Reliability and Safety of Cable-Supported Bridges

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
Acknowledgments
Notes on the Editors
List of Contributors
List of Abbreviations
Chapter 1: Introduction
	1.1 Safety of Cable-supported Bridges
	1.2 Uncertainties in Cable-supported Bridges
	1.3 System Reliability of Long-span Bridges
	1.4 Time-varying Reliability of Bridges during Construction
	1.5 Fatigue Reliability of Steel Bridges
	1.6 Dynamic Reliability of Bridges under Vehicle Loads
	1.7 Probabilistic Traffic Load Effects on Cable-supported Bridges
	1.8 Contents of this Book
	References
Chapter 2: Serviceability Reliability Assessment of Prestressed Concrete Cable-stayed Bridges Using Intelligent Neural Networks
	2.1 Introduction: Background
	2.2 Mathematical Models
	2.3 Proposed Computational Framework
	2.4 Validation Examples
		2.4.1 Numerical Example Analysis
		2.4.2 The Brotonne Cable-stayed Bridge
	2.5 Case Study
		2.5.1 Backgrounds of the Second Hejiang Yangtze River Bridge
		2.5.2 Random Variables
		2.5.3 Limit State Functions
		2.5.4 Reliability Analysis Based on Intelligent Neural Networks
		2.5.5 Parametric Sensitivity Analysis
	2.6 Conclusions
	References
Chapter 3: System Reliability Assessment of a Cable-stayed Bridge Using an Adaptive Support Vector Regression Method
	3.1 Introduction
	3.2 Support Vector Regression Methodology for Structural Reliability Estimation
		3.2.1 Approximating the Structural Responses based on an SVR Method
		3.2.2 Estimating Structural Reliability using the SVR-MCS Approach
	3.3 The Proposed ASVR Method for Structural System Reliability
		3.3.1 The Updating Idea
		3.3.2 The First Updating Procedure: Searching the MPFP
		3.3.3 The Second Updating Procedure: Searching Failure Sequences
		3.3.4 Correlation Coefficient Calculation
	3.4 Verification Examples
	3.5 Application Example: A Cable-stayed Bridge
		3.5.1 Project Profile and the Finite Element Model
		3.5.2 Random Parameters and Failure Modes
		3.5.3 Results and Discussion
	3.6 Conclusions
	References
Chapter 4: System Reliability Evaluation of In-service Cable-stayed Bridges Subjected to Cable Degradation
	4.1 Introduction
	4.2 Modeling Strength Reduction of Parallel Wire Cables
		4.2.1 Effects of Cable Length and Number of Wires
		4.2.2 Effect of Fatigue-corrosion
		4.2.3 Probabilistic Modeling of Cable Strength
	4.3 A Computational Framework for System Reliability Evaluation of Cable-stayed Bridges
		4.3.1 Component-level Failure Mode of a Cable-stayed Bridge
		4.3.2 System-level Failure Sequences and Subsystem Updating
		4.3.3 Structural System Reliability Evaluation via Machine Learning
	4.4 Case Study of a Short-span Cable-stayed Bridge
	4.5 Case Study of a Long-span Cable-stayed Bridge
		4.5.1 Prototype Bridge
		4.5.2 Deterministic Analysis
		4.5.3 System Reliability Evaluation
	4.6 Conclusions
	References
Chapter 5: Reliability Evaluation of a Cable-stayed Bridge Subjected to Cable Rupture During Construction
	5.1 Introduction
	5.2 Mechanical Behavior of a Cable-stayed Bridge Subjected to Cable Rupture During Construction
		5.2.1 Description of a Concrete Cable-stayed Bridge
		5.2.2 Critical Scenarios of Cable Rupture
		5.2.3 Finite Element Simulation of Each Scenario
	5.3 A Framework for System Reliability Evaluation of Cable-stayed Bridges Subjected to Cable Rupture
		5.3.1 System Properties of Cable-stayed Bridges
		5.3.2 An Effective Computational Framework for Structural System Reliability Evaluation
	5.4 System Reliability Evaluation of a Cable-stayed Bridge During Construction
		5.4.1 Random Variables and Sensitive Analysis
		5.4.2 Limit State Function
		5.4.3 System Reliability Evaluation
	5.5 Conclusions
	References
Chapter 6: Fatigue Reliability Evaluation of Orthotropic Steel Bridge Decks Based on Site-specific Weigh-in-motion Measurements
	6.1 Introduction
	6.2 Stochastic Truck Load Model Simulation Based on WIM Measurements
		6.2.1 WIM Measurements
		6.2.2 Stochastic Truck Load Simulation
	6.3 Limit State Function of Fatigue Damage Accumulation
		6.3.1 Fatigue Damage Accumulation Formulations
		6.3.2 Limit State Function
	6.4 Proposed Computational Framework
	6.5 Case Study
		6.5.1 Bridge Details
		6.5.2 Finite Element Simulation
		6.5.3 Probabilistic Modeling
		6.5.4 Fatigue Reliability Evaluation
	6.6 Conclusions
	References
Chapter 7: Probabilistic Fatigue Damage of Orthotropic Steel Deck Details based on Structural Health Monitoring Data
	7.1 Introduction
	7.2 Fatigue Reliability Assessment Integrating SHM Data using Copula
		7.2.1 Fatigue Reliability Functions based on SHM Data
		7.2.2 Reliability Index
		7.2.3 Theory of Copula
		7.2.4 Comparison and Selection of Copulas
		7.2.5 Fatigue Reliability Analysis Process using Copula
	7.3 Case Study of Nanxi Yangtze River Suspension Bridge
		7.3.1 Health Monitoring System of Yangtze River Suspension Bridge
		7.3.2 Strain Data-processing
		7.3.3 Variables Correlation Discussion
		7.3.4 Relevant Variables
			7.3.4.1 Joint Function Modeling Using Copula
			7.3.4.2 Dimension Gaussian Copula Function
		7.3.5 Fatigue Reliability Index
	7.4 Conclusions
	References
Chapter 8: Fatigue Crack Propagation of Rib-to-deck Double-sided Welded Joints of Orthotropic Steel Bridge Decks
	8.1 Introduction
	8.2 Details of Double-side Welded Joints
	8.3 Fatigue Crack Growth Simulation and Life Prediction Method
		8.3.1 M-Integral for SIF Determination
		8.3.2 Mixed mode SIF Range
		8.3.3 Kink Angle Model
		8.3.4 Crack Extension Type
		8.3.5 Fatigue Life Prediction
		8.3.6 Step-wise Procedure
		8.3.7 Numerical Examples and Verification
	8.4 Case Study
		8.4.1 Background of Prototype Bridge
		8.4.2 Finite Element Model
		8.4.3 Geometry and Location of Initial Flaws
		8.4.4 Fatigue Load
		8.4.5 Stress Analysis for No-crack Finite Element Model
		8.4.6 Static Crack SIF Analysis
	8.5 Crack Growth Analysis and Fatigue Life Predictions
		8.5.1 Crack Growth Behavior
		8.5.2 Variation of Equivalent SIF Range
		8.5.3 Fatigue Life Predictions
	8.6 Discussion
	8.7 Conclusions
	References
Chapter 9: Maximum Probabilistic Traffic Load Effects on Large Bridges Based on Long-term Traffic Monitoring Data
	9.1 Introduction
	9.2 Traffic Monitoring Data and Traffic Flow Simulation
		9.2.1 Traffic Data from WIM System
		9.2.2 Traffic Flow Simulation
		9.2.3 Critical Loading Scenarios
	9.3 Methodology for Extrapolating Maximum Traffic Load Effects
		9.3.1 Theoretical Basis
		9.3.2 Computational Framework
	9.4 Case Study
		9.4.1 Prototype Suspension Bridge
		9.4.2 Probabilistic Modeling of the Extreme Load Effects
		9.4.3 Parametric Study
	9.5 Conclusions
	References
Chapter 10: Dynamic Reliability of Cable-supported Bridges Under Moving Stochastic Traffic Loads
	10.1 Introduction
	10.2 Theoretical Basis of Rice’s Level-crossing Rate
	10.3 A Computational Framework for Extrapolation
	10.4 Numerical Simulation of Dynamic Traffic Load Effects on Cable-supported Bridges
		10.4.1 Stochastic Traffic Load Simulation based on WIM Measurements
		10.4.2 Dynamic Traffic Load Effect on Prototype Bridges
	10.5 Probabilistic Estimation using Rice’s Formula
		10.5.1 Maximum Deflection Extrapolation
		10.5.2 Probability of Exceedance of Threshold
	10.6 Conclusions
	References
Chapter 11: A Deep Belief Network-based Intelligent Approach for Structural Reliability Evaluation and Its Application to Cable-supported Bridges
	11.1 Introduction
	11.2 Mathematical Model For System Reliability of Cable-supported Bridges
		11.2.1 Nonlinear Limit State Functions
		11.2.2 Modeling of Cable Strength Degradation
		11.2.3 Modeling of System Failure
	11.3 A Framework for Reliability Evaluation based on Deep Belief Networks
		11.3.1 Theoretical Basis of Deep Belief Networks
		11.3.2 Proposed Computational Framework
	11.4 Case Study of a Suspension Bridge
		11.4.1 Background of the Prototype Suspension Bridge
		11.4.2 Traffic Load Modeling Using Weigh-in-motion Data
		11.4.3 Reliability Analysis Based on the DBNs Approach
		11.4.4 System Reliability Evaluation
	11.5 Conclusions
	References
Index