Selection of sand models and identification of parameters using an enhanced genetic algorithm

Y.-F. Jin, Zhenyu Yin, S.-L. Shen, P.-Y. Hicher

Research output: Journal article publicationJournal articleAcademic researchpeer-review

116 Citations (Scopus)


© 2016 John Wiley & Sons, Ltd.Numerous constitutive models of granular soils have been developed during the last few decades. As a consequence, how to select an appropriate model with the necessary features based on conventional tests and with an easy way of identifying parameters for geotechnical applications has become a major issue. This paper aims to discuss the selection of sand models and parameters identification by using genetic algorithm. A real-coded genetic algorithm is enhanced for the optimization with high efficiency. Models with gradually varying features (elastic-perfectly plastic modelling, nonlinear stress-strain hardening, critical state concept and two-surface concept) are selected from numerous sand models as examples for optimization. Conventional triaxial tests on Hostun sand are selected as the objectives in the optimization. Four key points are then discussed in turn: (i) which features are necessary to be accounted for in constitutive modelling of sand; (ii) which type of tests (drained and/or undrained) should be selected for an optimal identification of parameters; (iii) what is the minimum number of tests that should be selected for parameter identification; and (iv) what is the suitable and least strain level of objective tests to obtain reliable and reasonable parameters. Finally, a useful guide, based on all comparisons, is provided at the end of the discussion.
Original languageEnglish
Pages (from-to)1219-1240
Number of pages22
JournalInternational Journal for Numerical and Analytical Methods in Geomechanics
Issue number8
Publication statusPublished - 10 Jun 2016
Externally publishedYes


  • Constitutive model
  • Critical state
  • Genetic algorithm
  • Laboratory test
  • Optimization
  • Sand

ASJC Scopus subject areas

  • Computational Mechanics
  • General Materials Science
  • Geotechnical Engineering and Engineering Geology
  • Mechanics of Materials


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