Abstract
To address the issue of inevitable subjective factors in determining surrounding rock index parameters using existing surrounding rock classification methods, six parameters were comprehensively selected as evaluation indices for tunnel surrounding rock classification based on a review of various classification methods: rock uniaxial saturated compressive strength, rock integrity coefficient, rock mass volume joint count, groundwater, Rock Quality Designation (ROD), and surrounding rock elastic longitudinal wave velocity. The surrounding rock classification was performed using mathematical analytical methods based on entropy weight-extension matter-element theory and entropy weight-cloud model, and the rationality and accuracy were verified using the surrounding rock classification results from the design and construction stages of the Longnan Tunnel on the under-construction Ganzhou-Shenzhen high-speed railway. The results indicate that using the entropy weight method to calculate the weight coefficients of evaluation indices can overcome the subjectivity in weight determination and avoid human interference. These two surrounding rock classification methods represent a new exploration in tunnel surrounding rock classification, which is conducive to the development of surrounding rock classification towards intelligence and informatization.
Full Text
Surrounding Rock Classification Method for Tunnel Construction Based on Entropy Weight Method
ZHANG Bo
China Railway 16th Bureau Group the Third Engineering Co., Ltd., Huzhou 313000, China
Abstract
To address the problem of subjective factors inevitably introduced when determining evaluation indices in existing surrounding rock classification methods, this study comprehensively selected six parameters as evaluation indices for tunnel surrounding rock classification based on a review of various classification approaches: uniaxial saturated compressive strength of rock, rock mass integrity coefficient, volumetric joint count, groundwater conditions, Rock Quality Designation (RQD), and elastic longitudinal wave velocity of surrounding rock. The classification was performed using mathematical analytical methods based on entropy weight-extension matter-element theory and entropy weight-cloud model. The rationality and accuracy of these methods were verified using surrounding rock classification results from the design and construction stages of the Longnan Tunnel on the Ganzhou-Shenzhen high-speed railway currently under construction.
The results demonstrate that using the entropy weight method to calculate the weight coefficients of evaluation indices can effectively overcome subjectivity and avoid human interference in weight determination. These two surrounding rock classification methods represent a novel exploration in tunnel surrounding rock classification and are conducive to advancing the development of intelligent and information-based rock classification systems.
Keywords: tunnel engineering; surrounding rock classification; entropy weight method; extension matter-element theory; cloud model