EARTHQUAKE DISASTER SIMULATION OF CIVIL INFRASTRUCTURES

Foreword of the Second Edition
Preface of the Second Edition
Preface of the First Edition
Contents
Abbreviations
1 Introduction
	1.1 Research Background
	1.2 Significance and Implication of Earthquake Disaster Simulation of Civil Infrastructures
	1.3 Research Framework and Outlines
	References
2 High-Fidelity Computational Models for Earthquake Disaster Simulation of Tall Buildings
	2.1 Introduction
	2.2 Fiber-Beam Element Model
		2.2.1 Fundamental Principles
		2.2.2 Uniaxial Stress-Strain Model of Concrete
		2.2.3 Uniaxial Stress-Strain Model of Steel Reinforcement
		2.2.4 Validation Through Reinforced Concrete Specimens
		2.2.5 Stress-Strain Model of Composite Components
		2.2.6 Steel Fiber-Beam Element Model Considering the Local Buckling Effect
	2.3 Multi-layer Shell Model
		2.3.1 Fundamental Principles
		2.3.2 High-Performance Flat Shell Element NLDKGQ
		2.3.3 High-Performance Triangular Shell Element NLDKGT
		2.3.4 Constitutive Models of Concrete and Steel
		2.3.5 Implementation of Multi-layer Shell Element in OpenSees
		2.3.6 Validation Through Reinforced Concrete Specimens
		2.3.7 Collapse Simulation of an RC Frame-Core Tube Tall Building
	2.4 Hysteretic Hinge Model
		2.4.1 Overview
		2.4.2 The Proposed Hysteretic Hinge Model
		2.4.3 Validation of the Proposed Hysteretic Hinge Model
	2.5 Multi-scale Modeling
		2.5.1 Overview
		2.5.2 Interface Modeling
	2.6 Element Deactivation and Collapse Simulation
		2.6.1 Element Deactivation for Component Failure Simulation
		2.6.2 Visualization of the Movement of Deactivated Elements Using Physics Engine
	2.7 GPU-Based High-Performance Matrix Solvers for OpenSees
		2.7.1 Fundamental Conception of General-Purpose Computing on GPU (GPGPU)
		2.7.2 High-Performance Solver for the Sparse System of Equations (SOE) in OpenSees
		2.7.3 Case Studies
	2.8 Physics Engine-Based High-Performance Visualization
		2.8.1 Overview
		2.8.2 Overall Visualization Framework
		2.8.3 Clustering-Based Key Frame Extractions
		2.8.4 Parallel Frame Interpolation
	2.9 Summary
	References
3 Earthquake Disaster Simulation of Typical Supertall Buildings
	3.1 Introduction
	3.2 Earthquake Disaster Simulation of the Shanghai Tower
		3.2.1 Overview of the Shanghai Tower
		3.2.2 Finite Element Model of the Shanghai Tower
		3.2.3 Earthquake-Induced Collapse Simulation
		3.2.4 Impact of Soil–Structure Interaction
	3.3 Earthquake Disaster Simulation and Design Optimization of the CITIC Tower
		3.3.1 Introduction of the CITIC Tower
		3.3.2 Different Lateral Force Resisting Systems of CITIC Tower and the Finite Element Models
		3.3.3 Earthquake-Induced Collapse Simulation of the Half-Braced Scheme
		3.3.4 Earthquake-Induced Collapse Simulation of the Fully-Braced Scheme
		3.3.5 Comparison Between the Two Design Schemes
		3.3.6 Optimal Design of Minimum Base Shear Force
		3.3.7 Optimal Design of Brace-Embedded Shear Wall
	3.4 Summary
	References
4 Comparison of Seismic Design and Resilience of Tall Buildings Based on Chinese and US Design Codes
	4.1 Introduction
		4.1.1 From Performance-Based Design to Resilience-Based Design
		4.1.2 The Rationale of Design Code Comparison
	4.2 Comparison of RC Buildings Based on the Chinese and US Design Codes
		4.2.1 Comparison of the Seismic Designs
		4.2.2 Comparison of the Structural Performance
		4.2.3 Comparison of the Seismic Resilience
		4.2.4 Concluding Remarks
	4.3 Comparison of Steel Buildings Based on the Chinese and US Design Codes
		4.3.1 Comparison of the Seismic Designs
		4.3.2 Comparison of the Structural Performance
		4.3.3 Comparison of the Seismic Resilience
		4.3.4 Concluding Remarks
	4.4 Summary
	References
5 Simplified Models for Earthquake Disaster Simulation of Supertall Buildings
	5.1 Introduction
	5.2 The Flexural-Shear Model
		5.2.1 Fundamental Concepts of the Flexural-Shear Model
		5.2.2 Flexural-Shear Models of Supertall Buildings
	5.3 Floor Acceleration Control of Supertall Buildings with Vibration Reduction Substructures
		5.3.1 Overview
		5.3.2 Concept of the VRS
		5.3.3 Analytical Model of 300 m Supertall Buildings and Ground Motion Records
		5.3.4 Floor Acceleration Reduction Effect of VRS
		5.3.5 Determination of the Optimal Frequency of the VRS
		5.3.6 Validation
		5.3.7 Concluding Remarks
	5.4 Ground Motion Intensity Measure (IM) for Supertall Buildings
		5.4.1 Research Background
		5.4.2 A Brief Review of the Existing IMs
		5.4.3 An Improved IM for Supertall Buildings
		5.4.4 Comparison of Different IMs
		5.4.5 Comparison of Different IMs Through IDA-Based Collapse Simulation
	5.5 The Fishbone Model
		5.5.1 Fundamental Concept of the Fishbone Model
		5.5.2 The Fishbone Model of the Shanghai Tower
		5.5.3 The Fishbone Models of the CITIC Tower
	5.6 Summary
	References
6 Seismic Resilient Outriggers and Multi-hazard Resilient Frames
	6.1 Introduction
	6.2 Seismic Resilient Outriggers
		6.2.1 Research Background
		6.2.2 BRB Outriggers
		6.2.3 Sacrificial-Energy Dissipation Outrigger
		6.2.4 Friction Damped Outrigger
	6.3 Multi-hazard Resistant Concrete Frames
		6.3.1 Research Background
		6.3.2 Experimental Program
		6.3.3 Experimental Results
		6.3.4 Numerical Simulation of MHRPC Specimens Based on OpenSees
		6.3.5 Analytical Model for MHRPC Frame
	6.4 Multi-hazard Resilient Composite Frames
		6.4.1 Research Background
		6.4.2 SAS Components
		6.4.3 Experimental Study of MHRSCCF
		6.4.4 Design Method for MHRSCCF-2
	6.5 Summary
	References
7 Building Models for City-Scale Nonlinear Time-History Analyses
	7.1 Introduction
		7.1.1 The Probability Matrix Method
		7.1.2 The Capacity Spectrum Method
		7.1.3 The Simulation Method Based on Nonlinear MDOF Models and Time-History Analyses
		7.1.4 Organization of This Chapter
	7.2 Nonlinear MDOF Shear Model of Multi-story Buildings
		7.2.1 Overview
		7.2.2 Nonlinear MDOF Shear Model
		7.2.3 Parameter Determination for Multi-story Buildings in China
		7.2.4 Parameter Determination of Backbone Curve Based on the HAZUS Data
		7.2.5 Calibration of the Hysteretic Parameter
		7.2.6 Validation of the Proposed Parameter Determination Method
	7.3 Nonlinear MDOF Flexural-Shear Model of Tall Buildings
		7.3.1 Overview
		7.3.2 Nonlinear MDOF Flexural-Shear Model
		7.3.3 Parameter Calibration Based on Building Attribute Data
		7.3.4 Validation and Application of the Proposed NMFS Model to Individual Tall Buildings
		7.3.5 Application of the Proposed NMFS Model for Seismic Simulation of Regional Tall Buildings
	7.4 Parametric Sensitivity Study on City-Scale Nonlinear THA
		7.4.1 Research Background
		7.4.2 The FOSM and Monte Carlo Methods
		7.4.3 Case Study
		7.4.4 Concluding Remarks
	7.5 City-Scale Nonlinear Time-History Analysis Considering Site-City Interaction Effects
		7.5.1 Research Background
		7.5.2 City-Scale Nonlinear THA of Buildings Considering SCI Effects
		7.5.3 Validation Using Shaking Table Test
		7.5.4 Case Study of SCI Effects in a 3D Basin
		7.5.5 Case Study of Tsinghua University Campus
		7.5.6 Concluding Remarks
	7.6 Multi-LOD Seismic-Damage Simulation of Urban Buildings
		7.6.1 Research Background
		7.6.2 Multi-source Data and Multi-LOD Seismic-Damage Simulation
		7.6.3 Implementation of the Multi-LOD Seismic-Damage Simulation
	7.7 Summary
	References
8 Regional Seismic Loss Estimation of Buildings
	8.1 Introduction
	8.2 The Building-Level Loss Estimation Method
		8.2.1 Overview
		8.2.2 Damage Assessment of Multi-story Buildings
		8.2.3 Damage Assessment of Reinforced Concrete (RC) Tall Buildings
	8.3 Regional Seismic Loss Prediction Based on FEMA P-58 and Field Investigation Data
		8.3.1 Overview
		8.3.2 Prediction Methodology
		8.3.3 Case Study: Regional Seismic Loss Prediction of the Tsinghua University Campus
		8.3.4 Results and Discussion on Seismic Loss Predictions
		8.3.5 Findings of the Seismic Loss Prediction Study
	8.4 Seismic Loss Predictions Based on BIM and FEMA P-58
		8.4.1 Overview
		8.4.2 Integrated BIM and FEMA P-58 Framework
		8.4.3 Technical Implementation
		8.4.4 Case Study
		8.4.5 Concluding Remarks
	8.5 Seismic Loss Assessment Using Various-LOD BIM Data
		8.5.1 Overview
		8.5.2 Limitations of the FEMA P-58 Method
		8.5.3 Vulnerability Function of Building Components with Various LODs
		8.5.4 Modeling Rules and the Information Extraction for BIM
		8.5.5 Case Study
		8.5.6 Concluding Remarks
	8.6 Seimsic Loss Prediction Combiningg GIS and FEMA P-58
		8.6.1 Overview
		8.6.2 Estimate the Type of Components
		8.6.3 Estimate the Quantity of Components
	8.7 Summary
	References
9 Visualization and High-Performance Computing for City-Scale Nonlinear Time-History Analyses
	9.1 Introduction
	9.2 2.5D Visualization Model
	9.3 3D Visualization Model
		9.3.1 Overview
		9.3.2 The Proposed 3D Simulation Methodology
		9.3.3 3D-GIS Data Generation
		9.3.4 High-Fidelity Visualization Using 3D Urban Polygon Model
		9.3.5 Implementation
		9.3.6 Case Study
	9.4 Photo-Realistic Visualization Based on Oblique Aerial Photography
		9.4.1 Overview
		9.4.2 Visualization Framework
		9.4.3 Detailed Technical Implementations for Visualization Framework
		9.4.4 Case Study
		9.4.5 Concluding Remarks
	9.5 Coarse-Grained CPU/GPU Collaborative Parallel Computing
		9.5.1 Overview
		9.5.2 Computing Program Architecture
		9.5.3 Performance Benchmarking
	9.6 Simulation Using Distributed Computing and Multi-fidelity Models
		9.6.1 Various Models with Different Levels of Fidelities
		9.6.2 The Overall Computational Framework
		9.6.3 Software Implementation
		9.6.4 Case Study
	9.7 Cloud Computing for Post-earthquake Emergency Response
	9.8 Physics Engine-Based Collapse Simulation of Urban Buildings
		9.8.1 Overview
		9.8.2 Physics Engine-Based Collapse Simulation
		9.8.3 Integrated Visualization System
		9.8.4 Case Study
	9.9 Summary
	References
10 Fire Following Earthquake and Falling Debris Hazards
	10.1 Introduction
	10.2 Fire Following Earthquake Simulation Considering Overall Seismic Damage of Sprinkler Systems Based on BIM and FEMA P-58
		10.2.1 Overview
		10.2.2 Simulation Methods
		10.2.3 Case Study: RC Frame Dormitory Building
		10.2.4 Concluding Remarks
	10.3 Physics-Based Simulation and High-Fidelity Visualization of Regional Fire Following Earthquake Considering Building Seismic Damage
		10.3.1 Overview
		10.3.2 Proposed Framework of FFE Simulation and Visualization
		10.3.3 Methodology
		10.3.4 Case Study: Downtown Taiyuan City
		10.3.5 Concluding Remarks
	10.4 Earthquake-Induced Falling Debris Hazards
		10.4.1 Overview
		10.4.2 The Proposed Simulation Framework
		10.4.3 Methodology
		10.4.4 Case Study
		10.4.5 Concluding Remarks
	10.5 Site Selection for Emergence Shelters Considering Falling Debris Hazards
		10.5.1 Overview
		10.5.2 The Proposed Framework for Site Selection of Emergency Shelters
		10.5.3 Methodology
		10.5.4 Case Study: Residential Community Area
		10.5.5 Concluding Remarks
	10.6 Summary
	References
11 Post-earthquake Emergency Response and Recovery Through City-Scale Nonlinear Time-History Analysis
	11.1 Introduction
	11.2 Real-Time Earthquake Damage Assessment Through City-Scale Time-History Analysis
		11.2.1 Research Background
		11.2.2 Real-Time City-Scale Nonlinear Time-History Analysis
		11.2.3 Applications in Earthquake Emergency Response
		11.2.4 Concluding Remarks
	11.3 Regional Seismic Damage Prediction of Buildings Under a Mainshock–Aftershock Sequence
		11.3.1 Overview
		11.3.2 Prediction Methodology
		11.3.3 The MS–AS Sequence Generation Method
		11.3.4 Case Study: Seismic Damage Prediction of Buildings at the Longtoushan Town Damaged in the Ludian Earthquake
		11.3.5 Concluding Remarks
	11.4 Improving the Accuracy of Near-Real-Time Seismic Loss Estimation Using Post-earthquake Remote Sensing Images
		11.4.1 Overview
		11.4.2 Framework of Near-Real-Time Seismic Loss Estimation
		11.4.3 Evaluation of the Similarity Measures of Collapse Distribution
		11.4.4 Case Study: Virtual Earthquakes Occurring on Tsinghua University Campus
		11.4.5 Validation Using 2014 Ludian Earthquake
		11.4.6 Concluding Remarks
	11.5 Post-earthquake Repair Scheduling of City-Scale Buildings with Labor Constraints
		11.5.1 Overview
		11.5.2 Methodology Framework
		11.5.3 Calculation of Residual Functionality
		11.5.4 Recovery Curve and Labor Demand Curve
		11.5.5 Repair Scheduling and Simulation
		11.5.6 Case Study
		11.5.7 Concluding Remarks
	11.6 Summary
	References
12 Earthquake Disaster Simulation of Typical Urban Areas
	12.1 Introduction
	12.2 Earthquake Disaster Simulation of Ludian Earthquake
		12.2.1 Seismic Damage to Buildings in Longtoushan Town
		12.2.2 Comparison with Field Investigation Data
		12.2.3 Comparison with Damage Probability Matrix Method
	12.3 Earthquake Disaster Simulation of Beijing CBD
		12.3.1 Buildings of Beijing CBD
		12.3.2 Earthquake Data of Beijing CBD
		12.3.3 LOD 0 Simulation
		12.3.4 LOD 1 Simulation
		12.3.5 LOD 2 Simulation
		12.3.6 LOD 3 Simulation
	12.4 Seismic Damage Prediction and Visualization of the New Beichuan City
		12.4.1 Research Background
		12.4.2 Building Inventory Data of the New Beichuan City
		12.4.3 Ground Motion Simulation for the New Beichuan City
		12.4.4 Seismic Damage Simulation Considering Site-City Interaction Effects
		12.4.5 High-Fidelity Visualization of Seismic Damage
	12.5 Earthquake Disaster Simulation of 1.8 Million Buildings in the San Francisco Bay Area
		12.5.1 Research Background
		12.5.2 SimCenter Scientific Workflow Application
		12.5.3 Seismic Damage Simulation
		12.5.4 Fire Following Earthquake Simulation for Downtown San Francisco
	12.6 Earthquake Disaster Simulation of Xi’an, Taiyuan and Tangshan Cities in China
		12.6.1 Earthquake Disaster Simulation of Baqiao District in Xi’an City
		12.6.2 Earthquake Disaster Simulation for Taiyuan and Tangshan Cities
	12.7 Summary
	References
13 Conclusions
	13.1 Major Achievements and Contributions
	13.2 A Future Perspective