Journal
COMPUTERS AND GEOTECHNICS
Volume 79, Issue -, Pages 159-172Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.compgeo.2016.05.027
Keywords
Conditional random fields; Kriging; Reliability; Sampling efficiency; Spatial variability; Uncertainty reduction
Categories
Funding
- China Scholarship Council (CSC)
- Section of Geo-Engineering at Delft University of Technology
- SURF Foundation
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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.
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