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Indexed by:期刊论文

Date of Publication:2012-01-01

Journal:Electronic Journal of Geotechnical Engineering

Included Journals:EI、Scopus

Volume:17 Y

Page Number:3645-3655

ISSN No.:10893032

Abstract:In order to deal with the ill-posed problem of material parameter identification for rockfill materials, a procedure based on neural network is proposed. Duncan-Chang nonlinear constitutive model is adopted to characterize the behavior of the modeled rockfill materials. An analytical solution for computing the relationship between strain and vertical load is approached for simulating triaxial compression experiments. Based on neural network, the material parameters are determined from the triaxial compression experimental results. The investigation results show that the predicted strains provide satisfactory precision by comparing with observed ones. ? 2012, EJGE.