[1]包腾飞,程健悦,邢　钰,等.基于GD-PSO的水电站地下洞室初始地应力场反演[J].郑州大学学报(工学版),2025,46(05):130-136.[doi:10.13705/j.issn.1671-6833.2025.05.002]
　BAO Tengfei,CHENG Jianyue,XING Yu,et al.Inversion of Initial In-situ Stress Field of Underground Caverns of Hydropower Station Based on GD-PSO[J].Journal of Zhengzhou University (Engineering Science),2025,46(05):130-136.[doi:10.13705/j.issn.1671-6833.2025.05.002]
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基于GD-PSO的水电站地下洞室初始地应力场反演()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
46
期数:
2025年05期
页码:
130-136
栏目:
出版日期:
2025-08-10

文章信息/Info

Title:
Inversion of Initial In-situ Stress Field of Underground Caverns of Hydropower Station Based on GD-PSO
文章编号:
1671-6833(2025)05-0130-07
作者:
包腾飞1;  程健悦1;  邢　钰2;  周喜武3;  陈雨婷1;  赵向宇1
1.河海大学 水利水电学院,江苏 南京 210098;2.中国电建集团北京勘测设计研究院有限公司,北京 100024;3.江苏省水利工程科技咨询股份有限公司,江苏 南京 210029
Author(s):
BAO Tengfei1;  CHENG Jianyue1;  XING Yu2;  ZHOU Xiwu3;  CHEN Yuting1;  ZHAO Xiangyu1
1.College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China; 2.Power China Beijing Engineering Co., Ltd., Beijing 100024, China; 3. Jiangsu Province Water Engineering Sci-tech Consulting Co., Ltd., Nanjing 210029, China
关键词:
大型抽水蓄能电站;  地下洞室群;  地应力反演;  梯度下降法;  粒子群优化算法
Keywords:
large pumped storage power station;  underground caverns;  in-situ stress inversion;  gradient descent method;  particle swarm optimization
分类号:
TV22
DOI:
10.13705/j.issn.1671-6833.2025.05.002
文献标志码:
A
摘要:
针对现有的初始地应力场反演方法难以平衡收敛速度和非线性回归精度的问题,提出了一种联合梯度下降法(GD)和粒子群优化算法(PSO)的初始地应力场反演分析方法。首先,考虑影响初始地应力场的重力场及5种构造应力场的8种基础边界条件,利用有限元软件计算各边界条件下测点应力值;其次,以实测地应力值为目标值,利用GD-PSO算法进行回归分析,得到各边界条件的影响系数;最后,计算模型各点的回归地应力值,并作为初始地应力场输入三维有限元模型进行地应力平衡。实例分析表明:对比使用PSO算法的计算结果,使用GD-PSO算法求得的三次回归多项式精度最高,均方误差为0.579,回归结果与实测地应力值拟合较好,地应力平衡后除竖直方向应力值外,测点地应力值与实测值差值较小,围岩各向位移基本为零,最大位移仅有5.26 mm。
Abstract:
In view of the difficulty of balancing convergence speed and nonlinear regression accuracy of existing inversion methods, a new method combining gradient descent (GD) and particle swarm optimization (PSO) for inversion analysis of initial in-situ stress field was proposed. In this method, the gravity field and five tectonic stress fields that affects the initial in-situ stress field were considered as eight basic boundary conditions. The stress values of measuring points with each boundary condition were calculated by using finite element software. The measured in-situ stress values were taken as the target values, and the influence coefficients of each boundary condition were obtained by regression analysis using GD-PSO algorithm. The regression stress values of each point of the model were calculated and input into the 3D finite element model as the initial stress field to balance the in-situ stress. The example analysis showed that compared with the calculation results of PSO algorithm, the cubic regression polynomial obtained by GD-PSO algorithm had the highest accuracy, and the mean square error was 0.579. The regression results fit well with the measured ground stress values. After the in-situ stress balance, except for the vertical stress value, the difference between the calculated in-situ stress value at the measurement point and the measured value was relatively small, and the directional displacement of surrounding rock was basically zero, and the maximum displacement was only 5.26 mm.

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更新日期/Last Update: 2025-09-19