1st Edition
Risk and Reliability in Geotechnical Engineering
Establishes Geotechnical Reliability as Fundamentally Distinct from Structural Reliability
Reliability-based design is relatively well established in structural design. Its use is less mature in geotechnical design, but there is a steady progression towards reliability-based design as seen in the inclusion of a new Annex D on "Reliability of Geotechnical Structures" in the third edition of ISO 2394. Reliability-based design can be viewed as a simplified form of risk-based design where different consequences of failure are implicitly covered by the adoption of different target reliability indices. Explicit risk management methodologies are required for large geotechnical systems where soil and loading conditions are too varied to be conveniently slotted into a few reliability classes (typically three) and an associated simple discrete tier of target reliability indices.
Provides Realistic Practical Guidance
Risk and Reliability in Geotechnical Engineering
makes these reliability and risk methodologies more accessible to practitioners and researchers by presentingWith contributions from a broad international group of authors, this text:
- Presents probabilistic models suited for soil parameters
- Provides easy-to-use Excel-based methods for reliability analysis
- Connects reliability analysis to design codes (including LRFD and Eurocode 7)
- Maximizes value of information using Bayesian updating
- Contains efficient reliability analysis methods
Accessible To a Wide Audience
Risk and Reliability in Geotechnical Engineering presents all the "need-to-know" information for a non-specialist to calculate and interpret the reliability index and risk of geotechnical structures in a realistic and robust way. It suits engineers, researchers, and students who are interested in the practical outcomes of reliability and risk analyses without going into the intricacies of the underlying mathematical theories.
Part I
Properties
Constructing multivariate distributions for soil parameters
; Jianye Ching and Kok-Kwang PhoonIntroduction
Normal random variable
Bivariate normal vector
Multivariate normal vector
Non-normal random variable
Multivariate non-normal random vector
Real example
Future challenges
List of symbols
References
Modeling and simulation of bivariate distribution of shear strength parameters using copulas;
Dian-Qing Li and Xiao-Song TangIntroduction
Copula theory
Modeling bivariate distribution of shear strength parameters
Simulating bivariate distribution of shear strength parameters
Impact of copula selection on retaining wall reliability
Summary and conclusions
Acknowledgments
Appendix 2.1: MATLAB® codes
List of symbols
References
Part II
Methods
Evaluating reliability in geotechnical engineering;
J. Michael Duncan and Matthew D. SleepPurpose of reliability analysis
Probability of failure and risk
Language of statistics and probability
Probability of failure and factor of safety
Methods of estimating standard deviations
Computing probability of failure
Monte Carlo analysis using @Risk™
Hasofer Lind method
Taylor Series method with assumed normal distribution of the factor of safety
Taylor Series method with a lognormal distribution of the factor of safety
PEM with a normal distribution for the factor of safety
PEM with a lognormal distribution for the factor of safety
Comments on the methods
Summary
References
Maximum likelihood principle and its application in soil liquefaction assessment;
Charng Hsein Juang, Sara Khoshnevisan, and Jie ZhangIntroduction
Principle of maximum likelihood
Liquefaction probability based on generalized linear regression
Converting a deterministic liquefaction model into a probabilistic model
Estimation of liquefaction-induced settlement
Summary and Conclusions
Acknowledgments
Appendix 4.1: Model of Robertson and Wride (1998) and Robertson (2009)
Appendix 4.2: Notation
References
Bayesian analysis for learning and updating geotechnical parameters and models with measurements;
Daniel Straub and Iason PapaioannouIntroduction
Bayesian analysis
Geotechnical reliability based on measurements: Step-by-step procedure for Bayesian analysis
Advanced algorithms for efficient and effective Bayesian updating of geotechnical models
Application: Foundation of transmission towers under tensile loading
Application: Finite-element-based updating of soil parameters and reliability
Concluding remarks
Acknowledgment
References
Polynomial chaos expansions and stochastic finite-element methods;
Bruno SudretIntroduction
Uncertainty propagation framework
Polynomial chaos expansions
Postprocessing for engineering applications
Sensitivity analysis
Application examples
Conclusions
Acknowledgments
Appendix 6.1: List of symbols
Appendix 6.2: Hermite polynomials
References
Practical reliability analysis and design by Monte Carlo Simulation in spreadsheet;
Yu Wang and Zijun CaoIntroduction
Subset Simulation
Expanded RBD with Subset Simulation
Probabilistic failure analysis using Subset Simulation
Spreadsheet implementation of MCS-based reliability analysis and design
Illustrative example I: Drilled shaft design
Illustrative example II: James Bay Dike design scenario
Summary and concluding remarks
Acknowledgment
List of symbols
References
Part III
Design
LRFD calibration of simple limit state functions in geotechnical soil-structure design;
Richard J. BathurstIntroduction
Preliminaries
Bias value distributions
Calculation of β, ϒQ, and φ
Example
Additional considerations
Conclusions
References
Reliability-based design: Practical procedures, geotechnical examples, and insights;
Bak-Kong LowIntroduction
Example of reliability-based shallow foundation design
SORM analysis on the foundation of FORM results for a rock slope
Probabilistic analyses of a slope failure in San Francisco Bay mud
Reliability analysis of a Norwegian slope accounting for spatial autocorrelation
System FORM reliability analysis of a soil slope with two equally likely failure modes
Multicriteria RBD of a laterally loaded pile in spatially autocorrelated clay
FORM design of an anchored sheet pile wall
Reliability analysis of roof wedges and rockbolt forces in tunnels
Probabilistic settlement analysis of a Hong Kong trial embankment on soft clay
Coupling of stand-alone deterministic program and spreadsheetautomated reliability procedures via response surface or similar methods
Summary and conclusions
References
Managing risk and achieving reliable geotechnical designs using Eurocode 7;
Trevor L.L. OrrIntroduction
Geotechnical complexity and risk
Reliability requirements in designs to Eurocode 7
Verification of designs to Eurocode 7
Reliability levels
Conclusions
Acknowledgments
References
Part IV
Risk and decision
Practical risk assessment for embankments, dams, and slopes;
Luis Altarejos-García, Francisco Silva-Tulla, Ignacio Escuder-Bueno, and Adrián Morales-TorresIntroduction
Estimation of conditional probability as a function of safety factor
Role of fragility curves to evaluate the uncertainty in probability estimates
Mathematical roots and numerical estimation of fragility curves
From fragility curves to annualized probability of failure commonly used in risk analysis
Summary of main points
Acknowledgments
List of main symbols and acronyms
References
Evolution of geotechnical risk analysis in North American practice;
Gregory B. Baecher and John T. ChristianIntroduction
Beginnings
Geotechnical reliability (1971–1996)
Mining engineering (1969–1980)
Offshore reliability (1974–1990)
Environmental remediation (1980–1995)
Dam safety (1986–Ongoing)
Systems risk assessment (2005–Ongoing)
Emerging approaches: System simulation, stress testing, and scenario appraisals
Ten unresolved questions
Concluding thoughts
Acknowledgments
References
Assessing the value of information to design site investigation and construction quality assurance programs;
Robert B. Gilbert and Mahdi HabibiIntroduction
Value of information framework
Insights from Bayes’ theorem
Implementation of value of information assessment
Case-history applications
Summary
Acknowledgments
References
Verification of geotechnical reliability using load tests and integrity tests;
Limin ZhangIntroduction
Within-site variability of pile capacity
Updating pile capacity with proof load tests
Updating pile capacity with integrity tests
Reliability of piles verified by proof load tests
Reliability of piles verified by integrity tests
Summary
Acknowledgment
List of symbols
References
Part V
Spatial variability
Application of the subset simulation approach to spatially varying soils;
Ashraf Ahmed and Abdul-Hamid SoubraIntroduction
Karhunen–Loève expansion methodology for the discretization of a random field
Brief overview of the subset simulation approach
Method of computation of the failure probability by the SS approach in the case of a spatially varying soil property
Example applications
Conclusion
Appendix 15.1: Modified M–H algorithm
List of symbols
References
Index
Biography
Kok-Kwang Phoon is a distinguished professor and head of the Department of Civil and Environmental Engineering, National University of Singapore, and past president of the Geotechnical Society of Singapore. His main research interests include statistical characterization of geotechnical parameters and reliability-based design in geotechnical engineering. He is the recipient of numerous research awards, including the ASCE Norman Medal in 2005 and the NUS Outstanding Researcher Award in 2010. He is the founding editor of Georisk and chair of TC304 (Engineering Practice of Risk Assessment and Management) in the International Society for Soil Mechanics and Geotechnical Engineering.
Jianye Ching
is a professor in the Department of Civil Engineering, National Taiwan University. His main research interests include geotechnical reliability analysis and reliability-based design, basic uncertainties in soil properties, random fields and spatial variability, and geotechnical design codes. He is the secretary of TC304 (risk) in the International Society for Soil Mechanics and Geotechnical Engineering. He is the recipient of the Outstanding Research Award and the Wu-Da-Yu Memorial Award from the National Science Council of Taiwan, Republic of China."Risk and Reliability in Geotechnical Engineering ...was, originally, to be an update of the 2008 book Reliability-based Design in Geotechnical Engineering – Computations and Applications (edited by K. K. Phoon). The update turns out to be a completely new book, and is a ‘must-read’, not only for those interested in risk and reliability in geotechnical engineering, but also for the geotechnical practitioner."
—Suzanne Lacasse in Proceedings of the Institution of Civil Engineers: Geotechnical Engineering"This is a welcome continuation of the very successful volume, Reliability-Based Design in Geotechnical Engineering… Practitioners will find very useful information that range from simple to advanced methods, and from site characterization to design and decision. The book will certainly encourage the use of reliability in practice."
—Georisk, 2015"This is an excellent book, written by acknowledged experts in the field for practicing engineers interested in geotechnical reliability analysis. The presentation is very clear and the subject matter delivered at just the right level – not too mathematical, yet still rigorous in approach. Practical matters, such as designing site investigations and selecting parameters for design, are covered well. Highly recommended."
—Dr. Andrew Bond, Geocentrix Ltd."The main strength of the materials I have reviewed is that they address the needs and questions of users of many different backgrounds, from practicing engineers who are curious about the added value of doing risk and reliability analyses, but are intimidated by the terminology and mathematics, to professional risk analysts who are more concerned about safety philosophy and application of more advanced analysis methods in assessing the value of information."
Farrokh Nadim, Technical Director, Norwegian Geotechnical Institute