Reliability and safety of cable-supported bridges / edited by Naiwei Lu, Yang Liu, Mohammad Noori.

Format:

Book

Contributor:

Lu, Naiwei, Lu, editor.

Liu, Yang (Of Haerbin gong ye da xue), editor.

Noori, Mohammad, editor.

Series:

Resilience and Sustainability in Civil, Mechanical, Aerospace and Manufacturing Engineering Systems

Language:

English

Subjects (All):

Cable-stayed bridges--Reliability.

Cable-stayed bridges.

Physical Description:

1 online resource (255 pages)

Edition:

1st ed.

Place of Publication:

Boca Raton, Florida ; London ; New York : CRC Press, [2021]

Summary:

Reliability and Safety of Cable-Supported Bridges provides a comprehensive application and guidelines for system reliability techniques in cable-supported bridges.

Contents:

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

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

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

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

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

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

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

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

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

Index.

Notes:

Description based on print version record.

Description based on publisher supplied metadata and other sources.

ISBN:

1-000-38416-0

OCLC:

1250089543