A new search algorithm for strength anisotropy slope stability analysis based on numerical stress field
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A new search algorithm for strength anisotropy slope stability analysis based on numerical stress field
Vol. 35, Issue 12, (2014)
作者机构:
1. 北京交通大学 城市地下工程教育部重点实验室,北京,100044
2. 江苏省交通科学研究院股份有限公司,江苏,南京,210017
作者简介:
基金信息:
DOI:
CLC:TU433
Online First:15 December 2014,
Published:2014
稿件说明:
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CHEN Li-ping, ZHANG Ding-li, FANG Qian, et al. A new search algorithm for strength anisotropy slope stability analysis based on numerical stress field[J]. 2014, 35(12).
DOI:
CHEN Li-ping, ZHANG Ding-li, FANG Qian, et al. A new search algorithm for strength anisotropy slope stability analysis based on numerical stress field[J]. 2014, 35(12).DOI:
A new search algorithm for strength anisotropy slope stability analysis based on numerical stress field
an analysis algorithm which can be used to determine critical sliding surface and critical height of slope
based on numerical stress field
is presented. Upon the algorithm
firstly
the stress field of slope can be obtained by using the finite element analysis method to get more accuracy. Secondly
through simulation of slope
the laws of generation and movement of particles similar to the process of chain reaction are studied. Finally
the critical sliding surface can be determined. Therefore four conclusions can be drawn: (1) A method for determining the critical sliding surface of slope on account of numerical stress field is proposed
which can find potential failure path while no disturbance of the shape and location of slope sliding surface. (2) By controlling such four factors as range and boundary
excitation source
diffusion path and path metrics
the algorithm can get higher accuracy and simultaneously higher efficiency. (3) The algorithm takes the effect of strength anisotropy on stability of slope into consideration. And it is valid to compute the critical slope height. (4) A detailed calculation example has verified the proposed algorithm. Compared to calculation results obtained by the two methods of PSO and Monte Carlo
the reliability of the algorithm could also be proved.