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

Y. Li; M. A. Hicks; P. J. Vardon

doi:10.1016/j.compgeo.2016.05.027

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

Y. Li, M. A. Hicks^*, P. J. Vardon

^*Corresponding author for this work

Geo-engineering

Research output: Contribution to journal › Article › Scientific › peer-review

96 Citations (Scopus)

166 Downloads (Pure)

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.

Original language	English
Pages (from-to)	159-172
Number of pages	14
Journal	Computers and Geotechnics
Volume	79
DOIs	https://doi.org/10.1016/j.compgeo.2016.05.027
Publication status	Published - 1 Oct 2016

Keywords

Conditional random fields
Kriging
Reliability
Sampling efficiency
Spatial variability
Uncertainty reduction

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10.1016/j.compgeo.2016.05.027

cond_3d_li et al COGE 2016 vol79Accepted author manuscript, 1.18 MBLicence: CC BY-NC-ND

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title = "Uncertainty reduction and sampling efficiency in slope designs using 3D conditional random fields",

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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AU - Li, Y.

AU - Hicks, M. A.

AU - Vardon, P. J.

PY - 2016/10/1

Y1 - 2016/10/1

N2 - 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.

AB - 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.

KW - Conditional random fields

KW - Kriging

KW - Reliability

KW - Sampling efficiency

KW - Spatial variability

KW - Uncertainty reduction

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DO - 10.1016/j.compgeo.2016.05.027

M3 - Article

SN - 0266-352X

VL - 79

SP - 159

EP - 172

JO - Computers and Geotechnics

JF - Computers and Geotechnics

ER -

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

Abstract

Keywords

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Reliability of long heterogeneous slopes in 3d: Model performance and conditional simulation

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