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MODERN TUNNELLING TECHNOLOGY 2025, Vol. 62 Issue (2) :49-59    DOI:
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Study on the Distribution Law of Geotress Field and Classification of Disaster Prediction in Super Long and Deep-buried Highway Tunnels
(1. Key Laboratory of Transportation Tunnel Engineering of Ministry of Education, Southwest Jiaotong University, Chengdu 610031;2. Sichuan Transportation Survey and Design Research Institute Co., Ltd., Chengdu 610017)
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Abstract To investigate the characteristics of the geostress field along the axis of the Longmenshan super-long deep-buried tunnel, a 3D geological model was established using ABAQUS based on engineering geological survey and hydraulic fracturing test data. The nonlinear inversion of the geostress field was performed using the Bayesian regularized neural network, analyzing the impact of active fault zones on the geostress field, and comparing the results with traditional multiple linear regression methods. The results indicate: (1) The principal stress increases approximately linearly with the buried depth, with horizontal tectonic stress dominating( ), and the principal stress along the tunnel route exceeds 20 MPa, with local peaks reaching 64.5 MPa; (2) The geostress value in hard rock sections is very high, indicating a moderate risk of rock bursts; in soft rock sections, the risk of large deformation is significant, and local stress differences lead to the instability of surrounding rock; (3) In the fault zone, the variation rane of geostress is large, the azimuth angle shows deviation, and the surrounding strata exhibit stress relaxation and stress concentration in valleys.
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YUAN Quanyou1 CHEN Ziquan1 YUAN Song1
2 WANG Xibao2 JIANG Changwei1
KeywordsDeep-buried tunnel   Geostress field   Intelligent inversion analysis   Neural network   Bayesian regulariza? tion   Disaster prediction classification     
Abstract: To investigate the characteristics of the geostress field along the axis of the Longmenshan super-long deep-buried tunnel, a 3D geological model was established using ABAQUS based on engineering geological survey and hydraulic fracturing test data. The nonlinear inversion of the geostress field was performed using the Bayesian regularized neural network, analyzing the impact of active fault zones on the geostress field, and comparing the results with traditional multiple linear regression methods. The results indicate: (1) The principal stress increases approximately linearly with the buried depth, with horizontal tectonic stress dominating( ), and the principal stress along the tunnel route exceeds 20 MPa, with local peaks reaching 64.5 MPa; (2) The geostress value in hard rock sections is very high, indicating a moderate risk of rock bursts; in soft rock sections, the risk of large deformation is significant, and local stress differences lead to the instability of surrounding rock; (3) In the fault zone, the variation rane of geostress is large, the azimuth angle shows deviation, and the surrounding strata exhibit stress relaxation and stress concentration in valleys.
KeywordsDeep-buried tunnel,   Geostress field,   Intelligent inversion analysis,   Neural network,   Bayesian regulariza? tion,   Disaster prediction classification     
Cite this article:   
YUAN Quanyou1 CHEN Ziquan1 YUAN Song1, 2 WANG Xibao2 JIANG Changwei1 .Study on the Distribution Law of Geotress Field and Classification of Disaster Prediction in Super Long and Deep-buried Highway Tunnels[J]  MODERN TUNNELLING TECHNOLOGY, 2025,V62(2): 49-59
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