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Research on the Large Deformation Prediction Model and Supporting Measures of Soft Rock Tunnel

Author(s):






Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2020
Page(s): 1-13
DOI: 10.1155/2020/6630546
Abstract:

The weak surrounding rock has the characteristics of easy softening, poor integrity, low mechanical strength, etc., which makes it easy to induce different degrees of deformation and damage under excavation disturbance and then seriously affects the stability of the tunnel. Carrying out soft rock tunnel deformation prediction research and designing the supporting structure according to the predicted value is of great significance to engineering construction and design. Based on the grey theory, the large deformation of the vault, shoulder, and waist of the soft rock tunnel are predicted, and then the specific bolt support is designed in the maximum predicted value (Smax·R) area. The control effects of different bolts, spacing (d), length (L) on the maximum displacement (Smax·M), and maximum stress (σmax·M) the surrounding rock are analyzed by numerical simulation. Results show that the gray model has high prediction accuracy, the best prediction time is one week, and the maximum error is only 2.99%; with the decrease in d, resin bolt support has a significant supporting effect compared with mortar bolt support, with Smax.M and σmax·M reduced by 64.38% and 10.35%, respectively; as the L of bolt increases, compared with the mortar bolt support, the resin bolt support has a more obvious restraining effect on the surrounding rock deformation, and Smax·M and σmax·M are reduced by 28.20% and 10.00%, respectively; when 4.5 m < L < 6.0 m and 0.6 m < d < 0.7 m, resin bolt support should be adopted; in other ranges, mortar bolt support or resin bolt support has a less significant difference in controlling surrounding rock deformation.

Copyright: © Junying Rao et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10535961
  • Published on:
    01/01/2021
  • Last updated on:
    02/06/2021
 
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