The latest 4th edition of the international standard on the principles of reliability for load bearing structures (ISO2394: 2015) includes a new Annex D dedicated to the reliability of geotechnical structures. The emphasis in Annex D is to identify and characterize critical elements of the geotechnical reliability-based design process. This book contains a wealth of data and information to assist geotechnical engineers with the implementation of semi-probabilistic or full probabilistic design approaches within the context of established geotechnical knowledge, principles, and experience. The introduction to the book presents an overview on how reliability can play a complementary role within prevailing norms in geotechnical practice to address situations where some measured data and/or past experience exist for limited site-specifi c data to be supplemented by both objective regional data and subjective judgment derived from comparable sites elsewhere. The principles of reliability as presented in ISO2394: 2015 provides the common basis for harmonization of structural and geotechnical design. The balance of the chapters describes the uncertainty representation of geotechnical design parameters, the statistical characterization of multivariate geotechnical data and model factors, semi-probabilistic and direct probability-based design methods in accordance to the outline of Annex D. This book elaborates and reinforces the goal of Annex D to advance geotechnical reliability-based design with geotechnical needs at the forefront while complying with the general principles of reliability given by ISO2394: 2015. It serves as a supplementary reference to Annex D and it is a must-read for designing geotechnical structures in compliance with ISO2394: 2015.
Reliability as a basis for geotechnical design Kok-Kwang Phoon 1.1 Introduction 1.2 Evolution of structural and geotechnical design 1.3 Role of engineering judgment 1.4 Reliability versus geotechnical requirements of a safety format 1.5 Some reliability applications 1.5.1 Multivariate soil databases 1.5.2 Geotechnical information: Is it an "investment''or a "cost''? 1.5.3 Model uncertainties 1.5.4 Scarcity of geotechnical data 1.5.5 Probability distributions that accommodate a "worst credible'' value at a prescribed quantile 1.5.6 Spatial variability 1.5.7 Design point from the first-order reliability method (FORM) and partial factors 1.5.8 System reliability 1.6 Concluding thoughts 2 General principles on reliability according to ISO2394 Johan V. Retief, Mahongo Dithinde, and Kok-Kwang Phoon 2.1 Introduction: Background to the development of ISO2394:2015 2.1.1 Stages of development of ISO2394 2.1.2 Status and use of ISO2394 2.1.3 Objectives and fundamental principles 2.2 Overview of the standard ISO2394:2015 2.3 Conceptual basis and fundamental requirements 2.4 Key reliability concepts 2.5 Concluding summary of ISO2394:2015 3 Uncertainty representation of geotechnical design parameters Kok-Kwang Phoon, Widjojo A. Prakoso, Yu Wang, and Jianye Ching 3.1 Introduction 3.2 Sources of uncertainties 3.3 Natural variability 3.4 Measurement error 3.5 Transformation uncertainty 3.6 Scale of fluctuation 3.7 Intact rock and rock mass 3.7.1 Natural variability of intact rock 3.7.2 Intact rock measurement error 3.7.3 Intact rock scale of fluctuation 3.7.4 Rock mass natural variability 3.7.5 Rock mass transformation uncertainty 3.8 Statistical uncertainty for site-specific natural variability 3.8.1 Statistical uncertainty in site-specific trend 3.8.2 Statistical uncertainty of site-specific COV and SOF 3.9 Bayesian quantification of site-specific natural variability 3.10 Selection of site-specific transformation model 3.11 Conclusions and future work 4 Statistical characterization of multivariate geotechnical data Jianye Ching, Dian-Qing Li, and Kok-Kwang Phoon 4.1 Introduction 4.2 Correlation 4.3 Multivariate normal probability distribution function 4.4 Multivariate normal distributions constructed with genuine multivariate data 4.4.1 CLAY/5/345 4.4.2 CLAY/6/535 4.5 Multivariate normal distributions constructed with bivariate data 4.5.1 CLAY/7/6310 4.5.2 CLAY/10/7490 4.6 Multivariate normal distributions constructed with incomplete bivariate data 4.6.1 CLAY/4/BN 4.6.2 SAND/4/BN 4.7 Multivariate distributions constructed with the copula theory 4.7.1 Copula theory 4.7.2 Elliptical copulas (Gaussian and t copulas) 4.7.3 Kendall rank correlation 4.7.4 Estimating C using Pearson and Kendall correlations 4.7.5 Comparison between the Gaussian and t copulas 4.8 Conclusions 5 Statistical characterization of model uncertainty Mahongo Dithinde, Kok-Kwang Phoon, Jianye Ching, Limin Zhang, and Johan V. Retief 5.1 Introduction 5.2 Exploratory data analysis 5.3 Detection of data outliers 5.3.1 Sample z-score method 5.3.2 Box plot method 5.3.3 Scatter plot method 5.4 Probabilistic model for M 5.5 Verification of randomness of the model factor 5.5.1 Removal of statistical dependencies 22.214.171.124 Generalised model factor approach 126.96.36.199 Verification of removal of systematic dependency 5.5.2 Model factor as a function of input parameters 5.6 Available model factor statistics 5.6.1 Laterally loaded rigid bored piles (ultimate limit state) 5.6.2 Axially loaded piles (ultimate limit state) 5.6.3 Shallow foundations (ultimate limit state) 5.6.4 Axially loaded pile foundations (serviceability limit state) 5.6.5 Limiting tolerable displacement (serviceability limit state) 5.6.6 Factor of safety of a slope calculated by limit equilibrium method 5.6.7 Base heave for excavation in clays 5.7 Conclusions 6 Semi-probabilistic reliability-based design Kok-Kwang Phoon and Jianye Ching 6.1 Introduction 6.2 Survey of calibration methods 6.2.1 Basic Load Resistance Factor Design (LRFD) 6.2.2 Extended LRFD and Multiple Resistance and Load Factor Design (MRFD) 6.2.3 Robust LRFD (R-LRFD) 6.2.4 LRFD for total settlement 6.2.5 LRFD for differential settlement 6.2.6 First-order Reliability Method (FORM) 6.2.7 Baseline technique 6.2.8 Degree of understanding 6.3 Issue of variable coefficient of variation 6.3.1 Partial factors for the calibration case 6.3.2 Actual reliability index for the validation case 6.4 Issue of variable soil profiles 6.5 Quantile Value Method (QVM) 6.5.1 Robustness of QVM against variable COV 6.5.2 Pad foundation supported on boulder clay 6.6 Effective random dimension 6.6.1 Gravity retaining wall 6.7 Conclusions 7 Direct probability-based design methods Yu Wang, Timo Schweckendiek, Wenping Gong, Tengyuan Zhao, and Kok-Kwang Phoon 7.1 Introduction 7.2 Situations of direct probability-based design methods being necessary 7.3 Expanded reliability-based design (expanded RBD) method 7.4 Reliability-based robust geotechnical design (RGD) 7.5 The new safety standards for flood defenses in the Netherlands 7.6 System reliability 7.7 Reliability target 7.8 Gravity retaining wall design example 7.9 Concluding remarks and future work
Earthwork, Geotechnical engineering - Standards, Civil engineering, surveying & building