Numerical Optimisation of Excavation Pit Design Using Finite Element Analyses

被引:0
作者
Hauke Jürgens
Sascha Henke
机构
[1] Helmut Schmidt University/University of the Federal Armed Forces Germany,Department of Geotechnics
来源
Geotechnical and Geological Engineering | 2024年 / 42卷
关键词
Finite element analysis; Numerical methods; Excavation pit; Particle swarm optimisation; Differential evolution;
D O I
暂无
中图分类号
学科分类号
摘要
The present study focusses on optimising a single supported excavation pit to achieve a more economical design using finite element analyses. Two methods for automating the derivation of the excavation pit’s necessary embedment depth are presented, which involve either embedment depth reduction using additional calculation phases or adapting the entire model with renewed discretisation. The bending moments as well as the earth pressure distribution along the wall show good agreement, indicating that both methods are suitable for application. Subsequently, the feasibility of using optimisation algorithms (Particle Swarm Optimisation and Differential Evolution) for dimensioning the single supported excavation pit regarding stress analysis of the wall is investigated. Therefore, the embedment depth and the position of the strut are varied for five different sheet pile walls and three different strut profiles. The results demonstrate that both algorithms perform well, particularly with a higher number of calculation steps. After varying iteration steps and population size, the Differential Evolution approach shows better performance compared to Particle Swarm Optimisation by means of finding the optimal solution after a lower number of computational steps.
引用
收藏
页码:1659 / 1673
页数:14
相关论文
共 138 条
[1]  
Cheng YM(2007)Particle swarm optimization algorithm for the location of the critical non-circular failure surface in two-dimensional slope stability analysis Comput Geotech 34 92-103
[2]  
Li L(2021)35 Years of (AI) in geotechnical engineering: State of the art Geotech Geol Eng 39 637-690
[3]  
Chi S(2017)Optimization of retaining wall design using evolutionary algorithms Struct Multidisc Optim 55 809-825
[4]  
Wei WB(2017)Slope stability analysis using evolutionary optimization techniques Int J Numer Anal Methods Geomech 41 251-264
[5]  
Ebid AM(2010)Inverse determination of soil density and stress state using dispersion wave measurements and cone penetration tests in a non-layered soil Soil Dyn Earthq Eng 30 481-489
[6]  
Gandomi AH(2018)Applications of particle swarm optimization in geotechnical engineering: a comprehensive review Geotech Geol Eng 36 705-722
[7]  
Kashani AR(2010)Comparison of two inverse analysis techniques for learning deep excavation response Comput Geotech 37 323-333
[8]  
Roke DA(2020)Assessment of optimum location of non-circular failure surface in soil slope using unified particle swarm optimization Geotech Geol Eng 38 2061-2083
[9]  
Mousavi M(2019)Multi-objective optimization-based updating of predictions during excavation Eng Appl Artif Intell 78 102-123
[10]  
Gandomi AH(2020)Intelligent model selection with updating parameters during staged excavation using optimization method Acta Geotech 15 2473-2491