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Article: Estimation of water retention curve of granular soils from particle-size distribution: a Bayesian probabilistic approach

TitleEstimation of water retention curve of granular soils from particle-size distribution: a Bayesian probabilistic approach
Authors
KeywordsBayesian analysis
Particle-size distribution
Saturation
Soil suction
Unsaturated soils
Issue Date2012
PublisherNRC Research Press. The Journal's web site is located at http://pubs.nrc-cnrc.gc.ca/cgi-bin/rp/rp2_desc_e?cgj
Citation
Canadian Geotechnical Journal, 2012, v. 49 n. 9, p. 1024-1035 How to Cite?
AbstractThis study proposes two empirical relationships to estimate the parameters of van Genuchten's formula for modeling the water retention curve from the particle-size distribution. The relationships are determined by the Bayesian probabilistic method for selecting the most plausible class of models based on a database of 90 soil samples. The highest plausibility model among the selected relationships shows that the parameter α can be expressed as a first-order function of the particle size at 50% passing (d 50) and parameter n is expressed as a third-order polynomial of the reciprocal of the standard deviation of geometric mean particle size (σ g). The predictability of proposed relationships for other soils outside the calibrated database is also presented. It is found that the model prediction is highly consistent with the measurements for sands. However it only matches well with the measurements in the low suction regime for soils with at least 20% of fines content.
Persistent Identifierhttp://hdl.handle.net/10722/163615
ISSN
2021 Impact Factor: 4.167
2020 SCImago Journal Rankings: 2.032
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorChiu, CF-
dc.contributor.authorYan, WM-
dc.contributor.authorYuen, KV-
dc.date.accessioned2012-09-12T00:47:53Z-
dc.date.available2012-09-12T00:47:53Z-
dc.date.issued2012-
dc.identifier.citationCanadian Geotechnical Journal, 2012, v. 49 n. 9, p. 1024-1035-
dc.identifier.issn0008-3674-
dc.identifier.urihttp://hdl.handle.net/10722/163615-
dc.description.abstractThis study proposes two empirical relationships to estimate the parameters of van Genuchten's formula for modeling the water retention curve from the particle-size distribution. The relationships are determined by the Bayesian probabilistic method for selecting the most plausible class of models based on a database of 90 soil samples. The highest plausibility model among the selected relationships shows that the parameter α can be expressed as a first-order function of the particle size at 50% passing (d 50) and parameter n is expressed as a third-order polynomial of the reciprocal of the standard deviation of geometric mean particle size (σ g). The predictability of proposed relationships for other soils outside the calibrated database is also presented. It is found that the model prediction is highly consistent with the measurements for sands. However it only matches well with the measurements in the low suction regime for soils with at least 20% of fines content.-
dc.languageeng-
dc.publisherNRC Research Press. The Journal's web site is located at http://pubs.nrc-cnrc.gc.ca/cgi-bin/rp/rp2_desc_e?cgj-
dc.relation.ispartofCanadian Geotechnical Journal-
dc.rightsCanadian Geotechnical Journal. Copyright © NRC Research Press.-
dc.subjectBayesian analysis-
dc.subjectParticle-size distribution-
dc.subjectSaturation-
dc.subjectSoil suction-
dc.subjectUnsaturated soils-
dc.titleEstimation of water retention curve of granular soils from particle-size distribution: a Bayesian probabilistic approachen_US
dc.typeArticleen_US
dc.identifier.emailChiu, CF: acfchiu@yahoo.com.cn-
dc.identifier.emailYan, WM: ryanyan@hku.hk-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1139/t2012-062-
dc.identifier.scopuseid_2-s2.0-84865302920-
dc.identifier.hkuros206494-
dc.identifier.volume49-
dc.identifier.issue9-
dc.identifier.spage1024-
dc.identifier.epage1035-
dc.identifier.isiWOS:000308161200003-
dc.publisher.placeCanada-
dc.identifier.issnl0008-3674-

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