Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Research on the Back-Analysis of Tunnel Surrounding Rock Deformation Considering the Deterioration Effect of Surrounding Rock Parameters
https://orcid.org/http://orcid.org/0000-0002-3966-5283
This paper investigates the deformation patterns of surrounding rock in the Xingzishan Tunnel Project, located in Yunnan Province, China, and a method that can respond to the deterioration pattern of the surrounding rock parameters is proposed. The surrounding rock in this project is carbonaceous slate, which possesses the characteristics of anisotropy, and it is hard to detect the mechanical parameters of the rock. A deformation back-analysis method that considers the deterioration effect of the surrounding rock is proposed by using the function approximation and pattern recognition functions of the back propagation (BP) neural network. The fitting equations for the deterioration pattern of the vertical and horizontal elastic moduli E of the surrounding rock are established. Based on the regression prediction of the back propagation (BP) neural network, it is found that the changes in the deformation parameters of the surrounding rock follow certain variation rules within 20 m from the excavation surface. Furthermore, by comparing the deterioration of the surrounding rock in the vertical and horizontal directions, it is considered that the degree of deterioration of the anisotropic surrounding rock varies in different directions. The result is a reference for studying tunnel deformation in anisotropic rocks, and provide a basis for further studies on the deformation mechanisms and control measures of rock surrounding tunnels.
Research on the Back-Analysis of Tunnel Surrounding Rock Deformation Considering the Deterioration Effect of Surrounding Rock Parameters
https://orcid.org/http://orcid.org/0000-0002-3966-5283
This paper investigates the deformation patterns of surrounding rock in the Xingzishan Tunnel Project, located in Yunnan Province, China, and a method that can respond to the deterioration pattern of the surrounding rock parameters is proposed. The surrounding rock in this project is carbonaceous slate, which possesses the characteristics of anisotropy, and it is hard to detect the mechanical parameters of the rock. A deformation back-analysis method that considers the deterioration effect of the surrounding rock is proposed by using the function approximation and pattern recognition functions of the back propagation (BP) neural network. The fitting equations for the deterioration pattern of the vertical and horizontal elastic moduli E of the surrounding rock are established. Based on the regression prediction of the back propagation (BP) neural network, it is found that the changes in the deformation parameters of the surrounding rock follow certain variation rules within 20 m from the excavation surface. Furthermore, by comparing the deterioration of the surrounding rock in the vertical and horizontal directions, it is considered that the degree of deterioration of the anisotropic surrounding rock varies in different directions. The result is a reference for studying tunnel deformation in anisotropic rocks, and provide a basis for further studies on the deformation mechanisms and control measures of rock surrounding tunnels.
Research on the Back-Analysis of Tunnel Surrounding Rock Deformation Considering the Deterioration Effect of Surrounding Rock Parameters
https://orcid.org/http://orcid.org/0000-0002-3966-5283
This paper investigates the deformation patterns of surrounding rock in the Xingzishan Tunnel Project, located in Yunnan Province, China, and a method that can respond to the deterioration pattern of the surrounding rock parameters is proposed. The surrounding rock in this project is carbonaceous slate, which possesses the characteristics of anisotropy, and it is hard to detect the mechanical parameters of the rock. A deformation back-analysis method that considers the deterioration effect of the surrounding rock is proposed by using the function approximation and pattern recognition functions of the back propagation (BP) neural network. The fitting equations for the deterioration pattern of the vertical and horizontal elastic moduli E of the surrounding rock are established. Based on the regression prediction of the back propagation (BP) neural network, it is found that the changes in the deformation parameters of the surrounding rock follow certain variation rules within 20 m from the excavation surface. Furthermore, by comparing the deterioration of the surrounding rock in the vertical and horizontal directions, it is considered that the degree of deterioration of the anisotropic surrounding rock varies in different directions. The result is a reference for studying tunnel deformation in anisotropic rocks, and provide a basis for further studies on the deformation mechanisms and control measures of rock surrounding tunnels.
Research on the Back-Analysis of Tunnel Surrounding Rock Deformation Considering the Deterioration Effect of Surrounding Rock Parameters
Int J Civ Eng
Yan, Liang (Autor:in) / Zhang, Yawei (Autor:in) / Li, Yunong (Autor:in) / Wang, Qiang (Autor:in) / Guo, Yongfa (Autor:in)
International Journal of Civil Engineering ; 22 ; 2059-2089
01.11.2024
31 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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