Framework for earthquake-induced loss assessment of steel frame buildings–from building-specific to city-scale approaches

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FRAMEWORK FOR EARTHQUAKE-INDUCED LOSS ASSESSMENT OF STEEL FRAME BUILDINGS — FROM BUILDING-SPECIFIC TO CITY-SCALE

APPROACHES

by

Seong-Hoon Hwang

A dissertation submitted in partial fulﬁllment of the requirements for the degree of

Doctor of Philosophy

(Department of Civil Engineering and Applied Mechanics) in McGill University, Montréal

2017

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ACKNOWLEDGEMENTS

First and foremost, I would like to express my sincere gratitude to my academic advisor, Profes-sor Dimitrios G. Lignos for his continuous guidance and encouragement through my study. His invaluable contribution and insight into research work made possible the completion of this study. It has been deﬁnitely a pleasure and privilege being part of Professor Lignos research group.

I would like to thank all those who contributed to my doctoral research and made possible the completion of this thesis. A special thanks go to Dr. Ahmed Elkady for sharing his collapse analysis results for steel frame buildings with moment-resisting frames. I am also thankful to Dr. Tsuyoshi Hikino and Professor Masayoshi Nakashima, who shared the experimental data of the two structures tested at the E-Defense facility in Japan administered by the National Research Institute for Earth Science and Earthquake Mitigation (NIED).

This research was funded by a number of sources, including the Fonds de recherché du Québec – Nature et technologies (FQRNT), Projet de Recherché en Equipe (Award No. FQRNT 2013-PR-167747), McGill’s Faculty of Engineering through the McGill Engineering Doctoral Award (MEDA) program as well as École Polytechnique Fédérale de Lausanne (EPFL) for my one year stay in Switzerland. This ﬁnancial support is gratefully appreciated and acknowledged.

My special thanks go to my M.Sc advisor, Professor Sang Whan Han of Hanyang University, Seoul, Korea for giving me a great motivation to pursue my PhD study. I am also thankful to all my friends and colleagues at McGill University for their friendship and cooperation during my PhD years, including Sarven Akçelyan, Kyoungrae Baek, Julien Cravero, Kyu-Hyoung Lim, Moham-mad Motallebi Nasrabadi, Myoungho Yeo and many others. Special thanks are extended to my colleagues and members of the Resilient Steel Structures Laboratory of EPFL, including Subash Ghimire, Alexander Riley Hartloper, Hiroyuki Inamasu, Luisa Proietti Münzenmaier, Professor Alain Nussbaumer, Albano António Sousa and many others. The fellowship I shared with them during one year stay at EPFL made the time pass too quickly, and is deﬁnitely one of the most enjoyable memories I will take with me from EPFL.

I need to thank my friends – Dr. Sungchul Bae, Byoung-Gil Choi, Dr. Hyunwook Choo, Jungmin Hwang, Hantaek Jang, Minseok Jang, Myoungjun Joo, Ki-Byoung Kang, Byoung-Chul Kim, Hyochang Lee, Jinyoung Lee, Dr. Ki-Hoon Moon and Dr. Hyounoh Shin in South Korea and

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Chunhee Cho, Younho Rew, Ah-Young Seo and Seungwook Seok in the US for their thoughtful encouragement and true friendship.

Last, but not least, my deepest appreciation goes to my mother Young-Ae Lim, my father Il-Hyun Hwang, my brothers Ung Hwang, Ji-Hoon Hwang and In-Hoon Hwang, and my sister-in-laws Sehee Yoo and Seyoung Lee for their unconditional love, encouragement and support, without which I would not be here today. This thesis is dedicated to them.

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PREFACE

In accordance with the Guidelines for Thesis Preparation and the requirements of the Library and Archives Canada, this thesis is presented in the manuscript-based format. This thesis is a collection of the four research papers on improving earthquake-induced loss assessment. Authorships of the four research papers are explained as below.

Chapter 3:

Hwang SH, Lignos DG. Assessment of structural damage detection methods for steel structures using full-scale experimental data and nonlinear analysis. Submitted to Bulletin of Earthquake Engineering on 4 May 2017.

• Literature research and numerical analysis as well as writing of this publication were con-ducted by Hwang.

• Lignos served as an advisor to this research and edited the manuscript. Chapter 4:

Hwang SH, Lignos DG. 2017. Earthquake-induced loss assessment of steel frame buildings with special moment frames designed in highly seismic regions. Earthquake Engineering & Structural Dynamics, DOI: 10.1002/eqe.2898 (in press).

• Economic loss computation for steel frame buildings with moment-resisting frames and writ-ing of this manuscript were conducted by Hwang.

• Lignos served as an advisor to this research and edited the manuscript. Chapter 5:

Hwang SH, Lignos DG. 2017. Effect of modeling assumptions on the earthquake-induced losses and collapse risk of steel-frame buildings with special concentrically braced frames. ASCE Journal of Structural Engineering, 143(9): 04017116-1.

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• Structural analysis and economic loss computation for steel concentrically braced frames as well as writing of the manuscript were conducted by Hwang.

• Lignos served as an advisor to this investigation and edited the manuscript. Chapter 6:

Hwang SH, Lignos DG. 2017. Nonmodel-based framework for rapid seismic risk and loss assess-ment of instruassess-mented steel buildings. Submitted to Engineering Structures on 3 May 2017.

• Development of the proposed framework used for structural analysis and regional loss maps, and writing of this manuscript were conducted by Hwang.

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TABLE OF CONTENTS DEDICATION . . . . ii ACKNOWLEDGEMENTS . . . iii PREFACE . . . . v LIST OF FIGURES . . . . xi LIST OF TABLES . . . xx ABSTRACT. . . xxi RÉSUMÉ . . . xxiv CHAPTER 1. INTRODUCTION . . . 1

1.1 Problem Description and Motivation . . . 1

1.2 Scope and Research Objectives . . . 5

1.3 Organization of Dissertation . . . 5

2. LITERATURE REVIEW . . . 10

2.1 Introduction . . . 10

2.2 Methods for Structural Damage Diagnosis . . . 10

2.2.1 Structural health monitoring . . . 10

2.2.2 Simpliﬁed methods for estimating seismic demands in frame buildings . . . 24

2.2.3 Building assessment methodologies based on continuous models 29 2.2.4 Structural damage diagnosis based on fragility assessment . . . 32

2.2.5 City-scale damage distribution approaches . . . 37

2.2.6 Other methods for seismic assessment . . . 40

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2.3.1 Regional seismic loss assessment . . . 44

2.3.2 Building-speciﬁc seismic loss estimation . . . 49

2.4 Summary . . . 56

3. ASSESSMENT OF STRUCTURAL DAMAGE DETECTION METHODS FOR STEEL STRUCTURES USING FULL-SCALE EXPERIMENTAL DATA AND NONLINEAR ANALYSIS . . . 60

3.2 Review of Common Damage Identiﬁcation Techniques . . . 62

3.2.1 Frequency domain decomposition method . . . 63

3.2.2 Autoregressive with exogenous term method . . . 63

3.2.3 Numerical algorithm for subspace system identiﬁcation method 64 3.2.4 Wavelet-based damage-sensitive features . . . 65

3.3 Description of Shake Table Experiments & Nonlinear Building Models . . 67

3.3.1 Full-scale 4-story steel frame building with MRFs tested through collapse . . . 67

3.3.2 Single-story, chevron concentrically braced frame . . . 68

3.3.3 Nonlinear building models . . . 69

3.4 Efﬁciency of System Identiﬁcation Techniques for Assessing Structural Damage in Steel Frame Buildings . . . 71

3.4.1 Natural frequency as a damage indicator . . . 71

3.4.2 Equivalent damping ratio & mode shapes as damage indicators . 73 3.4.3 Wavelet-based DSFs as a damage indicator . . . 76

3.4.4 Proposed wavelet-based DSF1 to capture higher mode effect contributions . . . 77

3.5 Utilizing Damage-sensitive Features for Performance-based Seismic As-sessment . . . 79

3.6 Summary and conclusions . . . 79

4. EARTHQUAKE-INDUCED LOSS ASSESSMENT OF STEEL FRAME BUILD-INGS WITH SPECIAL MOMENT FRAMES DESIGNED IN HIGHLY SEIS-MIC REGIONS . . . 91

4.2 Overview of Employed Building-Speciﬁc Loss Estimation Methodology . 93 4.3 Design Characteristics of Archetype Steel Frame Buildings . . . 94

4.3.1 Site-speciﬁc seismic hazard curves . . . 95

4.3.2 Fragility and cost distribution functions . . . 95

4.4 Nonlinear Building Models and Response History Analyses through Col-lapse . . . 97

4.4.1 Nonlinear building models . . . 97

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4.5 Expected Losses Conditioned on Seismic Intensity . . . 99

4.6 Expected Annual Losses . . . 103

4.7 Present Value of Life-Cycle Costs . . . 105

4.8 Conclusions . . . 106

5. EFFECT OF MODELING ASSUMPTIONS ON THE EARTHQUAKE-INDUCED LOSSES AND COLLAPSE RISK OF STEEL-FRAME BUILDINGS WITH SPECIAL CONCENTRICALLY BRACED FRAMES . . . 123

5.2 Overview of Employed Seismic Loss Estimation Methodology . . . 125

5.3 Description of Steel Frame Buildings with SCBFs . . . 128

5.3.1 Site-speciﬁc seismic hazard curves . . . 129

5.3.2 Assumed fragility curves and cost distribution functions . . . . 129

5.4 Nonlinear Building Models and Simulation of Structural Collapse . . . 130

5.4.1 Structural collapse simulations and associated collapse risk . . . 132

5.5 Expected Losses Conditioned on Seismic Intensity . . . 134

5.6 Expected Annual Losses . . . 136

5.7 Limitations . . . 138

5.8 Conclusions . . . 139

6. NONMODEL-BASED FRAMEWORK FOR RAPID SEISMIC RISK AND LOSS ASSESSMENT OF INSTRUMENTED STEEL BUILDINGS . . . 157

6.2 Proposed Framework for Performance-based Rapid Assessment of Steel Frame Buildings . . . 158

6.2.1 System identiﬁcation . . . 159

6.2.2 Wavelet-based damage-sensitive features . . . 160

6.2.3 Approximate method for computing story-based EDPs . . . 162

6.3 Application of Simpliﬁed Seismic Assessment Methodology in Instru-mented Steel Frame Buildings . . . 167

6.3.1 Case study instrumented building . . . 167

6.3.2 Predicted engineering demand parameters and earthquake-induced economic losses . . . 168

6.3.3 Rapid seismic assessment at a “city-scale” . . . 172

6.4 Limitations of the Proposed Framework . . . 174

6.5 Summary and Conclusions . . . 174

7. SUMMARY, CONCLUSIONS, LIMITATIONS AND FUTURE WORK . . . 192

7.1 Overview . . . 192

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7.3 Economic Seismic Losses of Steel Frame Buildings with Special Moment

Frames (Chapter 4) . . . 194

7.4 Collapse Risk and Loss Assessment of Steel Frame Buildings with Con-centrically Braced Frames (Chapter 5) . . . 196

7.5 Nonmodel-based Framework for Estimating Story-based Engineering De-mand Parameters and City-scale Simulation in Highly Seismic Regions (Chapter 6) . . . 197

7.6 Main Research Contributions . . . 198

7.7 Limitations and Recommendations for Future Work . . . 199

BIBLIOGRAPHY . . . 202

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LIST OF FIGURES

Figure

1.1 Christchurchs central business district after the 2011 Christchurch earthquake [Image courtesy of John Kirk-Anderson (Stuart 2015)]. . . 8 1.2 Example of business interruption after the 2012 Emilia, Northern Italy

earth-quake: (a) shop inside the historic center; and (b) industrial building [adopted from Decanini et al. (2012)]. . . . 8 1.3 General overview of performance-based earthquake engineering. . . 9 2.1 Equivalent continuous model of multi-story building [adopted from Miranda

(1999)]. . . 58 2.2 ShakeMaps for the 1987 Mw 5.9 Whittier Narrows earthquake in California (on

October 1, 1987). . . 59 3.1 Full-scale 4-story steel frame building: (a) overview of test setup; (b) plan and

elevation view; (c) peak SDR distribution in the x loading direction; and (d) peak SDR distribution in the y loading direction. . . . 82 3.2 Large-scale model of a single-story chevron CBF: (a) elevation view of test

spec-imen (adopted from Okazaki et al. (2013a)); (b) test-bed system (adopted from Okazaki et al. (2013a)); and (c) peak SDRs at various ground motion intensities. . 82 3.3 Steel ofﬁce buildings with perimeter MRF and CBF for supplementary case studies. 83 3.4 Nonlinear building models of steel frame buildings: (a) 2-D model of 8-story

steel frame building with MRF; (b) 2-D model of 3-story steel frame building with CBF; (c) validation of calibrated bare steel beam with RBS connection [data from Gilton et al. (2000)]; and (d) validation of calibrated steel HSS braces [data from Han et al. (2007)]. . . 84 3.5 Dynamic analysis and peak SDR distributions: (a) incremental dynamic analysis

through collapse; (b) peak SDR distribution for the 8-story steel MRF at selected seismic intensities; and (c) peak SDR distribution for the 3-story CBF at selected seismic intensities. . . 84 3.6 Natural frequencies, mode shapes and damping ratios of the 4-story steel MRF

building (y loading direction) tested at E-Defense. . . 85 3.7 Identiﬁed natural frequency and its decrease in steel MRF buildings. . . 86 3.8 Identiﬁed natural frequency and frequency decrease in steel CBFs. . . 86

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3.9 Estimated damping ratio of the ﬁrst mode for test structures with MRFs: (a) y loading direction of the 4-story MRF building at E-Defense facility; and (b) numerical model of the 8-story MRF building. . . 87 3.10 Estimated damping ratio of the ﬁrst mode for CBFs: (a) single-story CBF at

E-Defense facility; and (b) numerical model of the 3-story CBF. . . 87 3.11 Wavelet-based DSF1for all the test structures. . . 88 3.12 Wavelet-based DSFs and PSD of the single-story CBF at E-Defense facility. . . . 88 3.13 Power spectral densities of the 8-story steel MRF subjected to two different

ground motions: (a) IV79cal; and (b) IV79chi. . . 89 3.14 Logarithmic difference between PSDs of the ground motions from LMSR-N set

and white noise excitation. . . 89 3.15 Comparison of wavelet-based DSFs of the 8-story steel MRF. . . 90 3.16 Scatter plots of wavelet-based DSF determined from the roof versus story-based

peak EDPs for all the case studies examined. . . 90 3.17 Scatter plots of wavelet-based DSF versus maximum EDPs for the 8-story MRF. . 90 4.1 Typical archetype steel frame buildings: (a) plan view; and (b) elevation of the

4-story SMFs. . . 114 4.2 Seismic hazard curves for bare models of all the steel buildings with SMFs

(SCWB> 1.0). . . 114 4.3 Example of analytical model representation for steel frame buildings with SMFs:

(a) 2-D analytical model for the 4-story steel frame building (CG-model); (b) moment-chord rotation relation for composite beam with RBS (data from Zhang and Ricles (2006)); and (c) moment-chord rotation relation for composite beam as part of a single-plate shear tab connection (data from Liu and Astaneh-Asl (2000)). . . 115 4.4 Critical EDPs and collapse fragility curves for steel frame buildings with SMFs. . 116 4.5 Normalized loss vulnerability curves for steel frame buildings with SMFs

condi-tioned on seismic intensity (B-models). . . 116 4.6 Normalized expected losses for steel frame buildings with SMFs at selected

seis-mic intensities (B-models). . . 117 4.7 Normalized expected losses for steel frame buildings with SMFs at selected

seis-mic intensities (CG-models). . . 118 4.8 Median values of EDPs of interest along the building height for CG-models of

the 8-story steel frame buildings with SMFs at selected seismic intensities. . . 119 4.9 Illustration of normalized expected annual losses for steel frame buildings with

SMFs. . . 120 4.10 EDPs from the 12-story buildings with/without the gravity framing (B- and

CG-models). . . 121 4.11 Normalized present value for CG-models of steel buildings with SMFs. . . . 122 5.1 Archetype steel frame buildings with perimeter SCBFs: (a) typical plan view;

and (b) elevation view of the 3-story SCBF. . . 147 5.2 Design spectrum and site-speciﬁc seismic hazard curves for bare model

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5.3 Example of fragility curves for damage state of global buckling for round HSS braces: (a) univariate fragility curve; and (b) dual-parameter (global slenderness KL/r) fragility curves [adopted from Lignos and Karamanci (2013a)]. . . 148 5.4 Analytical model representation of steel frame buildings with SCBFs: (a) 2-D

analytical model including the gravity framing (CG-model); (b) description of the steel brace component model; (c) axial force-deformation relation for rect-angular HSS brace section [data from Han et al. (2007)]; and (d) moment-chord rotation relation for composite beam in single-plate shear tab connections [data from Liu and Astaneh-Asl (2000)]. . . 149 5.5 IDA curves for the 3- and 12-story steel frame buildings with perimeter SCBFs

(CG-models). . . 150 5.6 Collapse fragility curves for steel frame buildings with perimeter SCBFs with/without

gravity framing system. . . 151 5.7 Collapse mechanisms for the 3- and 6-story archetypes based on B- and CG-models.152 5.8 Mean annual frequency of collapseλcand the corresponding collapse probability

over 50 years Pc(in 50 years) for the analytical model type of archetype buildings

with perimeter SCBFs. . . 153 5.9 Normalized loss vulnerability curves for steel frame buildings with perimeter

SCBFs designed for SDC Dmaxand Dminconditioned on seismic intensity. . . 154 5.10 Normalized expected losses of steel frame buildings with perimeter SCBFs

de-signed for SDC Dmaxconditioned on selected seismic intensities. . . 155 5.11 Normalized expected losses of the 12-story steel frame building with perimeter

SCBFs designed for SDC Dminconditioned on selected seismic intensities. . . 155 5.12 Normalized expected annual losses and present values for steel frame buildings

with SCBFs. . . 156 6.1 Flowchart of the proposed framework for rapid seismic risk and loss assessment

of instrumented steel frame buildings. . . 180 6.2 Stabilization diagram of the y loading direction of the 4-story steel frame building

with MRFs tested at E-Defense facility. . . 181 6.3 Wavelet-based DSF values in the y loading direction of the 4-story steel frame

building with MRFs tested at E-Defense facility. . . 181 6.4 Flowchart for the development of the approximate method for story-based EDP

computations. . . 182 6.5 Typical 8-story archetype steel frame building: (a) plan view; and (b) elevation. . 182 6.6 Example of nonlinear building model representation: (a) 2-D numerical model

of the 8-story steel frame building; and (b) component deterioration model vali-dation (data from Gilton et al. (2000)). . . 183 6.7 Scatter plots of wavelet-based DSF versus peak SDRs of the 8-story MRF building.183 6.8 Diagnostic residual plots for story-based EDPs of steel frame buildings with 8

stories or less. . . 184 6.9 Diagnostic residual plots for the 8-story steel frame building designed with SCWB

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6.10 Diagnostic residual plots for the 12-story steel frame building designed with SCWB≥ 1.0. . . 186 6.11 Predicted versus simulated story-based EDPs along the height of the 8-story steel

frame building designed with SCWB≥ 1.0. . . 187 6.12 Fifteen-story Government steel frame ofﬁce building (CSMIP 24569); (a) overview;

and (b) plan, and elevation view of the building (images from the US National Center for Engineering Strong Motion Data at http://strongmotioncenter.org). . . 188 6.13 Predicted story-based EDPs for the 15-story Government steel frame ofﬁce

build-ing (CSMIP 24569). . . 188 6.14 Fragility curves for typical pre- and post-Northridge fully-restrained

beam-to-column connections and conventional and sliding gypsum wallboard partitions. . 189 6.15 Normalized expected losses for 15-story Government steel frame ofﬁce building

(CSMIP 24569). . . 189 6.16 “City-scale” generalized damage and expected loss maps for Los Angeles after

the 1994 Northridge earthquake. . . 190 6.17 Loss disaggregation maps for the city of Los Angeles after the 1994 Northridge

earthquake; (a) losses due to repairs in pre-Northridge beam-to-column moment connections; (b) losses due to repairs in conventional gypsum wallboard parti-tions; (c) losses due to repairs in retroﬁtted beam-to-column moment connec-tions; and (d) losses due to repairs in sliding gypsum wallboard partitions. . . 191 A.1 Normalized loss vulnerability curves for steel frame buildings with perimeter

SMFs (B-models). . . 237 A.2 Normalized loss vulnerability curves for steel frame buildings with perimeter

SMFs (CG-models). . . 240 B.1 Normalized loss vulnerability curves for steel frame buildings with perimeter

SCBFs designed for SDC Dmax conditioned on seismic intensity based on uni-variate fragility curve (B-models). . . 244 B.2 Normalized loss vulnerability curves for steel frame buildings with perimeter

SCBFs designed for SDC Dmax conditioned on seismic intensity based on dual-parameter (global slenderness) fragility curve (B-models). . . 245 B.3 Normalized loss vulnerability curves for steel frame buildings with perimeter

SCBFs designed for SDC Dmax conditioned on seismic intensity based on dual-parameter (local slenderness) fragility curve (B-models). . . 246 B.4 Normalized loss vulnerability curves for steel frame buildings with perimeter

SCBFs designed for SDC Dmax conditioned on seismic intensity based on uni-variate fragility curve (CG-models). . . 247 B.5 Normalized loss vulnerability curves for steel frame buildings with perimeter

SCBFs designed for SDC Dmax conditioned on seismic intensity based on dual-parameter (global slenderness) fragility curve (CG-models). . . 248 B.6 Normalized loss vulnerability curves for steel frame buildings with perimeter

SCBFs designed for SDC Dmax conditioned on seismic intensity based on dual-parameter (local slenderness) fragility curve (CG-models). . . 249

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B.7 Normalized loss vulnerability curves for steel frame buildings with perimeter SCBFs designed for SDC Dmin conditioned on seismic intensity based on uni-variate fragility curve (B-models). . . 250 B.8 Normalized loss vulnerability curves for steel frame buildings with perimeter

SCBFs designed for SDC Dmin conditioned on seismic intensity based on dual-parameter (global slenderness) fragility curve (B-models). . . 251 B.9 Normalized loss vulnerability curves for steel frame buildings with perimeter

SCBFs designed for SDC Dmin conditioned on seismic intensity based on dual-parameter (local slenderness) fragility curve (B-models). . . 252 B.10 Normalized loss vulnerability curves for steel frame buildings with perimeter

SCBFs designed for SDC Dmin conditioned on seismic intensity based on uni-variate fragility curve (CG-models). . . 253 B.11 Normalized loss vulnerability curves for steel frame buildings with perimeter

SCBFs designed for SDC Dmin conditioned on seismic intensity based on dual-parameter (global slenderness) fragility curve (CG-models). . . 254 B.12 Normalized loss vulnerability curves for steel frame buildings with perimeter

SCBFs designed for SDC Dmin conditioned on seismic intensity based on dual-parameter (local slenderness) fragility curve (CG-models). . . 255 C.1 Diagnostic residual plots for story-based EDPs of steel frame buildings with 8

stories or less. . . 257 C.2 Diagnostic residual plots for story-based EDPs of steel frame buildings with 9 to

20 stories. . . 258 C.3 Box-whisker plot of simulated-to-predicted EDP ratios at the three selected

seis-mic hazard levels for the 2-story steel frame building designed with SCWB≥ 1.0 for LMSR-N set. . . 259 C.4 Box-whisker plot of simulated-to-predicted EDP ratios at the three selected

seis-mic hazard levels for the 8-story steel frame building designed with SCWB≥ 1.0 for LMSR-N set. . . 265

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C.10 Box-whisker plot of simulated-to-predicted EDP ratios at the three selected seis-mic hazard levels for the 8-story steel frame building designed with SCWB≥ 1.5 for LMSR-N set. . . 266 C.11 Box-whisker plot of simulated-to-predicted EDP ratios at the three selected

seis-mic hazard levels for the 2-story steel frame building designed with SCWB≥ 1.0 for FEMA P695 ground motion set. . . 274 C.19 Box-whisker plot of simulated-to-predicted EDP ratios at the three selected

seis-mic hazard levels for the 4-story steel frame building designed with SCWB≥ 2.0 for FEMA P695 ground motion set. . . 279

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C.24 Box-whisker plot of simulated-to-predicted EDP ratios at the three selected seis-mic hazard levels for the 8-story steel frame building designed with SCWB≥ 1.0 for FEMA P695 ground motion set. . . 280 C.25 Box-whisker plot of simulated-to-predicted EDP ratios at the three selected

seis-mic hazard levels for the 20-story steel frame building designed with SCWB≥ 2.0 for FEMA P695 ground motion set. . . 288 D.1 Predicted versus simulated story-based EDPs along the height of the 2-story steel

frame building with perimeter SMFs designed with SCWB≥ 1.0 for LMSR-N set.290 D.2 Predicted versus simulated story-based EDPs along the height of the 2-story steel

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D.9 Predicted versus simulated story-based EDPs along the height of the 8-story steel frame building with perimeter SMFs designed with SCWB≥ 2.0 for LMSR-N set.298 D.10 Predicted versus simulated story-based EDPs along the height of the 12-story

steel frame building with perimeter SMFs designed with SCWB≥ 1.0 for LMSR-N set. . . 299 D.11 Predicted versus simulated story-based EDPs along the height of the 12-story

steel frame building with perimeter SMFs designed with SCWB≥ 2.0 for LMSR-N set. . . 304 D.16 Predicted versus simulated story-based EDPs along the height of the 2-story steel

frame building with perimeter SMFs designed with SCWB ≥ 1.0 for FEMA P695 ground motion set. . . 305 D.17 Predicted versus simulated story-based EDPs along the height of the 2-story steel

frame building with perimeter SMFs designed with SCWB ≥ 1.0 for FEMA P695 ground motion set. . . 311

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D.23 Predicted versus simulated story-based EDPs along the height of the 8-story steel frame building with perimeter SMFs designed with SCWB ≥ 1.5 for FEMA P695 ground motion set. . . 312 D.24 Predicted versus simulated story-based EDPs along the height of the 8-story steel

frame building with perimeter SMFs designed with SCWB ≥ 2.0 for FEMA P695 ground motion set. . . 313 D.25 Predicted versus simulated story-based EDPs along the height of the 12-story

steel frame building with perimeter SMFs designed with SCWB≥ 1.0 for FEMA P695 ground motion set. . . 314 D.26 Predicted versus simulated story-based EDPs along the height of the 12-story

steel frame building with perimeter SMFs designed with SCWB≥ 2.0 for FEMA P695 ground motion set. . . 319 E.1 Predicted story-based EDPs and normalized expected losses for the instrumented

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LIST OF TABLES

Table

2.1 Basic scores and modiﬁers for steel moment-resisting frame buildings in FEMA P-154 (FEMA 2015a). . . 57 3.1 Natural frequencies and equivalent damping ratios of the test structures tested at

full-scale at the E-Defense shake table. . . 81 3.2 Comparisons of estimated mode shapes based on the modal assurance criterion

for the steel MRFs. . . 81 3.3 Comparisons of estimated mode shapes based on modal assurance criterion for

the 3-story CBF test structure. . . 81 4.1 Cost estimates for steel frame buildings studied. . . 109 4.2 Fragility and cost estimates for steel frame buildings with perimeter SMFs studied 110 4.3 Example of damageable components for the 4-story steel frame building with

perimeter SMFs designed with SCWB> 1.0. . . 112 4.4 Dynamic characteristics and constituents of expected annual losses for archetype

buildings. . . 113 5.1 Dual-parameter fragility distribution functions for steel braces (Lignos and

Kara-manci 2013a). . . 142 5.2 Fragility and cost estimates for steel frame buildings with perimeter SCBFs. . . . 143 5.3 Median and logarithmic standard deviation of collapse fragility curves for all the

analytical model representations of the archetype steel buildings with SCBFs. . . 145 5.4 Normalized EALs for archetype buildings with SCBFs based on drift-based steel

brace fragility curves. . . 146 6.1 Range of predictor variables for peak story-based EDPs based on the building

response database. . . 176 6.2 Regression coefﬁcients for story-based EDPs of steel frame buildings with less

than 8 stories. . . 176 6.3 Regression coefﬁcients for story-based EDPs of steel frame buildings with 9 to

20 stories. . . 177 6.4 System identiﬁcation for the 15-story instrumented steel frame ofﬁce building in

Los Angeles. . . 177 6.5 Fragility and cost estimates for the 15-story Government steel frame ofﬁce building.178 E.1 Dynamic properties of instrumented buildings. . . 321

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ABSTRACT

Framework for earthquake-induced loss assessment of steel frame buildings — from building-speciﬁc to city-scale approaches

by

Seong-Hoon Hwang

Department of Civil Engineering and Applied Mechanics McGill University, Montréal

Dimitrios G. Lignos, Advisor

Building speciﬁc and city-scale structural damage assessment methodologies are essential in order to predict and manage the socio-economic consequences within a region in the aftermath of an earthquake. In that respect, nonmodel-based as well as model-based approaches and tools have been widely used. Such approaches can facilitate the decision-making for emergency rescue force allocation and the minimization of business interruption due to downtime. The same tools can also quantify the earthquake-induced losses due to repairs associated with damage into the structural and non-structural content of building assets.

The first overarching goal of this thesis is to develop an efficient decision-making framework for rapid earthquake-induced risk and loss assessment of steel frame buildings. The second one is to develop tools and metrics that facilitate reliable building specific earthquake-induced loss as-sessment. The first goal is accomplished by combining concepts from structural health monitoring and performance-based earthquake engineering. In particular, a non-model based approach is de-veloped that can facilitate a near real-time and automated damage assessment of instrumented steel frame buildings. This approach is also extended at the city-level for disaster risk management of earthquake-prone urban areas. The second goal of this thesis is achieved through the utilization and refinement of model-based approaches for building specific earthquake-induced loss assess-ment. The objective in this case is to examine and benchmark the effect of modeling assumptions on structural/non-structural damage control of conventional steel frame buildings with moment-resisting frames (MRFs) and concentrically braced frames (CBFs).

In order to develop a nonmodel-based framework for seismic risk assessment of steel frame buildings, an extensive number of damage indicators computed based on nonmodel-based system

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identification techniques and wavelet analysis are evaluated. The efficiency of these indicators to infer the damage state of conventional steel MRFs and CBFs is evaluated through the utilization of landmark full-scale shake table experiments that examined the inelastic behavior of steel MRFs and CBFs at various seismic intensities. This data is complemented with nonlinear simulations. It is found that wavelet-based damage-sensitive features (DSFs) are well correlated with commonly used story-based engineering demand parameters (EDPs). A refined DSF is proposed that is suit-able for damage detection in buildings that higher mode effects are important.

A nonmodel-based framework is developed that utilizes the refined wavelet-based DSF and ba-sic building geometric information to infer the building damage state at a given seismic intensity. It is shown that story-based EDPs such as peak story drift ratios, peak absolute floor accelerations and residual story drift ratios are predicted with a reasonable accuracy. The efficiency of the pro-posed framework is validated with a number of instrumented steel frame buildings that experienced the 1994 Northridge earthquake in Los Angeles. It is shown that if the building content is known the proposed framework can facilitate near real-time building-specific seismic risk and loss assess-ment. The nonmodel-based framework is also extended at the city-scale through the development of generalized earthquake-induced damage and loss maps. The same framework can facilitate the decision-making for effective pre-disaster measures for earthquake disaster risk management of building assets.

In order to provide guidance in model-based approaches for building-specific seismic risk and loss assessment, the influence of modeling assumptions on the earthquake-induced loss assessment of steel frame buildings is examined. Typical office steel frame buildings designed with MRFs and CBFs are employed for this purpose. The influence of modeling choices is examined conditioned on a loss-metric of interest. It is shown that for seismic events with low probabilities of occurrence (i.e., 2% probability of occurrence in 50 years), losses due to demolition and collapse may be significantly overestimated when the loss computations are based on numerical models that ignore the composite beam effects and the interior gravity framing system. For frequent seismic events (i.e., 50% probability of occurrence in 50 years), building losses are dominated by non-structural content repairs. In this case, the choice of the numerical model representation of the steel frame building becomes insignificant. Losses due to demolition and collapse in steel frame buildings with MRFs designed with a strong-column/weak-beam (SCWB) ratio larger than 2.0 are reduced by a factor of two compared with those in the same frames designed with a SCWB ratio larger than 1.0 (i.e., code-based design). The expected annual losses (EALs) of steel frame buildings with MRFs vary from 0.38% to 0.74% over the building life expectancy. On the other hand, EALs in CBFs vary from 0.74% to 0.87%. In steel MRFs and CBFs, the EALs are dominated by repairs of acceleration-sensitive non-structural content followed by repairs of drift-sensitive non-structural

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components. However, an appreciable contributor to EALs in steel frame buildings with CBFs is structural repairs due to steel brace ﬂexural buckling. It is found that the effect of the employed strong-column/weak-beam ratio on EALs is negligible. It is advisable to employ a combination of loss metrics to assess the earthquake-induced losses in steel frame buildings depending on the seismic performance level of interest.

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RÉSUMÉ

Méthodologie d’évaluation des pertes causées par les séismes sur les bâtiments en acier — Plusieurs approches : de l’échelle du bâtiment à l’échelle de la ville

par

Seong-Hoon Hwang

Département de génie civil et mecanique appliquée Université McGill, Montréal

Dimitrios G. Lignos, Directeur de thèse

Les méthodologies d’évaluation de l’endommagement des structures, spéciﬁque à un bâtiment ou à l’échelle de la ville, sont essentielles pour prédire et gérer les conséquences socio-économiques d’un tremblement de terre dans une région. Ainsi, plusieurs approches et outils, avec ou sans modélisation de l’ouvrage, ont été largement utilisés. Ces approches peuvent faciliter la prise de décision pour déployer les forces de secours en cas d’urgence et minimiser les pertes d’exploitation dues à la cessation d’activité. Ces mêmes outils peuvent également quantiﬁer les pertes dues aux réparations suite à des dommages structuraux et non-structuraux des ouvrages étudiés.

L’objectif d’ensemble de cette thèse est de développer un cadre efﬁcace de prise de décision pour évaluer rapidement les risques et les pertes causés par les séismes sur les bâtiments en acier. Le deuxième objectif est de développer des outils et des métriques qui permettent une estimation ﬁable des pertes dues aux séismes à l’échelle du bâtiment. Le premier but a été atteint en combi-nant des concepts issus de la surveillance de l’état des structures (structural health monitoring) et de la conception parasismique axée sur la performance (performance-based earthquake engineer-ing). En particulier, une approche sans modèle préalable a été développée, qui peut permettre une évaluation de l’endommagement automatisée et quasiment en temps réel pour des bâtiments en acier instrumentés. Cette approche a été étendue à l’échelle de la ville pour la gestion des risques liés aux catastrophes dans les zones urbaines sujettes aux tremblements de terre. Le deuxième but a été rempli en améliorant des approches d’estimation de l’endommagement qui s’appuient sur des modèles, à l’échelle du bâtiment. L’objectif, dans ce cas, est d’examiner et d’évaluer l’effet des hypothèses de modélisation sur le contrôle de l’endommagement structurel/non-structurel subi par des bâtiments à charpente en acier conventionnelle avec des cadres rigides (moment-resisting

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frames ou MRF) ou des cadres à contreventement concentrique (concentrically braced frames ou CBF).

Afin de développer un cadre d’évaluation du risque sismique pour les bâtiments à ossature métallique sans recourir à des modèles, de nombreux indicateurs d’endommagement, calculés avec des techniques d’identification de système sans modèle et des méthodes d’analyse en ondelettes, ont été évalués. L’efficacité de ces indicateurs à inférer l’état d’endommagement de structures en acier conventionnelles employant des MRF ou des CBF a été appréciée grâce à des cas d’études expérimentaux sur table vibrante qui ont permis d’examiner le comportement plastique de ces cadres en acier pour différentes intensités sismiques. Ces données ont été complétées par des simulations non-linéaires. Nous avons constaté que les indicateurs d’endommagement déterminés par ondelettes sont bien corrélés avec des paramètres de demande sismique inter-étages courants. Un indicateur a été amélioré et proposé pour permettre la détection d’endommagement dans les bâtiments où les effets des modes supérieurs sont importants.

Une méthodologie non-basée sur la modélisation de l’ouvrage a été développée; elle utilise l’indicateur amélioré déterminé par ondelettes et des propriétés géométriques basiques du bâti-ment pour en déduire l’état d’endommagebâti-ment de la structure à une intensité sismique donnée. Il est montré que des paramètres de demande sismique tels que les déformations inter-étages maxi-males, les accélérations absolues des planchers maximales et les déformations inter-étages résidu-elles sont prédites avec une précision convenable. L’efficacité de la méthodologie proposée a été validée avec de nombreux bâtiments en acier instrumentés qui ont subi le tremblement de terre de Northridge, à Los Angeles, en 1994. Il apparaît que cette méthodologie peut faciliter une éval-uation quasiment en temps réel du risque sismique et de l’endommagement d’un bâtiment, si le contenu de ce bâtiment est connu. La méthodologie sans modèle est également étendue à l’échelle de la ville par le développement de cartes de dommages et de pertes post-séisme généralisées. La même méthodologie peut faciliter la prise de décision pour des mesures préventives efficaces afin de gérer les risques de désastre sismique concernant les infrastructures.

Afin de fournir des indications pour les approches nécessitant un modèle, pour estimer le risque sismique et les pertes touchant un bâtiment particulier, l’influence des hypothèses de modélisation sur l’évaluation des pertes causées par les séismes sur les bâtiments en acier a été examinée. Des bâtiments de bureaux typiques à ossature en acier, conçus avec des MRF et des CBF, ont été pris comme exemples. L’influence des facteurs de modélisation a été évaluée par l’intermédiaire d’une métrique d’estimation d’endommagement pertinente. Nous avons montré que pour les séismes avec une faible probabilité d’occurrence (soit une probabilité d’occurrence en 50 ans de 2%), les pertes dues à la ruine de la structure et à sa démolition peuvent être surestimées de manière sig-nificative lorsque les calculs d’endommagement proviennent de modèles numériques qui ignorent

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les effets de poutre composite et l’action du système de descente des charges verticales. Pour les séismes fréquents (c’est-à-dire avec une probabilité d’occurrence en 50 ans de 50%), les ré-parations des composants non-structuraux sont prépondérantes dans les pertes du bâtiment. Dans ce cas, le choix de la représentation du modèle numérique du bâtiment en acier devient néglige-able. Les pertes dues à la ruine de la structure et à sa démolition pour les bâtiments en acier utilisant des MRF conçus avec un ratio « poteau fort – poutre faible » supérieur à 2.0 sont ré-duites de moitié par rapport aux pertes associées aux mêmes portiques avec un ratio de 1.0 (soit la recommandation du code). Les pertes annuelles prévisionnelles pour les bâtiments à charpente en acier utilisant des MRF varient de 0.38% à 0.74% sur la durée de vie de la structure. En re-vanche, ce chiffre varie de 0.74% à 0.87% pour des CBF. Pour les MRF et les CBF en acier, les pertes annuelles prévisionnelles sont dominées par les réparations des composants non-structuraux sensibles aux accélérations, suivies par celles des composants non-structuraux sensibles au dé-placement. Cependant, dans le cas des bâtiments en acier employant des CBF, les réparations structurelles dues au ﬂambement des contreventements en acier contribuent aux pertes annuelles prévisionnelles de manière non négligeable. Nous avons montré que le ratio « poteau fort – poutre faible » utilisé a peu d’impact sur le calcul des pertes annuelles prévisionnelles. Il est préférable de combiner les métriques d’estimation d’endommagement, en fonction du niveau de performance sismique attendu, pour évaluer les dommages causés par les tremblements de terre sur les bâtiments en acier.

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CHAPTER 1

INTRODUCTION

1.1 Problem Description and Motivation

During and after natural disasters, the primary objectives of our society are to achieve the protection of life and to preserve the quality of life such that the continuous functionality of our built environ-ment (e.g., buildings, bridges, transportation, telecommunication and electrical supply networks) can be achieved. During earthquakes, socio-economical losses and extensive community disrup-tion are challenges that need to be addressed in order to embrace community disaster resilience (Bruneau et al. 2003). Since the 1994 Northridge in the United States (US) and 1995 Hyogoken-Nanbu (Kobe) earthquake in Japan, significant improvements have been made in seismic design provisions (AIJ 2007; CSA 2009; AISC 2010a,b; Mitchell et al. 2010). This is confirmed from the small number of building collapses and the observed seismic performance of recently engineered facilities in the aftermath of large magnitude earthquakes. However, important deficiencies still remain in our built environment; following the lessons learned from recent earthquakes, a period of time is required to assess earthquake-induced damage to an individual building and its con-tents, and ascertain whether the building can be safely re-occupied through detailed engineering inspections in the aftermath of an earthquake (Comerio 2006). This time period may cause serious community disruption after earthquakes.

For example, the February 27 2010 Chile earthquake with a moment magnitude scale Mw of

8.8 struck central Chile. Elnashai et al. (2010) reported that the earthquake affected more than 800,000 people. The economic losses were estimated to be $30 billion US dollars (USD) (loss of infrastructure: $20.9 billion, loss of production: $7.6 billion, other costs such as nutrition and debris removal: $1.1 billion), which is equivalent to nearly 17% of the national Gross Domes-tic Product (GDP) in 2009 (Elnashai et al. 2010). It was also reported that severe functionality problems occurred in various infrastructure systems.

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in New Zealand on February 22 2011. The Canterbury Earthquakes Royal Commission (CERC 2012) reported that during the earthquake more than 185 people were deceased. The earthquake caused substantial monetary losses; the New Zealand Treasury estimated the capital cost to be ap-proximately $40 billion New Zealand dollars (NZD), which is equivalent to apap-proximately 20% of the national GDP in 2011 (New Zealand Treasury 2013). The ﬁnancial losses were mainly due to rebuilding and repair of damaged buildings resulting from the earthquake; the Reserve Bank of New Zealand estimated the economic losses of $20 billion NZD in 2011 prices (Parker and Steenkamp 2012). This has a signiﬁcant impact on (re-)insurance companies. Moreover, it was also reported that more than 60% of the businesses in Christchurch’s central business dis-trict were forced to close at least temporarily (Stevenson et al. 2011; CERC 2012). Figure 1.1 shows Christchurch’s central business district that were closed for many months after the 2011 Christchurch earthquake.

The 2011 Tohoku-Oki earthquake with a magnitude Mwof 9.0 occurred off the Sanriku coast

of Japan on March 11 2011. The Government of Japan (2012) reported that this event caused more than 15,800 deaths, 3200 missing and 342,000 homeless. Approximately, 190,000 buildings were damaged, among which 45,700 totally collapsed due to the earthquake followed by a tsunami (Norio et al. 2011; Okazaki et al. 2013b). It is also reported that several nuclear power plants and thermal power plants were heavily damaged during the earthquake. The earthquake also af-fected Japan’s transportation systems (i.e., temporary shutdown of railways, ports, and airports). This disaster caused direct economic losses of at least $211.3 billion USD, which is equivalent to approximately 3.6% of the national GDP in 2011 (Government of Japan 2012).

Relatively moderate earthquakes can also trigger serious community disruption due to function-ality problems of the built environment. A representative example is the Mw 5.9 Emilia, Northern

Italy earthquake that occurred in May 20 2012. This earthquake highlights its potential for produc-ing large economic losses compared to relatively moderate earthquake intensities. The earthquake caused 7 deaths, 47 injuries, and 5292 homeless (Decanini et al. 2012). A second mainshock struck the same region in May 29 2012 and caused a further 20 deaths, 350 injuries and 15,000 homeless (Magliulo et al. 2014). This earthquake series caused signiﬁcant ﬁnancial losses due to business interruption amounted to C5 billion euros while the direct economic losses were estimated to be about C1 billion euros (Magliulo et al. 2014). Decanini et al. (2012) reported that 13,000 people were temporary unemployed, and more than 70% of the business activities inside the historical centers of the affected municipalities was interrupted. Figure 1.2 illustrates the business inter-ruption after the 2012 Emilia, Northern Italy earthquake; the damaged commercial activity in a historic center and the shutdown of an industrial building are shown in Figures 1.2(a) and 1.2(b), respectively.

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Another example is the Mw 5.8 Virginia, US earthquake on August 23 2011. This earthquake

struck most of the east coast of the US but caused only minimal structural damage. However, sig-niﬁcant business interruptions (especially in telecommunication and electric power supply) were reported from New York City in the north to Richmond, Virginia. The ﬁnancial losses were esti-mated at $200 million to $300 million USD with total insured losses of approximately $100 million USD (Morello and Wiggins 2011). In addition, the earthquake caused widespread confusion be-tween the public and emergency-response personnel on how to respond to such hazard (Kang and Muin 2011; Lowy 2011; Melvin 2011).

A recent study conducted by AIR Worldwide (2013), commissioned by the Insurance Bureau of Canada suggested that major earthquakes could cause signiﬁcant economic losses within British Columbia and the Ontario/Québec regions: the total direct and indirect economic losses associ-ated with a Mw9.0 earthquake scenario (i.e., The Western Cascadia subduction scenario) in British

Columbia were estimated to be almost $75 billion Canadian dollars (CAD) with total insured losses of $20 billion CAD; and the total economic losses computed based on a Mw 7.1 earthquake

sce-narios (i.e., the Eastern Charlevoix crustal scenario) in the Québec City-Montréal-Ottawa corridor would be approximate $61 billion CAD with total insured losses of $12 billion CAD.

A recent study by the Swiss Seismological Service (Wiemer et al. 2016) highlighted that an earthquake poses the potential for high economic losses and extensive community disruption in Switzerland; a repeat of the Mw 6.7 1356 Basel earthquake with return period of 1000 to 2000

years would result in direct economic losses of 70 to 140 billion Swiss francs (CHF), 600 to 1000 fatalities, and 45,000 to 1,600,000 homeless; and a repeat of the Mw 6.2 1855 Visp earthquake

with return period of 50 to 150 years would cost 2 to 5 billion CHF in direct economic losses alone. The signiﬁcant economic losses within Switzerland are attributed to the fact that buildings in Switzerland are not earthquake-resistant designed to a large extent.

The above recent earthquakes alert people to the importance of seismic resilience as a measure of a community’s ability to minimize loss of life, casualties and economic losses due to repairs as well as business interruption. From community resilience point of view, the built environment should have the ability to maintain an acceptable level of functionality and/or seismic performance during and after an earthquake and to rapidly return to full or acceptable levels of functionality within a speciﬁed period (Cimellaro et al. 2010; Burton et al. 2015; Hutt et al. 2016; McAllister 2016; Tirca et al. 2016). In this context, a framework for earthquake-induced loss assessment of buildings is essential. This framework will assist stakeholders, decision-makers, (re-)insurers and engineers to take decisions for immediate emergency-response operations and re-occupancy prioritize inspections and decide on investments for retroﬁtting of existing infrastructure in order to minimize the societal and economic impact in the aftermath of earthquakes. This framework

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can explicitly address regional impacts of earthquakes within a speciﬁc geographical area (i.e., city-scale approach) while retaining the ability to capture an adequate level of detail that enables estimates of direct losses attributable to earthquake-induced damage to an individual building and its contents (i.e., building-speciﬁc approach).

Given the sources of uncertainty related to the seismic hazard and the structural response, the next generation of performance-based earthquake engineering (PBEE) framework (Cornell and Krawinkler 2000; Porter 2003; Moehle and Deierlein 2004; Goulet et al. 2007) recently formalized guidelines that became publically available in FEMA P-58 (FEMA 2012) for earthquake-induced loss-assessment. Figure 1.3 conceptually illustrated the PBEE framework components. The PBEE framework involves four main steps. The ﬁrst one is hazard analysis, which entails the estimation of the frequency and severity of a possible future earthquake represented by the seismic hazard at the site of interest. The next step in the framework is to perform structural analysis, in which a suite of nonlinear response history analyses (NRHAs) of a nonlinear building model is gener-ally involved to estimate the engineering demand parameters (EDPs) conditioned on each level of intensity measure. The third step is the damage analysis, in which one quantiﬁes the extent of structural and non-structural building component damage in a probabilistic manner based on a library of fragility curves, given an EDP of interest based on structural analysis. The fourth step, loss analysis estimates the losses in terms of repair costs, injuries and fatalities, and downtime based on the results from the damage analysis.

The PBEE framework generally requires NRHAs to characterize the relationship between EDPs and the ground motion intensity in a probabilistic manner. A few studies [e.g., Erochko et al. (2011), FEMA (2012), Dyanati et al. (2015b), Ruiz-García and Chora (2015), etc] proposed simpliﬁed methods for estimating EDPs in steel frame buildings in an effort to reduce the com-putational cost of NRHAs. However, such methods require the explicit use of nonlinear building models. Therefore, detailed information of the building geometry and material properties is neces-sary in this case. Such models require an appreciable time investment for their further validation.

An efﬁcient decision-making framework is needed that will assist the reconnaissance efforts effectively to minimize the time delays due to computationally intensive NRHA. For this pur-pose, this thesis aims to develop a decision-making framework for rapid earthquake-induced loss assessment of steel frame buildings and facilitate effective recovery activities that minimize socio-economical impact in the aftermath of earthquakes.

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1.2 Scope and Research Objectives

The ultimate objective of this thesis is to develop an efficient and robust framework for rapid earthquake-induced loss assessment of steel frame buildings. To avoid time delays currently caused by detail engineering inspection, nonmodel-based damage indicators are developed based on con-cepts from structural health monitoring (SHM) that are able to implement a near real-time and automated damage diagnosis. At present, seismic instrumentation programs for new and existing buildings have been established in highly seismic regions around the world (Çelebi 2013; Hwang and Lignos 2017a) and therefore enable the SHM principles to be implemented in the framework of this thesis. Based on the nonmodel-based damage indicator, a simplified method is proposed in order to provide estimates of story-based EDPs of interest to the engineering profession. Such EDPs can facilitate loss assessment/control due to structural/non-structural damage in steel frame buildings via both building-specific and city-scale approaches. The specific objectives of this thesis are as follows:

(1) Introduce the best-suited global damage indicator estimated by nonmodel-based approach based on concepts of SHM, which does not require the use of detailed building models for structural and non-structural damage diagnosis.

(2) Propose an approximate method for providing story-based EDPs such as peak story drift ratios, peak absolute ﬂoor accelerations, and residual story drift ratios in instrumented steel frame buildings.

(3) Quantify the effect of numerical model choices on earthquake-induced economic losses of steel frame buildings with moment-resisting frames (MRFs) and concentrically braced frames (CBFs).

(4) Provide guidance on the selection of appropriate loss-metrics to assess the earthquake-induced economic losses in steel frame buildings, depending on the seismic performance of interest. (5) Perform city-scale simulations for loss assessment based on the data retrieved from

instru-mented steel frame buildings.

1.3 Organization of Dissertation

This thesis is based on a compilation of a number of research papers. These papers are co-authored; therefore, appropriate credit for the contributions of each author is given at the beginning of each chapter. The thesis consists of eight chapters that are organized as follows:

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Chapter 2 presents a comprehensive literature review of prior research on methods for earthquake-induced damage diagnosis in civil infrastructure as well as loss estimation methodologies. This chapter also summarizes the scope and limitations of these studies.

Chapter 3 presents an implementation of SHM concepts for structural damage diagnosis. The effectiveness of nonmodel-based damage-sensitive features computed based on various SHM ap-proaches is numerically and experimentally investigated using measured vibration data from three large-scale steel frame test beds complemented by nonlinear response history analyses on three-and eight-story steel frame models. The same chapter identiﬁes the limitations of existing ap-proaches widely used in SHM and proposes new best-suited damage-sensitive features.

Chapter 4 summarizes a detailed study that quantifies the probabilistic economic losses of a set of archetypes of typical office steel frame buildings with ductile steel MRFs designed in highly seismic regions. Emphasis is placed on the effect of analytical modeling choices of archetypes on earthquake-induced economic losses. This is achieved by utilizing a story-based building-specific loss estimation methodology that explicitly incorporates the effect of permanent deformation along the building height on the loss estimation in the aftermath of an earthquake. The study presented here attempts to provide guidance on the modeling assumptions of steel frame buildings with MRFs depending on the seismic performance of interest.

Chapter 5 presents a comprehensive study that quantiﬁes the collapse risk and the earthquake-induced economic losses of a steel frame-building portfolio with CBFs designed in highly seismic regions. The collapse risk of the buildings is quantiﬁed by considering the frequency and severity of possible future earthquakes represented by the seismic hazard at the site of interest. The same chapter evaluates the effect of interior gravity framing system and the selected steel brace fragility curve on the earthquake-induced economic losses of steel frame buildings with CBFs by utilizing the loss estimation methodology presented in Chapter 4.

Chapter 6 proposes a simplified method for estimating story-based EDPs such as peak story drift ratios, peak absolute floor accelerations and residual story drift ratios in steel frame buildings with ductile steel MRFs. The proposed method employs best-suited damage-sensitive features computed based on concepts of SHM and it does not require the use of detailed nonlinear building models for structural and non-structural damage diagnosis. Chapter 6 presents the concept of city-scale building simulation for the earthquake-induced loss assessment of steel frame buildings by using the simplified method proposed in same chapter and the loss estimation methodology il-lustrated in Chapters 4 and 5. Stakeholders and emergency responders can employ such approach to identify fairy quickly buildings that are potentially damaged following an earthquake event or scenario in an urban area. The proposed methodology utilizes data retrieved from instrumented steel frame buildings in urban California that experienced the 1994 Northridge earthquake.

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Gen-eralized earthquake-induced loss maps (i.e., economic losses and EDPs of interest to engineering profession) are developed with the use of geographical information system (GIS) for steel frame buildings around the Los Angeles area.

Chapter 7 summarizes the main results and contributions of this thesis. Finally, the main limitations of the present research are summarized in order to provide the basis for future research.

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Figure 1.1: Christchurchs central business district after the 2011 Christchurch earthquake [Image courtesy of John Kirk-Anderson (Stuart 2015)].

D E

Figure 1.2: Example of business interruption after the 2012 Emilia, Northern Italy earthquake: (a) shop inside the historic center; and (b) industrial building [adopted from Decanini et al. (2012)].

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CHAPTER 2

LITERATURE REVIEW

2.1 Introduction

This thesis is intended to develop a framework for rapid earthquake-induced loss assessment in steel frame buildings by combining concepts of performance-based earthquake engineering (PBEE) and structural health monitoring (SHM). This chapter summarizes previous research re-sults on a wide range of methods for diagnosing earthquake-induced damage in frame buildings as well as loss estimation methodologies. Limitations of such methodologies are also summarized.

2.2 Methods for Structural Damage Diagnosis

A variety of methods exist in the literature for structural damage diagnosis of engineered facili-ties that could be potentially used for rapid earthquake-induced damage assessment in steel frame buildings. These methods can be categorized as follows: (i) methods based on SHM principles; (ii) simpliﬁed methods for estimating seismic demands; (iii) damage assessment with utilization of fragility curves; (iv) use of equivalent continuous models; (v) city-scale damage distribution ap-proaches; and (vi) other methods such as use of rapid visual screening and social network analysis.

2.2.1 Structural health monitoring

With the advancements in sensing technology over the past decade (Spencer et al. 2004; Lynch and Loh 2006; Pakzad and Fenves 2009; Farrar and Worden 2012), there has been an increasing interest from the structural engineering community in implementation of the SHM principles. Structural health monitoring aims to develop automated monitoring systems in real-time or near real-time to identify the structural damage subjected to vibrations (e.g., wind and earthquakes) with minimum labor resources. Therefore, the SHM principles have been regarded as a useful tool to provide in-formation to building owners, occupants and structural engineers to support rapid safety evaluation