Construction Reliability

Julien Baroth is a professor at the?IUT Laboratoire of Grenoble University in?France. Denys Breysse is a professor?in the Department of Civil and Environmental Engineering (GCE) at Bordeaux 1 University's Institute of Mechanics and Engineering (I2M) in France. D. Franck Schoefs is a professor at the Institute for Research in Civil and Mechanical Engineering (GeM)?of Nantes University in France.

• Preface xiiiJulien BAROTH, Franck SCHOEFS and Denys BREYSSEIntroduction xviiJulien BAROTH, Alaa CHATEAUNEUF and Franck SCHOEFSPART 1. QUALITATIVE METHODS FOR EVALUATING THE RELIABILITY OF CIVIL ENGINEERING STRUCTURES 1Introduction to Part 1 3Chapter 1. Methods for System Analysis and Failure Analysis 5Daniel BOISSIER, Laurent PEYRAS and Aurélie TALON1.1. Introduction 51.2. Structural analysis 71.3. Functional analysis 101.4. Failure Modes and Effects Analysis (FMEA) 141.5. Bibliography 19Chapter 2. Methods for Modeling Failure Scenarios 21Daniel BOISSIER, Laurent PEYRAS and Aurélie TALON2.1. Introduction 212.2. Event tree method 222.3. Fault tree method 242.4. Bow-tie method 262.5. Criticality evaluation methods 292.6. Bibliography 34Chapter 3. Application to a Hydraulic Civil Engineering Project 37Daniel BOISSIER, Laurent PEYRAS and Aurélie TALON3.1. Context and approach for an operational reliability study 373.2. Functional analysis and failure mode analysis 393.3. Construction of failure scenarios 423.4. Scenario criticality analysis 443.5. Application summary 503.6. Bibliography 51PART 2. HETEROGENEITY AND VARIABILITY OF MATERIALS: CONSEQUENCES FOR SAFETY AND RELIABILITY 53Introduction to Part 2 55Chapter 4. Uncertainties in Geotechnical Data 57Denys BREYSSE, Julien BAROTH, Gilles CELEUX, Aurélie TALON and Daniel BOISSIER4.1. Various sources of uncertainty in geotechnical engineering 574.2. Erroneous, censored and sparse data 624.3. Statistical representation of data 644.4. Data modeling 664.5. Conclusion 744.6. Bibliography 74Chapter 5. Some Estimates on the Variability of Material Properties 77Denys BREYSSE and Antoine MARACHE5.1. Introduction 775.2. Mean value estimation 775.3. Estimation of characteristic values 825.4. Principles of a geostatistical study 865.5. Bibliography 96Chapter 6. Reliability of a Shallow Foundation Footing 97Denys BREYSSE6.1. Introduction 976.2. Bearing capacity models for strip foundations – modeling errors 986.3. Effects of soil variability on variability in bearing capacity and safety of the foundation 1016.4. Taking account of the structure of the spatial correlation and its influence on the safety of the foundation 1096.5. Conclusions 1156.6. Bibliography 117PART 3. METAMODELS FOR STRUCTURAL RELIABILITY 119Introduction to Part 3 121Chapter 7. Physical and Polynomial Response Surfaces 123Frédéric DUPRAT, Franck SCHOEFS and Bruno SUDRET7.1. Introduction 1237.2. Background to the response surface method 1247.3. Concept of a response surface 1257.4. Usual reliability methods 1317.5. Polynomial response surfaces 1337.6. Conclusion 1437.7. Bibliography 143Chapter 8. Response Surfaces based on Polynomial Chaos Expansions 147Bruno SUDRET, Géraud BLATMAN and Marc BERVEILLER8.1. Introduction 1478.2. Building of a polynomial chaos basis 1498.3. Computation of the expansion coefficients 1518.4. Applications in structural reliability 1588.5. Conclusion 1648.6. Bibliography 165PART 4. METHODS FOR STRUCTURAL RELIABILITY OVER TIME 169Introduction to Part 4 171Chapter 9. Data Aggregation and Unification 173Daniel BOISSIER and Aurélie TALON9.1. Introduction 1739.2. Methods of data aggregation and unification 1739.3. Evaluation of evacuation time for an apartment in case of fire 1819.4. Conclusion 1859.5. Bibliography 185Chapter 10. Time-Variant Reliability Problems 187Bruno SUDRET10.1. Introduction 18710.2. Random processes 18810.3. Time-variant reliability problems 19210.4. PHI2 method 19710.5. Industrial application: truss structure under time-varying loads 20210.6. Conclusion 20410.7. Bibliography 205Chapter 11. Bayesian Inference and Markov Chain Monte Carlo Methods 207Gilles CELEUX11.1. Introduction 20711.2. Bayesian Inference 20811.3. MCMC methods for weakly informative data 21011.4. Estimating a competing risk model from censored and incomplete data 21911.5. Conclusion 22511.6. Bibliography 225Chapter 12. Bayesian Updating Techniques in Structural Reliability 227Bruno SUDRET12.1. Introduction 22712.2. Problem statement: link between measurements and model prediction 22812.3. Computing and updating the failure probability 22912.4. Updating a confidence interval on response quantities 23312.5. Bayesian updating of the model basic variables 23512.6. Updating the prediction of creep strains in containment vessels of nuclear power plants 23812.7. Conclusion 24512.8. Acknowledgments 24612.9. Bibliography 246PART 5. RELIABILITY-BASED MAINTENANCE OPTIMIZATION 249Introduction to Part 5 251Chapter 13. Maintenance Policies 253Alaa CHATEAUNEUF, Franck SCHOEFS and Bruno CAPRA13.1. Maintenance 25313.2. Types of maintenance 25713.3. Maintenance models 26213.4. Conclusion 26913.5. Bibliography 269Chapter 14. Maintenance Cost Models 271Alaa CHATEAUNEUF and Franck SCHOEFS14.1. Preventive maintenance 27114.2. Maintenance based on time 27314.3. Maintenance based on age 27514.4. Inspection models 27614.5. Structures with large lifetimes 28314.6. Criteria for choosing a maintenance policy 28414.7. Example of a corroded steel pipeline 28514.8. Conclusion 29014.9. Bibliography 290Chapter 15. Practical Aspects: Industrial Implementation and Limitations in a Multi-criteria Context 293Franck SCHOEFS and Bruno CAPRA15.1. Introduction 29315.2. Motorway concession with high performance requirements 29615.3. Ageing of civil engineering structures: using field data to update predictions 30315.4. Conclusion 30715.5. Bibliography 308Conclusion 311Julien BAROTH, Franck SCHOEFS and Denys BREYSSEList of Symbols 315List of Authors 323Index 325