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- Title
Optimization of anchorage support parameters for soft rock tunnel based on displacement control theory.
- Authors
Li, Gan; Ma, Wei-bin; Yu, Chang-yi; Tao, Zhi-gang; Wang, Feng-nian
- Abstract
In the construction of a soft rock tunnel, it is critical to accurately estimate the pre-stressed anchor support parameters for surrounding rock reinforcement; otherwise, engineering disasters may occur. This paper presents a support parameter selection method that aims to allow deformation as a control objective, which was applied to the tunnel located in Muzailing Highway, Min County, Dingxi City, Gansu Province, China. Through theoretical analysis, we have identified five factors that influence pre-stressing anchorages. The selection of mechanical parameters for the rock mass was carried out using an inverse analysis method. Compared with the measured data, the maximum displacement error of the numerical simulation results was only 0.07 m. The length of anchor cable, circumferential spacing of anchor cable, longitudinal spacing, and pre-stress index are adopted as the input parameters for the support vector machine neural network model based on particle swarm optimization (PSO-LSSVM). Besides, the vault subsidence and the maximum deformation of surrounding rock are considered as output values (performance indices). The goodness of fit between the predicted values and the simulated values exceeds 0.9. Finally, all support parameters within the acceptable deformation range are calculated. The optimal support variables are derived by considering the construction cost and duration. The field application results show that it is feasible to construct the sample database utilizing the numerical simulation approach by taking the displacement as the control target and using the neural network to specify the appropriate support parameters.
- Subjects
GANSU Sheng (China); CHINA; ANCHORAGE; PARTICLE swarm optimization; TUNNEL design &; construction; SUPPORT vector machines; ROCK deformation; CONTROL theory (Engineering); QUANTUM tunneling
- Publication
Journal of Mountain Science, 2023, Vol 20, Issue 7, p2076
- ISSN
1672-6316
- Publication type
Article
- DOI
10.1007/s11629-023-7999-4