Abstract
The spatial and temporal distribution of tunnel failure is very complex due to geologic heterogeneity and variability in both mining processes and tunnel arrangement in deep metal mines. In this paper, the quantitative risk assessment for deep tunnel failure was performed using a normal cloud model at the Ashele copper mine, China. This was completed by considering the evaluation indexes of geological condition, mining process, and microseismic data. A weighted distribution of evaluation indexes was determined by implementation of an entropy weight method to reveal the primary parameters controlling tunnel failure. Additionally, the damage levels of the tunnel were quantitatively assigned by computing the degree of membership that different damage levels had, based on the expectation normalization method. The methods of maximum membership principle, comprehensive evaluation value, and fuzzy entropy were considered to determine the tunnel damage levels and risk of occurrence. The application of this method at the Ashele copper mine demonstrates that it meets the requirement of risk assessment for deep tunnel failure and can provide a basis for large-scale regional tunnel failure control in deep metal mines.
Highlights
At the current rate of mine expansion, more than 30% of the metal mines in China will enter into the deep mining category by the end of 2025
The evaluation index system is the foundation of risk assessment for tunnel failure
If the two results were inconsistent, the evaluation threshold T of the fuzzy entropy was determined by comparing the actual damage level and the result obtained from the maximum membership rule
Summary
At the current rate of mine expansion, more than 30% of the metal mines in China will enter into the deep mining category (i.e., a mining depth greater than 1000 m) by the end of 2025. Under high ground stress conditions in deep metal mines, frequent and strong blast disturbances can lead to the spalling and collapse of the rock surrounding tunnels. To better assess the risk of the tunnel failure in deep metal mines, it is necessary to consider a variety of parameters and utilize a mathematical method that can evaluate both the probability and uncertainty of rock mass failure. Three different evaluation indicators are considered in the risk assessment of deep tunnel failure (geological conditions, mining disturbances, and MS parameters). Sci. 2021, 11, 5208 by using the entropy weight method, the normal cloud model theory was applied to evaluate the rock mass failure risk at the Ashele copper mine
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