基于改进粒子群算法的面板堆石坝流变反演分析

doi:10.13722/j.cnki.jrme.2021.0327

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Abstract To improve the performance of particle swarm optimization(PSO) in model parameter inversion，an improved PARTICLE swarm optimization(FPSO) algorithm is proposed. By using linear piecewise function and exponential function，the learning factors and are adjusted by asynchronous strategy to realize dynamic adjustment of inertia weight and and with the number of iterations. The particle diversity is guaranteed by the immune mutation operator and convergence rate is guaranteed by the formation search，which is applied to the parameter inversion analysis of the incremental rheological model of the Arts face dam. The results show that：(1) the FPSO algorithm can effectively improve the accuracy and efficiency of the inversion analysis because it better fits the motion characteristics of particle from the early high-speed global search to the late local fine search，and the global search ability is greatly improved. (2) By using the measured settlement of the dam during the downtime，the rheological parameters of the rockfill are inverted based on FPSO，and the calculated results are in good agreement with the monitored values.

Key words： hydraulic engineering concrete face rockfill dam rheological particle swarm optimization immune variation inversion analysis FEM

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	ZHU Sheng1
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	LU Deren1
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Cite this article:

ZHU Sheng1,2,LU Deren1, et al. Rheological inversion analysis of face rockfill dam based on improved particle swarm optimization algorithm[J]. , 2022, 41(S1): 2971-2978.

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http://rockmech.whrsm.ac.cn/EN/10.13722/j.cnki.jrme.2021.0327 OR http://rockmech.whrsm.ac.cn/EN/Y2022/V41/IS1/2971

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