An effective method for real-time estimation of slope stability with numerical back analysis based on particle swarm optimization

被引:2
|
作者
Zou, Jiaqiang [1 ,2 ]
Chen, Hao [3 ]
Jiang, Yu [3 ]
Zhang, Wei [1 ]
Liu, Aihua [1 ]
机构
[1] South China Agr Univ, Coll Water Conservancy & Civil Engn, Guangzhou 510642, Peoples R China
[2] Univ Nat Resources & Life Sci, Inst Geotech Engn, A-1180 Vienna, Austria
[3] Guangzhou PRHRI Engn Survey & Design Co Ltd, Guangzhou 510610, Guangdong, Peoples R China
关键词
slope stability; back analysis; particle swarm optimization; SPATIAL VARIABILITY; NEURAL-NETWORKS; PARAMETERS; LANDSLIDE; PREDICTION; ALGORITHM; CRITERION; FAILURE; MODEL;
D O I
10.1515/arh-2022-0143
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
The purpose of this article is to provide an effective approach to evaluate slope stability in real-time in a reservoir area, which is significant for carrying out risk management for landslide disaster prevention in various engineering practices. A comprehensive idea for stability estimation of bank slope under the influence of rainfall or the reservoir water level is presented in this work. Slope stability analysis and back analysis of soil parameters are both included based on numerical simulation. The mechanical parameters of the bank slope were first back-analyzed using particle swarm optimization (PSO), and real-time stability analysis with high accuracy and efficiency was then established based on multiple continuously monitored displacements. Two case studies were carried out in this study. The results show that (1) based on the real-time monitored displacement and numerical simulation, the mechanical parameters of the slope can be reasonably retrieved through PSO; and (2) based on the inverse mechanical parameters, the safety factors of the slope can be numerically obtained, so that the real-time estimation of slope stability can be realized.
引用
收藏
页数:16
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