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A stochastic approach in modelling and estimating geotechnical data
Author(s) -
Christakos George
Publication year - 1987
Publication title -
international journal for numerical and analytical methods in geomechanics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.419
H-Index - 91
eISSN - 1096-9853
pISSN - 0363-9061
DOI - 10.1002/nag.1610110107
Subject(s) - consistency (knowledge bases) , geotechnical engineering , field (mathematics) , homogeneous , stochastic process , process (computing) , random field , stochastic modelling , computer science , geotechnical investigation , data mining , geology , mathematics , statistics , artificial intelligence , combinatorics , pure mathematics , operating system
A rational approach for dealing with uncertainties in geotechnical performance predictions is presented. First, sources of uncertainty are identified and treated stochastically. Then, the relative importance of each source is analysed and its influence in the decision‐making process is evaluated. Strong inferences concerning the spatial structure of soils are drawn from field or laboratory measurements, while maintaining consistency with engineering knowledge and experimenal findings. Optimal estimates of soil properties are derived by a stochastic method which is mathematically meaningful and portrays adequately the real behaviour of the data. The method is powerful when the data exhibit homogeneous or non‐homogeneous characteristics, and works well with any kind of data support. Its applicability is illustrated in a case study involving field vane data. Furthermore, contributions and benefits of the results obtained to the geotechnical decisions and design are discussed.