Tunnel advance geology forecast method based on surrounding rock deformation monitoring and numerical simulation

Abstract

The invention discloses a tunnel advance geology forecast method based on surrounding rock deformation monitoring and numerical simulation. The method comprises the steps that the actual classification condition of surrounding rock at the current section and preliminary qualitative classification which is conducted on surrounding rock in front of the surrounding rock at the current section by a distance through a comprehensive advance geology forecast method are combined, comprehensive quantity analysis is conducted on the surrounding rock in front of the surrounding rock at the current section by a distance, qualitative classification data obtained by conducting advance forecast on the surrounding rock in front of the surrounding rock by a distance at the current section through the comprehensive advance geology forecast method are amended, the man-made subjectivity in the advance forecast is reduced, and the objectivity of geology forecast is increased. The mode that 'one section is verified and one section is forecasted when one section is passed' is used for comparing the surrounding rock classification obtained qualitatively at the next section with the classification, obtained qualitatively, of the surrounding rock at the current section, so that the classification of the surrounding rock at the next section is obtained through qualitative analysis, and the classification and parameter, obtained through qualitative analysis, of the surrounding rock at the next section are amended. Comprehensive evaluation can be conducted on the advance geology forecast of the tunnel surrounding rock, and the accuracy of tunnel advance forecast is greatly improved.

Description

technical field [0001] The invention relates to the field of advanced geological prediction of underground engineering, in particular to a tunnel advanced geological prediction method based on surrounding rock deformation monitoring and numerical simulation. Background technique [0002] Tunnel is a building that deals with rock mass, but due to the ever-changing rock mass structure, the geological conditions ahead of tunnel construction are random, fuzzy and unpredictable. However, in tunnel construction, the construction methods and support measures used need to be adjusted according to the geological conditions. Therefore, it is of great economic value to do a good job in the geological forecast and grade identification work ahead of the tunnel construction process. [0003] In the existing technology, the geological forecast ahead of tunnel construction is mainly based on geological radar and TSP technology, but this kind of method is mainly based on the operator's exper...

AI Technical Summary

Problems solved by technology

In addition, the deformation of the tunnel structure, especially the deformation of the surrounding rock, is directly related to the geological conditions in front of the tunnel face. A single forecast of the geological conditions in front of the tunnel cannot achieve the forecast results without comparison and verification of the deformation monitoring of the tunnel excavation structure after the prediction. the accuracy of

For example, patents such as "Dynamic refinement and classification method for tunnel excavation surrounding rock based on comprehensive parameters" (CN02736124A), "method for advanced forecasting of underground engineering" (CN102495434 A), etc., use various geophysical prospecting methods to observe the geological conditions of the tunnel face, As well as the deformation measurement data of the structure, etc., the surrounding rock in front of the excavation face of the tunnel is graded to ensure the safety of the tunnel construction, but there is no "passing a section, verifying a section, and predicting a section". The comparison and analysis of the predicted deformation data generated by the structure before excavation and the monitoring measurement data during the excavation stage is simply a qualitative analysis of the surrounding rock in the excavation section ahead, without quantitative grading of the surrounding rock in combination with the actual excavation deformation , failed to effectively analyze the difference between the predicted deformation data and the actual excavation monitoring data, so that the previous prediction data could not be effectively verified

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