A critical state sand plasticity model accounting for fabric evolution

SUMMARY Fabric and its evolution need to be fully considered for effective modeling of the anisotropic behavior of cohesionless granular sand. In this study, a three‐dimensional anisotropic model for granular material is proposed based on the anisotropic critical state theory recently proposed by Li...

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Published inInternational journal for numerical and analytical methods in geomechanics Vol. 38; no. 4; pp. 370 - 390
Main Authors Gao, Zhiwei, Zhao, Jidong, Li, Xiang-Song, Dafalias, Yannis F.
Format Journal Article
LanguageEnglish
Published Chichester Blackwell Publishing Ltd 01.03.2014
Wiley
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ISSN0363-9061
1096-9853
DOI10.1002/nag.2211

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Summary:SUMMARY Fabric and its evolution need to be fully considered for effective modeling of the anisotropic behavior of cohesionless granular sand. In this study, a three‐dimensional anisotropic model for granular material is proposed based on the anisotropic critical state theory recently proposed by Li & Dafalias [2012], in which the role of fabric evolution is highlighted. An explicit expression for the yield function is proposed in terms of the invariants and joint invariants of the normalized deviatoric stress ratio tensor and the deviatoric fabric tensor. A void‐based fabric tensor that characterizes the average void size and its orientation of a granular assembly is employed in the model. Upon plastic loading, the material fabric is assumed to evolve continuously with its principal direction tending steadily towards the loading direction. A fabric evolution law is proposed to describe this behavior. With these considerations, a non‐coaxial flow rule is naturally obtained. The model is shown to be capable of characterizing the complex anisotropic behavior of granular materials under monotonic loading conditions and meanwhile retains a relatively simple formulation for numerical implementation. The model predictions of typical behavior of both Toyoura sand and Fraser River sand compare well with experimental data. Copyright © 2013 John Wiley & Sons, Ltd.
Bibliography:ERC IDEAS - No. 290963
istex:86212E6C71BC9B7524879FBFD1460027EBCF11C4
European Research Council under the European Union's Seventh Framework Program - No. FP7/2007-2013
NSF - No. CMMI-1162096
ark:/67375/WNG-4WDW86BH-6
Research Grants Council of Hong Kong - No. GRF 622910; No. SBI08/09.EG02
ArticleID:NAG2211
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ISSN:0363-9061
1096-9853
DOI:10.1002/nag.2211