<p>Accurate prediction of the deformation grade of surrounding rock is of critical importance. This study introduces an integrated prediction approach that combines advanced geological prediction techniques with geomechanical parameters. An improved strength–stress ratio method (S) was constructed by coupling the rock mass integrity coefficient, softening coefficient, and the conventional M-value. Based on the S-value, continuous and quantitative prediction of the surrounding rock-deformation risk in tunnels was achieved. The S-model was successfully applied to the Shizishan Tunnel and effectively identified deformation-risk zones. The predicted results showed a high degree of consistency with the field-measured deformation data. The findings confirm that the S-model offers better performance than conventional approaches and can be effectively applied in engineering practice.</p>

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Tunnel Large Deformation Risk Identification Driven by Advanced Geological Prediction: Model and Engineering Application

  • Xu Wang,
  • Lei Xu,
  • Zhi-Qiang Li,
  • Andong Chen

摘要

Accurate prediction of the deformation grade of surrounding rock is of critical importance. This study introduces an integrated prediction approach that combines advanced geological prediction techniques with geomechanical parameters. An improved strength–stress ratio method (S) was constructed by coupling the rock mass integrity coefficient, softening coefficient, and the conventional M-value. Based on the S-value, continuous and quantitative prediction of the surrounding rock-deformation risk in tunnels was achieved. The S-model was successfully applied to the Shizishan Tunnel and effectively identified deformation-risk zones. The predicted results showed a high degree of consistency with the field-measured deformation data. The findings confirm that the S-model offers better performance than conventional approaches and can be effectively applied in engineering practice.