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

Journal Article (2016)
Author(s)

Y Li (TU Delft - Geo-engineering)

Michael Hicks (TU Delft - Geo-engineering)

Philip James Vardon (TU Delft - Geo-engineering)

Geo-engineering
Copyright
© 2016 Y. Li, M.A. Hicks, P.J. Vardon
DOI related publication
https://doi.org/10.1016/j.compgeo.2016.05.027
More Info
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Publication Year
2016
Language
English
Copyright
© 2016 Y. Li, M.A. Hicks, P.J. Vardon
Related content
Geo-engineering
Volume number
79
Pages (from-to)
159-172
Reuse Rights

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Abstract

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.

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