Two-dimensional probabilistic infiltration analysis with a spatially varying permeability function

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• 作者：H. Zhu^a ; L.M. Zhang^a ; ^{cezhangl@ust.hk} ; L.L. Zhang^b ; C.B. Zhou^c
• 关键词：Random field ; Spatial correlation ; Risk and reliability ; Permeability ; Seepage ; Rainfall infiltration ; Slope stability ; Groundwater
• 刊名：Computers and Geotechnics
• 出版年：2013
• 出版时间：March, 2013
• 年：2013
• 卷：48
• 期：Complete
• 页码：249-259
• 全文大小：3283 K

文摘

The permeability function for a soil may change spatially due to uncertainties in soil fabric. The main objective of this paper is to investigate how the spatial variability of permeability function propagates to the variability of the pore-water pressures and groundwater table in a slope as well as the stability of the slope. A random field analysis method is explored by assigning discrete random values to a 2D space and controlling the density of random field grid to improve the calculation accuracy. Sequences of random numbers are generated using fast Fourier transform. In a given heterogeneous slope subject to steady-state rainfall infiltration, a parametric study shows that the matric suctions are 0.5-1.25 times those in a homogeneous slope when the correlation length of log-permeability varies from 0.4 to 50 times the slope height. The groundwater table is no longer unique with a spatially variable permeability function. There exists a critical correlation length approximately five times the slope height at which the change in the groundwater table is maximal and the mean factor of safety is minimal. The mean factor of safety of the heterogeneous slopes is smaller than that of a homogenous slope with mean input parameters. The spatial variability of soil influences the range of the calculated factor of safety significantly but does not influence the mean factor of safety substantially.