Inversion of Initial In-situ Stress Field of Underground Caverns of Hydropower Station Based on GD-PSO

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Inversion of Initial In-situ Stress Field of Underground Caverns of Hydropower Station Based on GD-PSO

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[1]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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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 46 Number of periods: 2025 05 Page number: 130-136 Column: Public date: 2025-08-10

Title:: Inversion of Initial In-situ Stress Field of Underground Caverns of Hydropower Station Based on GD-PSO

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

Keywords:: large pumped storage power station; underground caverns; in-situ stress inversion; gradient descent method; particle swarm optimization

CLC:: TV22

DOI:: 10.13705/j.issn.1671-6833.2025.05.002

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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Last Update: 2025-09-19