Uncertainty reduction and sampling efficiency in slope designs using 3D conditional random fields

A method of combining 3D Kriging for geotechnical sampling schemes with an existing random field generator is presented and validated. Conditional random fields of soil heterogeneity are then linked with finite elements, within a Monte Carlo framework, to investigate optimum sampling locations and t...

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Bibliographic Details
Published inComputers and geotechnics Vol. 79; pp. 159 - 172
Main Authors Li, Y.J., Hicks, M.A., Vardon, P.J.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.10.2016
Subjects
Conditional random fields
Kriging
Reliability
Sampling efficiency
Spatial variability
Uncertainty reduction
Uncertainty reduction
Spatial variability
Conditional random fields
Sampling efficiency
Reliability
Kriging
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ISSN0266-352X
1873-7633
DOI10.1016/j.compgeo.2016.05.027

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Summary:A method of combining 3D Kriging for geotechnical sampling schemes with an existing random field generator is presented and validated. Conditional random fields of soil heterogeneity are then linked with finite elements, within a Monte Carlo framework, to investigate optimum sampling locations and the cost-effective design of a slope. The results clearly demonstrate the potential of 3D conditional simulation in directing exploration programmes and designing cost-saving structures; that is, by reducing uncertainty and improving the confidence in a project’s success. Moreover, for the problems analysed, an optimal sampling distance of half the horizontal scale of fluctuation was identified.
ISSN:0266-352X
1873-7633
DOI:10.1016/j.compgeo.2016.05.027