrid, and analytical procedures (Farshadmanesh and Mohammadi 2019, Elhami-Khorasani et al. 2017, Scawthorn 2009, Zolfaghari et al. 2009). Most fire ignition models aim to assess the number of ignitions, ignition locations, and/or the time of occurrence across a community. Lee et al. (2008) provided a comprehensive literature review on state-of-the-art ignition models until the late 2000s. Most of the empirical ignition models utilize historical ignition data from previous earthquakes. For example, the ignition model in Hazus-MH (FEMA 2009a) was developed using data from the 1971 San Fernando, 1983 Coalinga, 1984 Morgan Hill, 1986 North Palm Springs, 1987 Whittier Narrows, 1989 Loma Prieta, and 1994 Northridge earthquakes. Existing studies used various functional forms for ignition models, including power law, linear, semi-log, extreme value type III, and polynomial equations (Scawthorn 2009). In these models, the dependent variable is, in general, the ignition rate within an area of study, whereas the independent variables could be earthquake characteristics (e.g., typically reported as peak ground acceleration), community characteristics, or structural damage. Geographical information system-based tools provide a practical method to relate the geographic and demographic information of a study area to historical ignition datasets to estimate the likelihood of FFE in a given region (Zhao et al. 2006, Davidson 2009, Elhami-Khorasani et al. 2017, Farshadmanesh and Mohammadi 2019). Developing an analytical model to estimate the probability of ignition after an earthquake is a complicated and uncertain task. However, analytical models improve the fidelity of predictions by considering the underlying factors and, as opposed to data-driven models, are not limited in application to a specific area with

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particular characteristics (Mohammadi et al. 1992, Williamson and Groner 2000, Zolfaghari et al. 2009). To develop an analytical model, the contributing factors to FFE need to be identified, and their significance evaluated. Farshadmanesh et al. (2016) identifies the underlying causal factors of FFE ignitions, including spatial characteristics (e.g., floor area, building occupancy type), temporal characteristics (e.g., seasonality), ignitability [e.g., material(s) type/assembly], and seismicity of an area. The authors used the probability of ignition at normal conditions (i.e., fire occurrence during everyday activities and routine operation) as a baseline for the estimation of post-earthquake ignition probability (Farshadmanesh et al. 2016). The authors later proposed a negative binomial distribution to calculate the failure probability of independent ignition sources within residential buildings (Farshadmanesh and Mohammadi 2019). Kelly and Tell (2011) also utilizes negative binomial distribution to assess the expected number of ignitions as a function of earthquake characteristics. Further details on the modeling of postearthquake ignitions are provided in Section 3.2.

2.4.3  Design Fire Scenario Structural design fires are typically represented by localized, compartment, or traveling fires. Localized fires do not induce a flashover condition, and only a part of the compartment becomes involved in the fire, whereas a compartment fire represents a fully developed fire that reaches flashover conditions. In a fully developed fire, it can be assumed that the fuel load is uniformly distributed across the compartment. The concept of traveling fires has gained attention in recent years and refers to a fire in a large open plan compartment (e.g., offices with open cubicle arrangements) in which the whole compartment does not get involved at the same time, and the fire spreads within the compartment over time. Calculation methods to determine a structural design fire scenario can be categorized into three groups: simple models, zone models (one-zone models that generalize fire with uniform temperature in the compartment or two-zone models that take a smoke layer into account), and field models that are complex and, at times, computationally expensive. Fuel load density, in general, reported as MJ/m2, is one of the most important parameters in defining the temperature–time evolution of a structural design fire scenario. Fuel load density can be calculated as the total available fuel in a compartment, normalized by the area. Fuel load density is a function of building occupancy type, and design codes, such as NFPA 557 (NFPA 2002) or Eurocode 1 (EN 1991-1-2:2002) (CEN 2002), provide statistics of this parameter. Once the value of the fuel load density is decided on, the available openings and compartment characteristics will determine whether the fire is fuel controlled or ventilation controlled. Although fuel load characterizes the available potential energy, the fire severity is primarily based on the fire’s heat release rate and the containment of that heat. Standard time–temperature curves, such as ASTM E119 (ASTM 2016) and ISO 834 (ISO 1999) are used for standard furnace tests of structural elements and subassemblies. These curves have a heating phase only and are independent of fuel

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load density or ventilation conditions. The parametric fire curve of Eurocode 1 (EN 1991-1-2:2002) (CEN 2002) has been extensively used for structural fire engineering design purposes. The formulation is a function of fuel load density, ventilation, and thermal properties of the enclosure in a compartment. The input fuel load density is adjusted based on the probabilities of having a fire started and interventions by occupants, fire brigade, or active firefighting measures to extinguish the fire although the use of these adjustment factors varies topically. The input parameters to the model change the peak fire temperature, fire duration, and rate of heating and cooling of the time–temperature curve. The Eurocode parametric time–temperature curve represents compartment fires with postflashover conditions, and for design spaces with a floor area of less than 500 m2, a ceiling height of less than 4 m, and no ceiling openings. However, applying these equations to areas exceeding 500 m2 may be regarded as conservative (Kirby et al. 1999). Recent probabilistic studies illustrated the sensitivity of gas temperatures to compartment size and ventilation conditions (Gernay et al. 2019, Guo and Jeffers 2015). For application in probabilistic PBD, Eurocode 1 provides statistics of fuel load density, Elhami-Khorasani et al. (2014) discuss probabilistic models for fuel load density in office buildings, and JCSS (2001) models the value of the opening factor as a random variable. Zone models, such as the two-zone model Ozone (Cadorin and Franssen 2003) developed at the University of Liege or CFAST (NIST 2016) developed by the National Institute of Standards and Technology (NIST), can be used to determine the structural design fire scenario and the temperature of the upper zone (or the hot zone) during fire and height of the interface of the two zones. These models require the heat release rate as an input. Finally, computational fluid dynamics (CFD) simulations calculate the growth and evolution of temperature using mathematical methods by dividing the compartment space into cells to analyze low-speed, thermally driven fluid flow throughout the space. These models are relatively complex, computationally intensive, and require reasonable assumptions for materials and their combustion properties within the compartment. NIST has developed fire dynamics simulator, a software that can be used to conduct CFD analyses.

2.5  BUILDING RESPONSE TO FIRE The common approach for structural fire protection design is based on the prescriptive fire-resistance rating of structural components according to applicable building code, for instance, the adoption and amendment of the International Building Code (ICC 2012). The prescriptive approach relies on the standard furnace tests of structural elements subjected to the ASTM E119 fire curve. These tests provide data on the performance of components or subassemblies subjected to a defined heating exposure based on a furnace setup and its acceptance criteria. However, there is no correlation between the performance of a mock-up assembly

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during a furnace test and in situ structural system performance under natural fire exposure, where continuity, alternate load paths, and restraints play a significant role in the performance of the entire system (Rini and Lamont 2008). Although PBD in earthquake engineering is well established, it is only in recent years in the United States that the application of structural fire engineering has gained attention, and the industry has started adapting the idea in practice.

2.5.1 Background Analyzing a structure under fire conditions involves heat transfer analysis and structural analysis at elevated temperatures. Once the structural design fire scenario has been established (Section 2.4.3), heat transfer analyses can be completed to capture the temperature of structural components over time. Thermal properties of the material, such as specific heat, thermal conductivity, and density of structural members and applied fire protection, are needed to conduct heat transfer analysis. The three modes of heat transfer are conduction, convection, and radiation. In general, the heat flux that a structural element or assembly receives from a fire is governed by radiative and convective heating conditions, whereas conduction and convection modes should be considered for heat transfer within the element. Once the temperature history of the structural elements is obtained, a thermomechanical analysis of the structure can be completed, taking into account temperature-dependent material properties. The literature on the performance of individual structural components (steel, concrete, and composite) when subjected to fire is quite comprehensive. Extensive efforts have been conducted to investigate modes of failure of structural elements at high temperatures through experimental and numerical analyses. A sample of existing studies on steel and concrete beams, columns, and beam–columns in the United States include Kodur et al. (2004), Takagi and Deierlein (2007), Garlock and Quiel (2007), Quiel and Garlock (2008), Agarwal and Varma (2011), Agarwal et al. (2014), Naser and Kodur (2016), and Memari and Mahmoud (2018a). The provided list of references is not intended as an exhaustive review of the literature. Field observations, such as the World Trade Center buildings (Gann 2008), and experimental work (Kirby 1997, Wald et al. 2004, Dai et al. 2009, Yu et al. 2011, Yuan et al. 2011, Hu and Engelhardt 2014, Mahmoud et al. 2016, Fischer et al. 2017), show that connections can be vulnerable not only during fire exposure but also during the cooling phase after the fire (Almand 2012). Garlock and Selamet (2010) show that single-plate shear connections are vulnerable when large tensile forces are created during the cooling phase. The ASCE Structural Fire Engineering, Manual of Practice No. 138 (ASCE 2018) provides more details on the structural response to fire effects. A limited number of experiments have been carried out on the global response of complete structural systems under fire, the most notable of which are summarized here. The Cardington fire tests included six full-scale fire tests on an 8-story structure in Bedfordshire, United Kingdom (Swinden Technology Centre 1999). The tests provide insight into the behavior of composite floor systems where interior beams were not insulated. Although the structure did not

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collapse, large deformations and local buckling of the columns were observed. In 2008, two full-scale fire tests, FRACOF and COSSFIRE, were conducted as part of the EU Commission-funded projects to study the behavior of composite floor systems and investigate the findings from the Cardington test for different design details and extended fire duration (Vassart and Zhao 2011). These frame tests under real fires confirm the importance of robust load paths and the performance of connections for overall stability and improved structural response during a fire. Four composite floor beams with various end support conditions have been recently tested under compartment fires at the National Fire Research Laboratory at NIST (Choe et al. 2019). The observed vulnerabilities during the heating and cooling phases of fire included local buckling of the steel beams near supports, weld shear or bolt shear failure of connections, yielding of steel beams, and concrete fracture near restrained end supports. A large volume of literature is available on the modeling of structural elements and systems under fire. Going beyond element-level studies, Bailey (2002) discusses the structural behavior of concrete buildings during fire based on test observations. Sun et al. (2012) confirms that the lateral restraint of the structural system and configuration of bracings affect the global response of a system under fire. Lange et al. (2012) studied the global behavior of a 12-story composite steel frame with fire on three floors. The study used a 2D model and excluded connection failures. Different failure modes were investigated depending on weak versus strong floor mechanisms (i.e., the stiffness of the beams was varied). Jiang et al. (2014, 2015) analyzed a 2D model of an 8-story steel frame and showed that the bracing configuration changes resistance against progressive collapse during a fire. Also, the fire scenario has a significant influence on the collapse mechanism. The results from a study by Agarwal and Varma (2014) concludes that gravity columns are the most important components for the overall stability during the fire, and if one column fails, the presence of steel reinforcement in the concrete slab of the floor system, that is in addition to the minimum required reinforcement for shrinkage, leads to a uniform redistribution of forces to the neighboring columns and reduces the risk of progressive collapse. Memari and Mahmoud (2014) investigated 3-, 9-, and 20-story moment-resisting frames (MRFs) with reduced beam section connections using 2D modeling. The results showed that the beams and columns experienced residual axial forces and bending moments at the end of the cooling phase, but the global stability of the structure was not compromised by a single compartment fire. Rackauskaite et al. (2017) studied the performance of a 10-story, 5-bay steel frame under different regular and traveling fire scenarios (a total of 51 simulations) using a 2D finiteelement model. The results showed that the fire scenario, including the number of floors on fire, has a significant effect on failure time and the collapse mechanism.

2.5.2  Performance-Based Structural Fire Engineering Structural stability is needed for the safe evacuation of occupants as well as the protection of the property (Lange et al. 2014). When designing for fire, especially in the case of steel structures, the assumption is that the passive fire protection

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(i.e., insulation) will delay heat propagation to the structural elements and that the fire will burn out prior to the loss of stability and collapse. In addition, if active fire protection (such as sprinklers) is provided, the chance of a structurally significant fire is lower with the intent to have the fire extinguished prior to flashover. However, as previously discussed, the reliability of design based on a prescriptive approach has not been quantified, and the level of safety is unknown. Structural fire engineering, a PBD approach, can be formulated to design a structure for specified performance objectives in case of a fire event; for example, case studies are discussed by Block et al. (2010) and Hopkin et al. (2018a). A direct adaption of performance-based methods to structural fire engineering is not necessarily trivial, and the definition of various parameters within the framework, such as intensity measure, engineering demand parameter, and damage measure, is still being researched. For instance, although interstory drift, which characterizes global damage, is a common parameter as the EDP in earthquake engineering, no specific variable to represent damage in structural fire engineering has been published as a consensus. This could be related to how fire damage could remain a local event inside a building and would not necessarily be characterized with a single parameter that represents damage at the system level. Equation (2-2) is an adaption of Equation (2-1), showing the mathematical expression of performance-based structural fire engineering (PBSFE) (Lange et al. 2014): g (DVF ) = ∫ ∫ ∫ p(DVF | DM F ) ⋅ p(DM F | EDPF ) ⋅ p(EDPF | IM F ) ⋅ d(DM F )d(EDPF ) × d(IM F ) (2-2)  where IM = Intensity measure, EDP = Engineering demand parameter, DM = Damage measure, DV = Decision variable, and F subscript refers to the fire hazard. Appropriate variables must be realized for each of the hazard, system, and damage domains. The hazard analysis characterizes the intensity measure of a fire along with the mean annual probability of exceedance of the given intensity. Equation (2-3) relates the intensity measure to (1) the probability of having an ignition, (2) reaching a flashover condition given an ignition, and (3) reaching the intensity level under consideration given the flashover condition. Several variables have been considered as the intensity measure for fire, including the maximum gas temperature, duration of the fire, peak temperature in a compartment, heat flux, or fuel load density. Moss et al. (2014) introduced the idea of incremental fire analysis, similar to the incremental dynamic analysis in earthquake engineering, where the structure is exposed to an incrementally increasing intensity of the

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hazard. The study considered both the peak room temperature and the total radiant heat energy (RHE) as IMs in analyzing a two-span concrete beam. It was concluded that the RHE is a more efficient IM than the peak temperature as the aggregated results showed less dispersion; however, RHE is not a simple variable to calculate and requires advanced analysis. g (IM F ) = ∫ ∫ p(IM F | Flashover ) ⋅ p(Flashover | Ignition) ⋅ d(Ignition)d(Flashover ) (2-3) The system domain requires the selection of an appropriate EDP to assess the performance of the structural system. A wide variety of variables have been considered for the EDP, including in- plane deflection of beams, lateral deformation in columns, axial force in beams and columns, the maximum temperature in steel, instability owing to the formation of plastic hinges or inelastic buckling, pseudo velocity, and time of failure. Depending on the selected EDP, different criteria are defined to quantify damage (e.g., if deflection is defined as the EDP, limiting deflections are associated with the level of damage). The selected criteria depend on the design performance objectives, which could range from life safety for a typical structure to resilience objectives for critical structures where immediate occupancy or minimal loss of functionality is required. Elhami-Khorasani et al. (2019) compared the actual fire performance of a composite floor system typical of a US office building as a function of the prescriptive versus PBD approaches, where performance was measured using survival time at the structural system level but also with predefined thresholds in deflection and reinforcement bar temperature. Further discussions on relevant performance objectives to structural fire engineering and FFE can be found in Fischer (2014), Van Coile et al. (2019), Hopkin et al. (2018b), ASCE (2018), and Gernay and Elhami-Khorasani (2020). While the majority of studies in PBSFE follow deterministic analysis, there have been advances in quantifying uncertainties in structural design fire scenarios, and thermal and mechanical properties of the material, which can be used to formulate a probabilistic framework. Iqbal and Harichandran (2010) proposed a framework to determine load and resistance factors for the fire design of structural members. The study performed a statistical analysis of uncertainties in variables relevant to the fire design of structural steel components. The study showed that owing to scatter in load and material properties at elevated temperatures, there exist significant uncertainties in the fire design of structural elements compared with design at ambient temperatures. Guo et al. (2013) and Guo and Jeffers (2015) developed a probabilistic framework to calculate fire resistance of structural members using Monte Carlo simulations and including uncertainties in fire and structural resistance. Rush et al. (2014) studied the performance of a concrete column, subjected to a range of structural design fire scenarios that were generated by varying the compartment size, fuel load, and ventilation. The results showed that the column capacity was affected by both the peak temperature and the duration of the fire. Elhami-Khorasani et al. (2014) used a Bayesian-based approach to quantify fuel load density in office buildings using surveyed data. Elhami-Khorasani

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et al. (2015a) and Qureshi et al. (2020) modeled uncertainty in the thermal and mechanical properties of structural steel and concrete and the thermal properties of passive fire protection using test data. Gernay et al. (2016) introduced the idea of presenting the fire performance of buildings in terms of fragility functions. The study used fuel load density within a compartment as the IM and took uncertainty in the opening factor and the thermal and mechanical properties of materials into account to generate fragility functions for beams and columns of a gravity frame in a steel structure. The probabilities of fire within a compartment on different stories and bays of the building were incorporated using an event tree analysis. In developing the fragility functions, flexural resistance of beams (local failure) and resistance of columns (that could lead to global collapse) were considered as EDPs. In another study, Gernay et al. (2019) performed a sensitivity analysis of fire fragility functions to a series of random variables related to fire, heat transfer analysis, and the structural model. The study concluded that, in addition to fuel load as the intensity measure, uncertainty in the compartment geometry and openings, the thickness and thermal conductivity of fire protection, and the temperature-dependent mechanical properties of steel are significant to the probabilistic analysis.

2.6  BUILDING RESPONSE TO FIRE FOLLOWING EARTHQUAKE 2.6.1  Numerical Studies A few review articles on the response of structures to FFE are available in recent years (Elhami-Khorasani and Garlock 2017, Chicchi and Varma 2018, Gernay and Elhami-Khorasani 2019). Modeling the response of a structure under FFE requires proper assumptions on the level of damage to the structure because of the earthquake, the status of passive fire protection systems, and the potential for fire spread because of damage to active fire protection systems. Analysis of the structural system under FFE scenarios can provide insight into the stability and strength of damaged structures. One of the challenges in modeling FFE is to perform earthquake and fire analyses seamlessly within one programming environment. Most commercially available finite-element programs cannot efficiently model both seismic and thermal analyses; therefore, the majority of completed studies performs a dynamic analysis of the structure in one platform and then simplify the outputs of the earthquake analysis to a set of inputs as initial boundary conditions for the thermal analysis in a different modeling platform. However, OpenSees (version 2.4.0), an open-source finite-element program, which is primarily used for dynamic analysis, has been expanded to include thermal analysis and to enable seamless FFE modeling (Jiang and Usmani 2013). Elhami-Khorasani et al. (2015b) further modified the thermal module in OpenSees to enhance the code and facilitate reliability analysis at elevated temperatures.

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Della Corte et  al. (2003, 2005) proposed a methodology for evaluating steel MRFs under FFE, where seismic and thermal analyses of a structure were performed independently (i.e., no seamless transition between the two sets of analysis). To model the interaction between dynamic and thermal loads, Della Corte et  al. characterized the earthquake-induced damage as geometric and mechanical damage. It was argued that mechanical damage was significant only for very large values of the PGA and that the steel frames experienced small stiffness degradation by the design-level earthquakes. The interstory drift was taken as the main indicator of geometric damage, which would result in an increase in the member stresses owing to excessive lateral displacements. Yassin et al. (2008) proposed a step-by-step methodology, building on the research of Mousavi et al. (2008), and conducted an FFE analysis by taking into account both geometric and mechanical damage. However, because of the limited available tools to perform both nonlinear dynamic and thermal analyses, Yassin et  al. introduced the effect of seismic load on the frame using static loads to cause a lateral drift in the structure. The study concluded that evaluating buildings under fire and earthquake separately may not be sufficient, and the cascading effect should be taken into account. Zaharia and Pintea (2009) investigated the behavior of unprotected steel MRFs under FFE. The results show that frames that are designed for stronger seismic action have reserve capacity in case of both fire and FFE. Ronagh and Behnam (2012) studied the performance of reinforced concrete portal frames under FFE, with three levels of earthquake damage, namely, damage levels that would permit immediate occupancy, life safety, and collapse prevention. The results showed that the endurance of frames that experience considerable earthquake damage (life safety and collapse prevention categories) is notably different from the endurance of an undamaged frame, with global lateral collapse as the primary mode of failure. Memari et al. (2014) studied the performance of low-, medium-, and high-rise steel MRFs with reduced beam section (RBS) moment connections subjected to FFE scenarios. The study was conducted using nonlinear dynamic time–history analysis followed by a sequentially uncoupled thermal–mechanical analysis. The fire scenarios were applied to RBS connections under the assumption that the fireproofing was damaged during the earthquake owing to a large concentration of inelastic demands in the connections. The results showed that the potential for system collapse was not imminent as a result of applied post-earthquake fires. Elhami-Khorasani et al. (2016) investigated the reliability of a 9-story MRF subjected to fire only and FFE scenarios, taking fuel load density and mechanical properties of steel as random variables (within a probabilistic framework), while also changing the location of the fire compartment in the building. Plastic hinge formation, pseudovelocity, tension force, and deflection were among the four considered limit states, with associated defined EDPs. Steel sections in the MRF were not insulated. The structure was subjected to a ground motion scaled to the MCE followed by a series of FFE scenarios. The results suggested that modern MRF designs have enough residual strength that the change in their strength after an earthquake is not significant. However, earthquakes can

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increase the chances of fire spread inside buildings, whereas gravity frames within the structure would be more vulnerable in such scenarios. Memari et al. (2018) developed a nonlinear stability formulation to evaluate the response of steel columns under sequential earthquake and fire exposure. The proposed approach can be utilized to study the effects of a variety of variables on the instability of steel columns subjected to FFE. This methodology includes both P–δ and P–Δ effects, residual stresses in hot-rolled W-shaped steel sections, temperature-dependent material modeling, different boundary conditions, and nonuniform temperatures along the length of the steel columns. Memari and Mahmoud (2018b) studied the onset of instability in steel columns subjected to earthquakes followed by nonuniform longitudinal temperature profiles that can also accommodate various boundary conditions at the column ends. This study highlighted the reduction in column strength under fire as a result of a pre-imposed lateral drift caused by an earthquake. In more recent studies, Zhou et  al. (2020) studied post-earthquake fire performance of an MRF and a steel concentrically braced frame, subjected to moderate earthquakes and considering the damage to cementitious passive fire protection. The strain level in beams and columns is used as the damage indicator for passive fire protection. The thermomechanical analyses, conducted in OpenSees, demonstrate that the post-earthquake fire protection damage could result in significant reductions in structural fire performance. Vitorino et al. (2020) studied the behavior of reinforced concrete beams and columns under FFE. The results show that the damage imposed by an earthquake on reinforced concrete structures could reduce the fire performance, especially when the concrete cover is damaged, and the reinforcement is exposed to fire. Although not within the focus of this report, another potential scenario that has been studied for earthquake-prone areas is the post-earthquake fire seismic strength of structural systems. In this case, the hazards are not cascading (i.e., the earthquake does not immediately follow the fire), but the question is that if a structure experiences a fire, how does the capacity of the lateral load–resisting system change. For instance, community stakeholders may question the ability of a high-rise building to withstand an earthquake if some of the building’s bucklingrestrained braces experienced fire exposure during a previous accidental event. In this case, the inherent condition or the lengthy replacement time for these critical members could leave the building vulnerable to seismic motions for a considerable time, perhaps years. Ni and Birely (2018a, b) studied the impact of fire-induced structural damage on the lateral load resistance of reinforced concrete walls. The analysis was completed in two different modeling environments. SAFIR (Franssen and Gernay 2017) was used for the thermal analysis to obtain the maximum temperature in concrete and steel reinforcement. The residual strength and firedamaged material properties were then used as an input for cyclic analysis of the reinforced concrete shear wall in OpenSees. The results showed that fire damage could impact the load-bearing capacity and stiffness of reinforced concrete shear wall.

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2.6.2  Experimental Studies In general, full-scale experimental tests of building response to FFE are complex considering the limited availability of funding and strenuous efforts in coordinating the process at different phases. However, a limited number of full-scale fire tests to determine post-earthquake fire performance have been conducted in the recent past to study various aspects of building response. A series of structural FFE tests were conducted at the Indian Institute of Technology Roorkee in collaboration with the University of Edinburgh, funded by the UK-India Education and Research Initiative to determine the holistic structural response of reinforced concrete frames subject to FFE (Kamath et al. 2015, Shah et al. 2016) All tests were conducted on a heavily instrumented 1-story reinforced concrete structure in three stages: (1) quasistatic cyclic pushover loading at immediate occupancy and collapse prevention levels, (2) real compartment fire tests using a 1 h design fire, and (3) residual cyclic pushover tests to determine the residual capacity of the frame. The tests reported a significant loss in the residual capacity of the structure after three stages; however, they reported no structural collapse. Cracks and spalling of concrete at connection areas were reported during earthquake loading, which can expedite the heat transfer through the structural elements, thus causing weakening and potential failure of the connection in a fully developed fire. In addition, the tests compared the effect of the ductile and nonductile design of reinforced concrete frames (Shah et al. 2016). The authors also conducted lab-scale experimental tests to develop material models for damaged concrete at elevated temperatures. In 2012, a series of full-scale FFE experimental tests on a 5-story reinforced concrete frame were conducted at the University of California, San Diego (Hutchinson et  al. 2013). The tests mainly studied the performance of nonstructural building systems and post-earthquake fire performance of the building (the relevant results are reported in Section 2.3). In 2016, another series of full-scale FFE tests were conducted on a 6-story cold-formed steel-framed building protected with passive fire protection systems. Fire tests conducted on two levels showed severe damage and dehydration of gypsum wallboards. However, owing to the short duration of fire tests, the temperature in the wall cavities remained low. The fire tests were followed by two near-fault ground motion tests (aftershock), where an extensive fall off of a fire-damaged gypsum wall and ceiling boards were reported (Wang et al. 2016, Kamath et al. 2017). As a parallel effort, component-level FFE tests on gypsum-sheathed cold-formed steel wall panels were conducted at the NIST to study the effect of seismic and fire loads. The tests showed a 35% reduction in the lateral load–carrying capacity of the wall systems subject to fire and earthquake (Hoehler et al. 2017). Further to this, NIST has conducted tests to determine the effect of various levels of fire severity on the seismic shear capacity of cold-formed steel-framed shear wall systems in an effort to provide fragilities for these wall systems in response to real fires for performance-based design (Andres et al. 2019, Hoehler et al. 2019).

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2.7 SUMMARY Structural and nonstructural building components get damaged owing to earthquakes. Expected seismic performance levels from the structural point of view (i.e., operational, immediate occupancy, life safety, collapse prevention) have been established as a function of the earthquake intensity and building occupancy type. The level of damage to nonstructural components owing to earthquakes can be predicted with less certainty. Damage to nonstructural components (such as walls, egress stairs, etc.) in a building can compromise passive fire protection, such as compartmentation and insulation on members, and active fire protection such as sprinklers. Mitigation measures have been recommended to reduce damage; for example, seismic bracing of sprinkler pipes could support the system from excessive shaking. Structural design or assessment of buildings for FFE can be completed following performance-based structural fire engineering. The fire intensity measure, EDPs, and damage measures should be defined with care. Realistic, rather than standard, fire scenarios should be used to characterize hazards. Multicompartment fire, owing to the spread of fires within the building, should be considered. The bond between sprayed fire-resistive materials and steel can be compromised owing to shaking of the earth; thus, steel elements could become partially unprotected. The concrete cover in reinforced concrete elements could get damaged owing to earthquakes, resulting in higher temperatures in the rebar in case of a fire. The lateral force–resisting systems in a building are primarily designed to take the earthquake load and could get damaged; however, they have reserved capacity, relatively large thermal mass, and low utilization ratio under gravity loading. Thus, the gravity loading system in a building, with a higher utilization ratio and lighter sections, could be more vulnerable to fire load. The effect of stiffness of the lateral force–resisting system on the overall behavior of the structure during a fire (e.g., axial forces developed in beams owing to restraint from expansion) should be considered.

References Agarwal, A., L. Choe, and A. H. Varma. 2014. “Fire design of steel columns: Effects of thermal gradients.” J. Constr. Steel Res. 93: 107–118. Agarwal, A., and A. H. Varma. 2011. “Design of steel columns at elevated temperatures due to fire: Effects of rotational restraints.” Eng. J. 48 (4): 297–314. Agarwal, A., and A. H. Varma. 2014. “Fire induced progressive collapse of steel building structures: The role of interior gravity columns.” Eng. Struct. 58: 129–140. Almand, K. H. 2012. Structural fire resistance experimental research—Priority needs of U.S. industry. Prepared for the Engineering Laboratory National Institute of Standards and Technology. Gaithersburg, MD: Fire Protection Research Foundation. Andres, B., M. S. Hoehler, and M. F. Bundy. 2019. “Fire resistance of cold-formed steel framed shear walls under various fire scenarios.” Accessed November 19, 2021. https:// tsapps.nist.gov/publication/get_pdf.cfm?pub_id=927363 ASCE. 2017. Minimum design loads and associated criteria for buildings and other structures. ASCE 7-16. Reston, VA: ASCE.

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CHAPTER 3

Fire Following Earthquake at the Community Level

3.1  MODELING APPROACH AND AVAILABLE PLATFORMS As briefly discussed in Section 2.4.2, modeling post-earthquake fire ignitions is typically completed at the community level, rather than individual buildings, to account for the characteristics and demographics of the community as well as the response of the infrastructure and lifelines. This chapter focuses on communitylevel factors that contribute to fire following earthquake (FFE). Modeling FFE in an urban environment can be divided into three stages: ignition, spread, and suppression. Ignition is, in general, modeled independently from the other stages and, over time, on the scale of buildings, census tracts, or counties. Most ignition models account for one or more of the following parameters: earthquake intensity, population density, building material, building area, time of day, time of year, and so on. Fire spread is modeled over time on the scale of individual buildings or neighborhoods, accounting for the following parameters: building material, building area, the distance between buildings, characteristics of the built environment (streets vs. vegetation, etc.), wind speed, wind direction, and fire department response. The final parameter, namely, the fire department response, occurs during the suppression stage and, in general, acts as a modifier to the fire spread algorithm. Firefighter response and subsequent suppression are modeled over time, based on the following parameters: fire engine availability, fire personnel availability, fire reporting time (often a function of communication network operability), water availability at the boundary of fires (often a function of both earthquake intensity and power network operability), transportation time (often a function of road network operability), along with individual fire departments’ emergency preparedness, fire headquarters functionality because of structural damage and/or power loss, post-earthquake scouting routes, and effectiveness of reporting. The resilience of a community subjected to FFE is challenged by two phenomena: cascading hazards (also referred to as interacting or multihazards) and failure of dependent and interdependent infrastructure systems. The former

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is the idea that a certain hazard is likely to cause or be followed by a second hazard (Pescaroli and Alexander 2015). Examples are an earthquake causing a tsunami or landslide, a hurricane causing a storm surge and flooding, and in this case, a fire or multiple fires following an earthquake. Cascading hazards are dangerous because they require extra resources from an already damaged community and often lead to damage greater than the sum of their parts. In addition, much of the research history on disasters has focused on isolated hazards. The latter consideration is the failure of dependent and interdependent systems within an urban community. For example, the water network relies on the electric network to ensure the functionality of pumps, whereas power plants require water for the generation of electricity or cooling; emergency services require a functional communication network to receive emergency calls and an operational transportation system to reach those in need. Therefore, when an earthquake hits a community, the ability to effectively fight fires relies not only on the operation of the fire department and water network but also on the functionality of the power network, the communication network, and roadways (Coar et al. 2020). Among the available platforms with the capability to perform FFE analysis, Hazus (FEMA 2003) and MAEViz/Ergo (Ergo 2019) are the most notable software tools. Hazus evaluates the extent of fire in terms of the number of fire ignitions and fire spread by knowing the general building stock inventory, the average speed of fire engines, and the speed and direction of the wind. The default model calculates losses based on inventory and input parameters, including, among other parameters, building square footage and appraised value, population characteristics, and costs of building repairs. The results could be refined with supplemented user-provided information, such as the number of available fire trucks in the region or the proximity of fire stations. This FFE model outputs the number of expected ignitions, percentage of the area that would be involved in the fire, the population that is exposed to fire, and the dollar value of inventory that is exposed to fire. Although the FFE module in Hazus covers all three phases of fire (ignition, spread, and suppression), the technical manual warns the user that the module is based on limited research and, as a result, losses on account of fire are not included in total potential losses from an earthquake event. MAEViz/Ergo is an open-source software platform that was developed for estimating potential earthquake damage, including effects on transportation networks and socioeconomic systems. The program was developed by the Mid-America Earthquake Center and can be further expanded to evaluate loss estimations for multihazard studies. Yildiz and Karaman (2013) investigated the post-earthquake ignition vulnerability of a region in Turkey by implementing an ignition model in MAEViz (known as HAZTURK). Researchers at the NIST-funded Center for Risk-Based Community Planning based at the Colorado State University continue to develop the Interdependent Networked Community Resilience Modeling Environment (IN-CORE). IN-CORE v 1.0 is based on the previously mentioned MAEViz/Ergo platform and is an open-source code. This developing software can serve as a multihazard assessment, response, and planning tool for performing risk-based community

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resilience planning. Version 2.0 is under development, and at completion, will be an open-source web application with additional functionality. Updates to this point have been tracked on the software website and in the Journal of Sustainable and Resilient Infrastructure.

3.2 IGNITION In general, there are two approaches in the modeling of community-level fire ignitions following an earthquake: using historical data or physics-based modeling. The former method is a more traditional technique and is best applied when an urban community in a specific earthquake-prone region has a wellrecorded history of both earthquakes and fires following those earthquakes. When both these events are well known, it is possible to use regression analysis to relate different characteristics of the community to earthquake intensity and then apply this knowledge to predict ignitions either for a specific earthquake event or for an expected number of FFE ignitions over a time period. These prediction algorithms can also be applied to predict FFE ignitions in a different community within the same region or another region with similar community characteristics and earthquake types. Section 2.4.2 provided a summary of existing modeling approaches; this section discusses the topic in more detail. Several ways exist by which a fire can start following an earthquake, and the likelihood of ignition depends on the specifics of the area, local land use, cultural differences, socioeconomic status, and so on. Several papers also include a temporal component, tracking not only where but when fires break out following an earthquake (Zhao et al. 2006). This is especially important for firefighting planning efforts. In general, the majority of post-earthquake ignitions commence within the first 30 min after an earthquake, as appliances, candles, and equipment overturn and ignite, or gas leaks and electric arcing occur. In case of communityscale power loss following a seismic event, a second peak of fire ignition may begin on power restoration, as broken and short-circuited wires regain current, sparking and igniting nearby fuel. Few ignitions occur 12 or more hours after an earthquake, and almost none after 24 h (Zhao et al. 2006).

3.2.1  Data-Driven Models A number of papers on data-driven models for post-earthquake ignitions have been published. For an exhaustive collection of state-of-the-art research work through 2008, refer to Lee et  al. (2008). Some of the more influential papers referenced there and published since include Hamada (1951, 1975), TFD (1997), FEMA (2003), Scawthorn (1986, 2008), Scawthorn et  al. (2005), Zhao et  al. (2006), Davidson (2009), Elhami-Khorasani et al. (2017), and Farshadmanesh and Mohammadi (2019). The following section reviews the input parameters that have been considered as part of these models and would influence the likelihood of a fire ignition after an earthquake.

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3.2.1.1  Earthquake Intensity arthquake intensity is used as an input to all FFE ignition models. Without taking the intensity into account, there is no difference between modeling FFE and the likelihood of a fire on a typical day. In fact, at least one method (Farshadmanesh and Mohammadi 2019) models FFE ignition by simply taking the likelihood of a fire in a census tract at a time of the day and a day of the week and multiplying this likelihood by a modifier based on the modified Mercalli intensity (MMI). Different models tend to use different indexes, although the most popular are MMI and peak ground acceleration, whereas more detailed models consider permanent ground deformation and, at times, more than one index. Among other parameters, MMI gives a general understanding of the shaking level leading to ignition, whereas acceleration relates to the likelihood of overturning appliances, and deformation relates to the likelihood of gas lines failing (Himoto 2019).

3.2.1.2  Population Density The majority of data-driven models depend on population density as a metric to determine the likelihood of ignition following an earthquake. As more people are in a given area, more fuel and ignition sources would be available in that area. Population density is a preferred metric because of the ease of access to data. Census records are widely available in the developed world and provide density down to the small blocks of census tracks, often already mapped as geographical information system (GIS) data. In addition, for studies with higher resolution in smaller communities, the maximum occupancy loads of buildings are recorded in building permits. For models that take time of day into account, many metropolitan areas have records of the variation in occupancy (residents of the city, commuters, and tourists) for any hour of the day and week (FEMA 2003, Elhami-Khorasani 2015).

3.2.1.3  Floor Area The overall usable square footage (defined as the occupiable area minus shared spaces) of an urban area relates directly to the number of fuel and ignition sources contained within that area. Many models (Ren and Xie 2004, Scawthorn et al. 2005, Zhao et al. 2006, Elhami-Khorasani et al. 2017) use this information to quantify the likelihood of FFE.

3.2.1.4  Building Type A building’s structural type and materials of construction influence the likelihood of a structurally significant fire after an earthquake. At the community scale, building type is often generalized as noncombustible (steel, concrete, and unreinforced masonry), combustible (wood construction), and mobile homes (Elhami-Khorasani et al. 2017). Historical data with the breakdown of the number of ignitions based on the type of construction are available for recent earthquakes in California. Other factors may also contribute to the likelihood of ignition. For example, a building with unreinforced or combustible partitions is less likely to

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confine an ignition within a compartment, which can lead to a faster spread of fire within the building (Yildiz and Karaman 2013).

3.2.1.5  Building Collapse Longstanding models developed in Japan (Kawasumi 1961, Mizuno 1978, Kobayashi 1984) relate the likelihood of ignition to the number of buildings that would be at risk of structural collapse because of FFE, with the highest risk occurring in dense, wooden urban centers. It is unlikely that these models can be taken and applied directly to the modern US community and building practice, but the modeled relationship provides an insight into possible additional ignitions that could be expected in collapsed structures.

3.2.2  Physics-Based Models Data-driven models can be biased toward the characteristics of regions for which they have been developed. Local building codes and regulations, vernacular building practices, time of day or year of the historical events used for data collection, and cultural behavior can limit the applicability of these models to regions with different characteristics. In the United States, there are regions where historical FFE data are not available, such as a region that was thought to have little seismic threat until recent times when a new seismic activity or a historical/geological study showed that the threat of an earthquake in the area was nonnegligible. For example, the US Pacific Northwest (PNW) was thought to have little seismic threat until the mid1980s, when geologic studies of the Seattle area, historical research of Japanese, and reports of a massive earthquake and subsequent tsunami by indigenous PNW people showed that the region was overdue for a massive subduction zone earthquake from the Juan de Fuca plate (Atwater 2015). In addition, large-scale geologic analysis in the region, made possible by recent developments in light detection and ranging technology, showed several surface-level faults that have not had activity in recent years and could still be a threat (Atwater 2015). Another example of an area without historical records of FFE is a region with a seismic threat that only recently has experienced urban development to a degree where FFE would be notable and has potential for damage. Parts of the US Midwest, such as Missouri, have recently experienced an increase in population, and therefore, building density, and have realized the threat of FFE without the historical experience to know what to expect following an earthquake (Farshadmanesh and Mohammadi 2019). In addition, human industrial activities in some developed areas have triggered seismic activity in previously seismicdormant regions. Actions such as the construction of mega-tall towers (Ravilious 2005) or widespread fracture drilling (fracking) (Wendel 2015, Lin 2015) can affect the earth’s crust in such a way as to cause induced seismicity along a previously existing fault. In recent years, efforts have been made to predict post-earthquake ignitions using probabilistic physics-based models for cases without available data. For

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example, Farshadmanesh and Mohammadi (2019) proposed a model for seismicprone regions that have a little-to-no history of FFE. Their model takes the normal condition ignition, that is, the probability of fire occurrence during everyday activities without a seismic event, as a baseline, and then modifies this probability with factors such as the seismicity of the region, the geographic distribution of residential buildings, and ignition sources within those buildings. The model not only focuses on the effect of equipment failure because of an earthquake but also accounts for an increase in the risk of typical (nonseismic) occupant-caused sources of ignition (such as misuse/mishandling of heat and ignition materials) because of increased anxiety and stress affecting the occupants following an earthquake. The model also separates ignition sources into acceleration-sensitive and drift-sensitive components. Finally, the results of the analysis are in the form of probability of x ignitions over y years rather than a deterministic output. Zolfaghari et  al. (2009) and Zolfaghari and Peyghaleh (2010a) used a probabilistic logic tree model coupled with a GIS-based computer program to run a Monte Carlo simulation of ignitions following an earthquake, accounting for fuel pipelines, the power network, and building stocks. Multiple fuel and ignition sources are probabilistically modeled, as are a range of earthquake scenarios and intensity measures. This model is tuned and validated by an earthquake event in Kermanshah, Iran (Omidvar et al. 2013), and applied to the city of Tehran, Iran, for a range of analysis and mitigation optimization studies (Peyghaleh 2006, Zolfaghari and Peyghaleh 2010b, 2016). This method allows for a Bayesian approach for modeling ignitions, where any data-driven, physics-based, or expertguided probabilistic model can be inserted into different branches of the logic tree, gradually fine-tuning a model for a specific location as more information becomes available. Overall, a number of assumptions and simplifications are made to quantify parameters and coefficients in physics-based models, but a framework is available in the literature to evaluate the risk of post-earthquake ignitions in nonhistoric seismic urban areas.

3.3 SPREAD Urban fire spread has been studied since the 1950s, and dozens of papers have been published since then. For a thorough review of the state-of-the-art urban fire spread models through 2008, see Lee et al. (2008). In recent years, increased computational capacity and detailed GIS infrastructure have dramatically improved the ability to perform full-scale simulations of fire spread over an entire urban area. The following section discusses the most influential of the traditional, empirical fire spread algorithms (Hamada 1951, 1975, TFD 1997, 2001, FEMA 2003, Himoto and Tanaka 2000, 2003, 2008) and the more recent fire spread simulation methodologies (Scawthorn 2008, Davidson 2009, Lee and Davidson 2010b, Li and Davidson 2013, Nishino et al. 2012, Rafi et al. 2018, Himoto 2019).

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Note that many of the fire spread algorithms contain modifiers to implicitly account for fire department suppression efforts. Accordingly, assumptions related to suppression are discussed together with the relevant fire spread algorithms.

3.3.1  Data-Driven Models The Hamada model (1951) was among the first widely used building-to-building fire spread models. This empirical model assumes a grid of homogenous square buildings over a city block with homogenous street widths. The model assumes that the fire spreads in an elliptical manner in the direction of the wind, accounting for the “built-upness’ (defined as the total floor area density) of the area and the construction type of buildings in the area. This model is computationally inexpensive and provides a rough estimate of the total number of buildings that could potentially experience fire exposure. However, the model can be regarded as overly simplistic and biased toward its training data (mainly from FFE cases in Japan). Also, the model does not account for the heterogeneity of a city or a change in wind speed and direction (Lee et al. 2008). Scawthorn (FEMA 2003) has adapted the Hamada model for application in HAZUS with minor changes (most notably by including “fire breaks” such as wide streets or rivers); however, it still relies on the original assumptions and overall framework (Lee and Davidson 2010a). The Tosho model, published in 1997 and updated in 2001 by the Tokyo Fire Department, is another empirical model that assumes an elliptical fire spread and heterogeneous building distribution and street width. The Tosho model considers fire spread because of radiation and reduces the assumed speed of fire growth (as compared to the Hamada model) to achieve a better agreement with historical data. Also, this model has a feature that can be used to calculate the potential number of damaged buildings because of FFE (Scawthorn et al. 2005). The Tosho model is, in general, viewed as an improvement over the Hamada model but still includes major simplifications. A detailed description of both the Hamada and Tosho models and their constituent equations can be found in Section 4.4 of Scawthorn et al. (2005).

3.3.2  Physics-Based Models Physics-based models for FFE take into account all forms of fire spread— conduction, convection, radiation, direct flame impingement, and burning brand impingement—often drawing on previous research on fire spread during wildfire events. These models essentially generalize the fire spread prediction applicability across different regions and construction types. However, this generalization results in increased computational expense and a requirement for more detailed input data about the given community. Lee et  al. (2008) provide a detailed discussion on the state-of-the-art physics-based fire spread models up to 2008, as well as a general history of contemporary fire spread modeling. Thermal radiation is the dominant cause of fire spread in urban environments, causing spontaneous ignition of neighboring structures further off. Convection is less likely to cause fire spread from building to building, but in the case of strong winds, it can become a significant factor and influence the direction of fire

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spread (Nussle et al. 2004). Branding can double fire spread velocity by helping the fire “jump” long distances (Scawthorn 1986). When it comes to modeling FFE compared with compartments or wildfires, there are significant differences, but lessons and fundamentals can be adapted from such cases. Earlier fire spread models (Cousins et al. 2003, Iwami et al. 2004, Nussle et al. 2004) use physics as a basis but modify those rules and combine them with historical data to simplify the application for FFE computation. For example, progress from an unburned to fully burnt structure can be estimated with a measure of elapsed time (Cousins et al. 2003) or by assuming that a building ignites simply if a flame touches the structure (Iwami et al. 2004). No consensus exists on the required spatial and temporal resolution to obtain reasonable accuracy. Cousins et al. (2003) and Ohgai et al. (2004) used cellular automata to divide the subject landscape into equally spaced grid cells with a single state assigned to them that would change based on the status of nearby cells over time. The ResQ Firesimulator (Nussle et al. 2004) treats buildings as individual units but overlays a 2D grid of volumetric cells that update the air temperature at each time step and affect the fire exposure conditions of the buildings around them. Himoto and Tanaka (2008) modeled individual compartments within buildings and, using conservation of mass and energy equations, estimated the temperature in each room at a given time step. This model accounts for the presumed “burn-through” of a compartment wall into the next room and includes multiple physics-based equations to account for the spread of the fire to the next building. At this scale, the physics pertinent to building-to-building fire spread is followed without much simplification, but a significant amount of input information and process time are necessary. Unfortunately, precise data on the contents of each room within a given building may be unknown. Thus, a balance between the precision of input data and the implementation of fire spread physics is needed for large-scale urban fire spread simulations for FFE. Davidson (2009), and Lee and Davidson (2010a, b) studied compartment-scale fire spread using advanced GIS algorithms to model building footprints, heights, and, most important, a reasonable estimate of room configurations within each building. They also included radiation, branding, and roof fire models, as well as options for deterministic or probabilistic ignition models. Li and Davidson (2013) continued this work with the addition of a suppression module, creating an integrated spread and suppression model. This model makes simplifying assumptions on the response time of the fire department to the locations of ignition and water availability after an earthquake. Li and Davidson (2013) also completed a sensitivity analysis and found that the most critical FFE scenario is a combination of multiple ignitions in conjunction with a relatively high wind speed and limited water availability. Nishino et al. (2012) developed an ignition-spread-suppression model for the analysis of FFE. This model is unique in that, along with building damage, it includes evacuee location as an input, simulates evacuation efforts, and addresses evacuee fatality as a loss. This model also includes weather as input and accounts for civilian firefighting efforts (previous models only accounted

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for fire department response). It also uniquely accounts for building structural damage following an earthquake both in formulating the estimated fire spread in damaged buildings and the roadway blockage because of structural debris, which would affect both fire department response and evacuation route availability. The primary limitations of this model are the simplified ignition formulation and the treatment of floors in buildings as single compartments. Rafi et  al. (2018) attempted to bridge the gap between the traditional empirical models and the modern physics-based models that require a conceivably unattainable level of data and computational power, drawing on many of the aforementioned studies and the work of Zhao (2011). Specifically, they used deterministic prediction of ignition and ignored suppression to focus on fire spread. However, the model could hypothetically be harmonized with, for example, the Elhami-Khorasani et al. (2017) ignition model and the Li and Davidson (2013) suppression model. This model considers the state of fire in six stages—no fire, ignition (a single compartment is ignited), flashover (all ignitable surfaces in the compartment are on fire), full development (the fire moves into other compartments—at this point, the model no longer accounts for individual compartments but looks at heat release rate as a function of floor area, building occupancy type and material, and elapsed time since flashover), structure fire (entire building on fire with the maximum heat release rate), and structural failure. At any time step, a building at Stage 0 (no fire) is liable to be ignited by Stage 3 (full development) and Stage 4 (structure fire) of other buildings if the building is within an elliptical near-source fire spread zone or a flame branding spread zone of a burning structure. Any nonburning building within a burning building’s influence zone is assigned a fire spread judgment index that ranges from 0 to 1 (Zhao 2011), where higher numbers indicate a greater likelihood of ignition at the next time step. Empirical data help simplify the physics of the near field and branding, whereas input data such as weather, building height, material, floor area, and structural damage remain as part of the model.

3.4 SUPPRESSION Most of the existing FFE fire spread algorithms have some ability to account for fire suppression, often as a modifier for the fire growth rate, where explicit modeling of related infrastructure systems is, in general, eschewed in favor of model simplicity. It is, in general, acceptable to view the two stages of spread and suppression as a single integrated step. The following section discusses implemented methods in the literature to model fire suppression and the related infrastructure systems at the community level. The suppression model by Scawthorn (1986) and Scawthorn et al. (2005), that is implemented in HAZUS, accounts for firefighting suppression efforts and the effects of damage to the water supply, the fire department engine, personnel availability, and damage to the transportation network in a simplified framework.

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The suppression model controls the spread rate of a modified Hamada elliptical spread model with the following equation: Spread Rate = Spread Ratenon-suppressed ∗ (1 − Peff 0.7), where Peff is the fire suppression effectiveness, which is a function of both fire truck availability and water availability, compared with the required fire trucks and water to fight a fire of the specified size as determined by Scawthorn et  al. (2005), in discussion with firefighting departments. The model makes a number of assumptions and simplifications. For example, it simply doubles the average engine response time after an earthquake compared with normal operations and performs a coarse analysis of water availability (FEMA 2003). Li and Davidson (2013) expand on Scawthorn’s model with a similar simplified reporting time of the fire department to fire locations but include a new investigation into prioritizing response as a function of building importance, occupancy type, and floor area. The needs for each fire are calculated as a function of the fire perimeter, and fire engines are assigned considering two strategies: concentrated (where the highest priority fires are assigned sufficient engines to control the demand) and distributed (where engines are assigned one at a time from the highest to the lowest priority fire until looping again to the highest priority fire). The suppression activity is tracked by the volume of water leaving the engines via exterior aerial attacks, extinguishing the roof first and then spreading water equally among exterior compartments. The model assumes defensive attacks and does not apply water to interior burning rooms. The suppression activity affects the spread model by reducing the fire intensity of the target building and lowering the likelihood of fire spread. Again, water and transportation networks are not modeled explicitly. Nishino et al. (2012) include an explicit transportation model, but the model is only applied to evacuation routes and not to fire department suppression efforts. Recent work aims to explicitly model infrastructure systems that contribute to fire response procedures in preparation for integrating them into a holistic suppression model, but a fully explicit model has yet to be published. Guidotti et  al. (2017) developed a framework for analyzing dependent infrastructure systems, including transportation, power, and water, and Ellingwood et al. (2017) demonstrated the application of this methodology to a hypothetical community. Also, work by Coar et  al. (2020) and Sarreshtehdari et  al. (2020) propose a methodology for analyzing water network, power network, and the dependence of water on power within the context of FFE. Wu and Chen (2019) modeled traffic network operability for emergency vehicles after an earthquake, and Sun et al. (2018) reviewed the state-of-the-art for resilient metrics of transportation infrastructure after extreme events. Johansen and Tien (2018) developed a novel Bayesian approach to model the interdependence of infrastructure systems on multiple scales and applied the approach to real interdependent water, power, and gas networks. Lastly, Huizar et al. (2018) developed modern metrics for the robustness of the water network. Historical records show that FFE damage can be significantly greater than the sum of individual earthquake or fire events (Elhami-Khorasani and Garlock 2017). Considering FFE as a cascading multihazard scenario, and acknowledging the complex behavior of interdependent infrastructure systems within a

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community, make it difficult to establish efficient and accurate modeling methods to predict the expected damage in a community. Research is currently in progress to advance modeling methods that could be used by emergency management offices and first responders to minimize losses. These models would be applicable to mitigation and preparation phases, as well as a real-time response for the fire engine and personnel distribution after an earthquake.

3.5 SUMMARY The critical infrastructure in a community, including water, power, communication, and transportation system, together with the available fire department resources, affects the three phases of fire ignition, spread, and suppression following an earthquake. The vulnerability of the infrastructure and characteristics of the community should be taken into account when planning for post-earthquake fires. The number of ignitions is a function of earthquake intensity, population density, building footage area, and building construction. Redundancy in the systems, such as backup water resources for firefighting, reduces the risk of fire spread and prevents it from going out of control. Alternate response routes could prevent the creation of islands (i.e., isolated blocks) within the community. The available modeling techniques for estimating the number and locations of ignition, the likelihood of fire spread, and the required resources for suppression rely on both empirical and physics-based approaches. Existing models make a series of simplified assumptions given the complexity and level of uncertainty in the process. These models can be used for mitigation and planning; however, the user should analyze results with care and be mindful of the limitations of the models. For example, the results from empirical models developed based on data from one region (e.g., a data-driven ignition model based on data from historical earthquakes in California) cannot be generalized to any region.

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Li, S., and R. A. Davidson. 2013. “Parametric study of urban fire spread using an urban fire simulation model with fire department suppression.” Fire Saf. J. 61: 217–225. Lin, C. H. 2005. “Seismicity increase after the construction of the world’s tallest building: An active blind fault beneath the Taipei 101.” Geophys. Res. Lett. 32(22). Accessed November 19, 2021. https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2005GL024223 Mizuno, H. 1978. “On outbreak of fires in earthquakes.” Ph.D. thesis, Kyoto University, Dept. of Architecture. Nishino, T., T. Tanaka, and A. Hokugo. 2012. “An evaluation method for the urban postearthquake fire risk considering multiple scenarios of fire spread and evacuation.” Fire Saf. J. 54: 167–180. Nussle, T., A. Kleiner, and M. Brenner. 2004. Approaching urban diasaster reality. The ResQ Firesimulator. Accessed November 19, 2021. http://www.diva-portal.org/smash/ get/diva2:459923/FULLTEXT02 Ohgai, A., Y. Gohnai, S. Ikaruga, M. Murakami, and K. Watanabe. 2004. “Cellular automata modeling for fire spreading as a tool to aid community-based planning for disaster mitigation.” In Recent advances in design and decision support systems in architecture and urban planning, edited by J. P. Van Leeuwen and H. J. P. Timmermans, 193–209. Dordrecht, Netherlands: Kluwer. Omidvar, B., M. Eskandari, and E. Peyghaleh. 2013. “Seismic damage to urban areas due to failed buried fuel pipelines case study: Fire following earthquake in the city of Kermanshah, Iran.” Nat. Hazard. 67: 169–192. Pescaroli, G., and D. Alexander. 2015. “A definition of cascading disasters and cascading effects: Going beyond the ‘toppling dominos’ metaphor.” Planet@Risk 3: 58–67. Peyghaleh, E. 2006. “Fire following earthquake risk analysis, a pilot study for the city of Tehran.” M.Sc. thesis, KN Toosi University of Technology, Dept. of Civil Engineering. Rafi, M. M., T. Azis, and S. Lodi. 2018. “A suggested model for mass fire spread.” Sus. Resil. Infrastruct. 5(4): 214–231. Ravilious, K. (2005). Skyscraper that may cause earthquakes. The Guardian, Accessed November 2021. https://www.theguardian.com/environment/2005/dec/02/natural​ disasters.climatechange, Ren, A. Z., and X. Y. Xie. 2004. “The simulation of post-earthquake fire-prone area based on GIS.” J. Fire Sci. 22 (5): 421–439. Sarreshtehdari, A., N. Elhami Khorasani, and M. Coar. 2020. “A streamlined approach for evaluating post-earthquake performance of an electric network.” Sus. Resil. Infrastruct. 5(4): 232–251. Scawthorn, C. 1986. “Fire following earthquake.” Fire Saf. Sci. 1: 971–979. Scawthorn, C. 2008. Fire following earthquake. Denver: SPA Risk. Scawthorn, C., J. M. Eidinger, and A. J. Schiff. 2005. Fire following earthquake. Reston, VA: ASCE. Sun, W., P. Bocchini, and B. Davison. 2018. “Resilience metrics and measurement methods for transportation infrastructure: The state of the art.” Sus. Resil. Infrastruct. 5 (3): 168–199. TFD (Tokyo Fire Department). 1997. Analysis of the causes/spread of the fires caused by an earthquake directly below Tokyo. [In Japanese.] Fire Prevention Deliberation Council Report. Tokyo: TFD. TFD. 2001. Development and use of the method for the evaluation of local. [In Japanese.] Preparedness for Earthquake Fires, Fire Prevention Deliberation Council Report. Tokyo: TFD. Wendel, J. 2015. “Ohio earthquake directly tied to fracking.” Eos 96. Accessed July 2021. https://eos.org/articles/ohio-earthquake-directly-tied-fracking

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CHAPTER 4

Recommendations

ASCE 7, Appendix E is the current industry standard for the performance-based design of structures for fire exposure. This standard requires consideration of uncontrolled fire exposure (e.g., fire sprinkler systems must be considered inoperative) and fulfillment of mandatory performance objectives pertaining to occupant life safety. In addition, this standard provides an outlet for discretionary performance objectives to be posed and designed for. Fire following earthquake (FFE) could be a pertinent discretionary performance objective for certain projects if deemed as such by project stakeholders, notably the building authority and property insurance carriers. Although this standard does not provide explicit guidance for FFE, it does provide a general design framework that can be adapted and adjusted for this purpose. In addition, Structural Fire Engineering, Manual of Practice No. 138, provides more detailed guidance and cursory information on FFE. This book focused exclusively on FFE and provided a more explicit discussion on this distinct hazard compared to the generalized structural fire engineering guidance provided in the ASCE/SEI documents previously mentioned. Design for extreme scenarios, such as FFE, which is a low-probability event with high consequences, involves a large level of uncertainty; therefore, probabilistic performance-based design can ideally be used to obtain the full spectrum of potential outcomes. As a discretionary performance objective according to ASCE 7, Appendix E and with the mandatory performance objectives presumably fulfilled, the use of a probabilistic method that accounts for active fire protection systems (e.g., fire sprinkler system effectiveness) can be harnessed (whereas they would need to be considered completely inoperative otherwise). For special projects, rigorous analysis using probabilistic risk assessment methods can be used to identify and evaluate the consequences of active and passive firefighting system failures. For example, an event tree of potential outcomes can be set up to examine a series of subsequent events considering fire safety systems, as discussed in Chapter 2. Figure 4-1 shows a sample of such event tree analysis, whereas the listed probability values are for illustration purposes and cannot be generalized for all design applications. These values should be evaluated by the designergiven specifications of the structure (e.g., the probability of ignition is a function of location and characteristics of the structure, or the probability of damage to 65

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Figure 4-1.  Event tree example for post-earthquake fire analysis. nonstructural components is related to interstory drift and/or floor accelerations that are driven by the performance of structural systems). When designing for FFE, it is necessary to review, and if needed, make assumptions on the behavior of safety systems, which could prevent fire spread and lower the risk of severe damage to the structure. Sprinkler systems are perhaps the most effective way to extinguish a fire before it goes out of control. Based on the total probability rule, the probability of failure (Pf ) equals the probability of having a structurally significant fire (Pfi) multiplied by the probability of failure given a structurally significant fire (Pf | fi). In the case of buildings with sprinklers, Pfi is smaller during normal conditions, and, therefore, the value of Pf | fi can be relaxed while maintaining the same value of Pf for the building. However, the potential damage to sprinklers, disconnect in water supply, or pipe failure during an earthquake may lead to inoperability or failure of the sprinkler systems. Therefore, the chance of having a fire that goes out of control after an earthquake is higher than that in normal conditions. Although Pfi in a building could have a larger value after an earthquake, it should be noted that the target Pf  (or reliability requirements) for FFE scenarios is typically less strict compared with that for normal conditions, given that the probability of having a severe earthquake during the lifetime of a building should also be taken into account. Rather than using risk-informed performance-based methods, a designer may opt for a less computationally expensive approach and demonstrate adequate safety using scenario-based deterministic analysis, where performance outcomes for a number of identified scenarios are evaluated within a deterministic framework. It is recommended to consider multicompartment fire scenarios, as opposed to single-compartment fires within the building when analyzing the performance of the structure after an earthquake. Damage to nonstructural components, such

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as non-load-bearing walls or glazing during an earthquake can lead to a loss of compartmentation. This leads to a faster spread of fire in a damaged structure compared with normal conditions. Fire spread can happen horizontally within a floor or vertically between floors. Damage to glazing and breakage of windows can be taken into account by adjusting the opening factor in the calculation of natural fire scenarios. Damage to egress routes, such as stairs, is also possible. Conservative design recommendations for FFE may assume that fire protection (such as sprayed fire-resistant materials) in regions of expected large deformations during the earthquake (e.g., beam plastic hinges) has endured significant damage, and, thus, the underlying structure becomes unprotected. Gravity frames typically have a high utilization ratio and are more vulnerable than heavier systems such as moment-resisting frames. Heavy structural systems (such as moment-resisting frames) inherently have some reserved capacity because of larger section sizes and consequently thermal masses (take longer to heat up). In addition, lateral loadresisting systems have a relatively low utilization ratio (demand-to-capacity ratio) under gravity loads, given that their design is governed by lateral loads. However, stiffness of the lateral load-resisting system could influence the overall behavior of the building, and therefore, careful consideration should be given if a simplified two-dimensional analysis of the building gravity system is conducted. Aside from building-level design considerations, mitigation actions at the community level can reduce the likelihood of fire ignition and fire spread after an earthquake. For example, automatic gas shutoff valves will reduce the risk of post-earthquake fires, preplanned scouting routes and redundancy in the transportation network will reduce the response time of the fire department to locations of ignition, and backup water supplies will increase the potential to control a fire in case of an ignition if water network is damaged. The preparedness and implemented strategies to lower the risk of FEE at the community level could influence the target reliability for design at the building level.

Index Note: Page numbers followed by f and t indicate figures and tables. active fire protection systems,  18–26; damage to,  20t. See also nonstructural components damage armover pipe,  26

physics-based models,  55–56, 57–59; redundancy in systems,  61; resilience of,  51; software tools,  52; spread,  56–59; supplemented user-provided information,  52; suppression,  59–61 computational fluid dynamics (CFD),  33

building response to fire,  33; Cardington fire tests,  34; challenges in modeling FFE,  38; experimental studies,  41; following earthquake,  38–41; fuel load density quantification,  37–38; hazard analysis,  36; modeling of structures under fire,  34; nonlinear stability formulation,  40; numerical studies,  38–40; OpenSees,  38; performance-based structural fire engineering,  35–38; radiant heat energy,  37; RBS connections,  39; SAFIR,  40; structure analysis under fire conditions,  34. See also fire following earthquake at building level

damage: to active fire protection systems,  20t; to building and sprinkler systems,  22f; to fire door,  17f; in fire sprinkler systems,  24t–25t; to means of egress,  27f; to passive fire protection,  18f; percentages of fire safety systems,  19f; precast concrete staircase collapse,  27f; of staircases in Christchurch earthquake,  28f. See also nonstructural components damage data-driven models,  53; building collapse,  55; building type,  54–55; earthquake intensity,  54; floor area,  54; Hamada model,  57; ignition,  53–55; population density,  54; spread,  57. See also community subjected to FFE

Cardington fire tests,  34. See also building response to fire cascading hazards,  51–52. See also community subjected to FFE community subjected to FFE,  51, 61; cascading hazards,  51–52; data-driven models,  53–55, 57; firefighter response and subsequent suppression,  51; Hazus,  52; ignition,  53–56; MAEViz/Ergo,  52; modeling approach,  51–53; number of ignitions,  61;

earthquake: hazard scenario,  11–12; potential damage assessment,  1–2 egress routes,  26–27. See also nonstructural components damage

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Index

engineered cementitious composites (ECCs),  29 engineering demand parameters (EDPs),  12 explosive gas mixtures,  6 fire: compartmentation,  16–18; -related code provisions,  7; safety,  15; spread models,  58; sprinkler systems,  1; triangle,  29. See also community subjected to FFE; fire hazard scenario; nonstructural components damage fire following earthquake (FFE),  1; at building and community scales,  8f; causes of fire ignitions,  4–7; codes and provisions,  7–8; design recommendations,  67; earthquake shutoff switches,  6; event tree for post-earthquake fire analysis,  66f; failure modes of water heaters,  6; heavy structural systems,  67; historical events,  2–4, 3t; ignitions due to natural gas,  5t; post-earthquake ignitions,  4f; recommendations,  65–67; scope and objectives,  8; sprinkler systems,  66 fire following earthquake at building level,  11, 42; building response,  12, 33–38, 38–41; damage to nonstructural components,  15–29, 42; damage to structural system,  12–15; design guidelines,  11; earthquake hazard scenario,  11–12; equivalent lateral force method,  11; response spectrum analysis,  11. See also fire hazard scenario fire hazard scenario,  29; design fire scenario,  32–33; fault tree of utility-related ignitions,  31f; fire triangle,  29; fuel load density,  32; ignition model in Hazus-MH,  31; ignition sources,  29–31; predictive

models,  31–32; structural design fires,  32; time–temperature curves,  29f, 32–33; zone models,  32, 33 fire ignitions,  55–56; causes of,  4–7; in community,  53, 61; data-driven models,  53–55; fault tree of utility-related,  31f; model in Hazus-MH,  31; due to natural gas,  5t; post-earthquake,  4f, 31–32; -spread-suppression model,  58. See also fire hazard scenario Fire Protection Association of New Zealand (FPANZ),  16 fire protection systems: active,  18–26; passive,  17, 18f, 28–29 fuel load density,  32; quantification,  37–38. See also fire hazard scenario geographical information system (GIS),  54 Hamada model,  57. See also community subjected to FFE hazard: analysis,  36; in built environment,  1; cascading,  51–52; earthquake,  11–12 Hazus,  52. See also community subjected to FFE Hazus-MH ignition model,  31. See also fire hazard scenario heavy structural systems,  67 ignition,  51, 53; data-driven models,  53–55; physics-based models,  55–56; sources,  29–31; -spread-suppression model,  58 Interdependent Networked Community Resilience Modeling Environment (IN-CORE),  52 MAEViz/Ergo,  52. See also community subjected to FFE

Index

maximum considered earthquake (MCE),  13 modified Mercalli intensity (MMI),  54 moment-resisting frames (MRFs),  35 National Fire Protection Association (NFPA),  7 National Institute of Standards and Technology (NIST),  33 New York-New Jersey-Connecticut area (NYCEM),  2 New Zealand sprinkler standard,  19 nonstructural components damage,  15, 42; active fire protection systems,  18–26; armover pipe,  26; building fire safety,  15; egress routes,  26–27; failure modes for sprinkler systems,  23; fire compartmentation,  16–18; fire sprinkler system,  21f; New Zealand sprinkler standard,  19; passive fire protection for structural elements,  28–29; passive fire protection products,  17; performance of sprinkler systems as function of ground motion intensity,  23t; shake table tests,  23, 26; simulation methodology for fire sprinkler piping systems,  23. See also damage; sprinkler OpenSees,  38. See also building response to fire organization disruptions,  1 Pacific Earthquake Engineering Research (PEER),  13 Pacific Northwest (PNW),  55 passive fire protection: damage to,  18f; products,  17; for structural elements,  28–29. See also nonstructural components damage performance-based design (PBD),  12

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performance-based structural fire engineering (PBSFE),  35–38. See also building response to fire physics-based models,  55; ignition,  55–56; ignition-spreadsuppression model,  58; ResQ Firesimulator,  58; spread,  57–59. See also community subjected to FFE post-earthquake fire ignitions,  31–32. See also fire hazard scenario radiant heat energy (RHE),  37. See also building response to fire reduced beam section (RBS),  39 ResQ Firesimulator,  58. See also community subjected to FFE SAFIR,  40. See also building response to fire shake table tests,  23, 26 Society of Fire Protection Engineers (SFPE),  7 Southern California Gas Company (SoCalGas),  5 spread,  56; data-driven models,  57; physics-based models,  57–59. See also community subjected to FFE sprinkler,  19; failure during nonstructural damage,  22f; piping supported by bracing,  26f; reliability,  26. See also nonstructural components damage sprinkler system,  21f, 66; damage to building and,  22f; failure during 1994 Northridge earthquake,  22f; observed damage during historic earthquakes,  24t–25t; performance as function of ground motion intensity,  23t; reliability,  26; simulation methodology for,  23; sprinkler piping supported by bracing,  26f. See also nonstructural components damage

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Index

standard time–temperature curves,  32–33. See also fire hazard scenario structural design fires,  32. See also fire hazard scenario Structural Engineering and Earthquake Simulation Laboratory (SEESL),  23 structural system damage,  12–15; expected building performance level,  13f; interstory drifts,  14t; PBD in earthquake engineering,  12;

permanent drift,  14. See also fire following earthquake at building level structural type of buildings,  54 structure analysis,  34. See also building response to fire suppression,  59; firefighter response and subsequent,  51; fire spread algorithms,  59; model,  59–60. See also community subjected to FFE zone models,  32, 33. See also fire hazard scenario