土工基础 ›› 2022, Vol. 36 ›› Issue (2): 214-218.

• 专题论述 • 上一篇    下一篇

基于粒子群差分进化耦合算法的滑带土强度三维数值反演分析

张述涛,彭 君   

  1. (民航中南机场设计研究院(广州)有限公司,广州 510405)
  • 收稿日期:2021-08-04 修回日期:2021-08-17 出版日期:2022-04-30 发布日期:2022-04-27
  • 作者简介:张述涛(1985-),男,高级工程师,研究方向为机场工程总承包管理、岩土工程、机场场道工程设计。

Numerical Back Analysis of Soil Strength near Failure Plane using Particle Swarm Optimization and Differential Evolution Coupled Method

ZHANG Shutao, PENG Jun   

  1. (CAAC Central & Southern Airport Design & Research Institute (Guangzhou) Co. Ltd., Guangzhou 510405)
  • Received:2021-08-04 Revised:2021-08-17 Online:2022-04-30 Published:2022-04-27

摘要: 滑动带作为滑坡的重要组成部分,是滑坡形成、发育和演化的关键,滑带土强度参数的确定对于滑坡稳定性分析具有重要意义。由于滑带土分布和参数的离散性、取样扰动影响和试验的误差,难以获得准确的参数值,对于体型复杂的滑坡,以调研得到的稳定性状态进行三维数值参数反演分析是确定滑带土强度的较好方法。然而,采用试算法的反演方法存在三维数值分析工作量大的问题。以云南腾冲机场滑坡为例,依据实际的地形建立了精细化的三维数值模型,采用粒子群-差分进化法对滑坡当前状态滑带土强度进行参数反演,得出了滑带土饱和参数组合。采用该方法大大提高了滑坡参数反演分析的计算效率。

关键词: 参数反演, 滑坡, 滑带土, 粒子群算法

Abstract: The failure plane is a critical part of the entire landslide components and plays a key role in the form, development and evolution of a landslide. Therefore, the determination of the shear strength parameters at the failure plane is very important in the landslide stability evaluation. However, it is difficult to accurately obtain the design parameters due to the discrete nature of the failure plane distribution, the sampling disturbance and the potential testing errors. For landslide with complicated sliding bodies, the strength parameters obtained from the back analysis with the three-dimensional numerical analysis is still a good method, although the many disadvantages exist in the trial-and-error method in the numerical analysis. This paper presents a case history of three-dimensional numerical back analysis results on a landslide at the Yunnan Tengchong Airport using Particle Swarm Optimization and Differential Evolution approach. The detailed numerical model was established based on the actual topographical conditions and the strength parameters at the failure plane were obtained. This method significantly improves the efficiency of the back analysis process. 

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