Reliability and Statistics in Geotechnical Engineering

By Donald E. Myers. Technometrics, 2005

614 citations recorded by the source corpus.

Subfields: Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/56c2fe072530c3c4c428e086ce88a54824143b6c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Safety, Risk, Reliability and Quality

1. Dianqing Li
2. Kok-Kwang Phoon
3. Z. Cao
4. Xiao-Song Tang
5. Chuangbing Zhou
6. Li-min Zhang
7. Dong Zheng
8. A. Soubra

Citations in the corpus

• Effect of spatial variability of cross‐correlated soil properties on bearing capacity of strip footing (2010, background): “A ratio of about 1 to 10 for these autocorrelation distances is common [8].”
• Application of fuzzy set theory to evaluate the probability of failure in rock slopes (2012, background): “The advantages of Monte Carlo simulation are that it is relatively easy to implement on a computer and it can deal with a wide range of functions, including those that cannot be expressed conveniently in an explicit form (Baecher and Christian, 2003).”
• Bivariate simulation using copula and its application to probabilistic pile settlement analysis (2013, background): “INTRODUCTION The geotechnical engineering literature is replete with correlations between two engineering parameters, for example, undrained shear strength and cone tip resistance, negative correlation between cohesion and friction angle [1,2], two hyperbolic curve-fitting parameters underlying load”
• Random field characterisation of stress-normalised cone penetration testing parameters (2005, methodology): “The mathematical and statistical techniques commonly used to treat stochastic processes are then useful to describe spatial variations in a parsimonious and concise way ( Baecher & Christian, 2003 ).”
• Improved knowledge-based clustered partitioning approach and its application to slope reliability analysis (2012, methodology): “Furthermore, these parameters usually follow non-normal distributions [2,33,17,19].”
• Probabilistic analysis of strip footings resting on a spatially random soil using subset simulation approach (2012, background): “A common ratio of about 1 10 for these autocorrelation lengths can be used (Baecher and Christian 2003).”
• Efficient reliability method for implicit limit state surface with correlated non‐Gaussian variables (2015, neutral): “The procedure is well explained elsewhere [15, 20, 21].”
• Learning soil parameters and updating geotechnical reliability estimates under spatial variability – theory and application to shallow foundations (2017, background): “…to the inherent variability of soil mass due to the intrinsic randomness of soil formation processes, the statistical uncertainty due to the limited number of site investigations and the errors in measurement devices and data processing (Phoon and Kulhawy 1999; Baecher and Christian 2003).”
• Response surface methods for slope reliability analysis: Review and comparison (2016, background): “Reliability analysis of soil slopes has gained considerable attention in the geotechnical reliability community over the past few decades (e.g., Baecher and Christian, 2003; Low and Tang, 2004; Cho, 2007, 2009, 2010, 2013; Fenton and Griffiths, 2008; Ching et al., 2009; Wang et al., 2010, 2011; Ji…”