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contributor authorKok-Kwang Phoon
contributor authorAnastasia Santoso
contributor authorSer-Tong Quek
date accessioned2017-05-08T21:46:39Z
date available2017-05-08T21:46:39Z
date copyrightMarch 2010
date issued2010
identifier other%28asce%29gt%2E1943-5606%2E0000238.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/61993
description abstractDirect measurement of the soil-water characteristic curve (SWCC) is costly and time consuming. A first-order estimate from statistical generalization of experimental data belonging to soils with similar textural and structural properties is useful. A simple approach is to fit the data with a nonlinear function and to construct an appropriate probability model of the curve-fitting parameters. This approach is illustrated using sandy clay loam, loam, loamy sand, clay, and silty clay data in Unsaturated Soil Database. This paper demonstrates that a lognormal random vector is suitable to model the curve-fitting parameters of the SWCC. Other probability models using normal, gamma, Johnson, and other distributions do not provide better fit than the proposed lognormal model. The engineering impact of adopting a probabilistic SWCC is briefly discussed by studying the uncertainty of unsaturated shear strength due to the uncertainty of SWCC.
publisherAmerican Society of Civil Engineers
titleProbabilistic Analysis of Soil-Water Characteristic Curves
typeJournal Paper
journal volume136
journal issue3
journal titleJournal of Geotechnical and Geoenvironmental Engineering
identifier doi10.1061/(ASCE)GT.1943-5606.0000222
treeJournal of Geotechnical and Geoenvironmental Engineering:;2010:;Volume ( 136 ):;issue: 003
contenttypeFulltext


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