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

delete2016-10-01
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李亚军 封面图
李亚军 (Yajun Li)
M
Michael Hicks *
P
Philip J. Vardon
DOI:10.1016/j.compgeo.2016.05.027delete
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摘要

摘要

En 中文
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. (C) 2016 Elsevier Ltd. All rights reserved.
Keyword:
Conditional random fields
Kriging
Reliability
Sampling efficiency
Spatial variability
Uncertainty reduction
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Computers and Geotechnics 封面图
Computers and Geotechnics
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6.2
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被引数:
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Delft University of Technology
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论文数: 2.5W
被引数: 3.8W
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