Reliability and Statistics in Geotechnical Engineering

By G. Baecher. 2003

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A computational study on the uncertainty quantification of failure of clays with a modified Cam-Clay yield criterion (2021, background): “In the present work, Ni are linear functions and the fi follow the truncated normal distribution [2, 6, 7, 49] which has a pdf described by the equation g1(x) = (X0) d (Φ(B)−Φ(A)) , where (X0) and Φ(X0) are the standard normal probability and cumulative distribution function for X0 , respectively, a”
Bayesian identification of random field model using indirect test data (2016, background): “Inherent spatial variability (ISV) of soils is one of major sources of uncertainties in soil properties (e.g., Phoon and Kulhawy, 1999a; Baecher and Christian, 2003; Wang et al., 2016).”
Impact of sample size on geotechnical probabilistic model identification (2017, background): “, marginal distribution for single parameter or joint probability distribution for multiple correlated parameters) for geotechnical parameters are essential inputs for geotechnical reliability analysis and risk assessments [27,3,8,22].”