An artificial neural network approach to inhomogeneous soil slope stability predictions based on limit analysis methods

Title: An artificial neural network approach to inhomogeneous soil slope stability predictions based on limit analysis methods
Creator: Qian, Z. G.; Li, A. J.; Chen, W. C.; Lyamin, A. V.; Jiang, J. C.
Relation: Soils and Foundations Vol. 59, Issue 2, p. 556-569
Publisher Link: http://dx.doi.org/10.1016/j.sandf.2018.10.008
Publisher: Japanese Geotechnical Society
Resource Type: journal article
Date: 2019
Description: The assessment of soil slope stability is an important task in geotechnical designs. This study uses finite element upper bound (UB) and lower bound (LB) limit analysis (LA) methods to investigate inhomogeneous soil slope stability on the basis of the conventional Mohr-Coulomb parameters. The obtained stability numbers are presented in inhomogeneous soil slope stability charts. In order to minimize manual reading errors when using the chart solutions, an artificial neural network (ANN) is employed to develop a stability assessment tool for the slopes investigated in this paper. The slope stability analysis using the ANN-based tool is convenient, and the predictions it provides are highly accurate.
Subject: stability number; stability chart; limit analysis; filled slope; artificial neural network
Identifier: http://hdl.handle.net/1959.13/1445997
Identifier: uon:42730
Identifier: ISSN:0038-0806
Language: eng
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