Redefinition and identification of critical pillars in goaf based on the risk analysis of pillar instability
The large-scale collapse of goaf is one of the typical disasters in underground mines.This disaster is primarily triggered by the instability of the critical key pillar within the goaf.In this paper,to accurately identify the critical pillar in the goaf,the fundamental concept of the critical pillar in goaf is developed based on the cascading failure mechanism of pillar group in goaf and the principles of risk theory.Additionally,a novel method for recognizing the critical pillar is proposed based on a comprehensive risk analysis of pillar instability.The methodology involves several key steps:(1)obtaining the distribution characteristics of pillar strength through field research or empirical estimations,and then establishing the probability density function for pillar strength within the goaf;(2)computing the stress on each pillar by introducing the formula of maximum stress diffusion distance,subsequently,calculating the instability probability for each pillar;(3)utilizing a dynamic updating iterative approach to assess the stress transfer and instability patterns within the pillar group system,considering any pillar as the initial failure point;(4)quantitatively characterizing the consequence of any single pillar instability by using the index of the bearing area loss rate of the pillar group within the goaf,specifically measuring the severity of goaf collapse disasters induced by individual pillar instability;(5)determining the instability risk value for each pillar by calculating the product of the instability probability and its associated consequence.Accordingly,identifying the critical pillar within the goaf as the one with the highest instability risk value.The proposed method is applied to Fetr6 mining area for verification.The results demonstrate that this method is easy to implement,involving straightforward parameter acquisition and calculation processes,while also offering clear physical significance.Furthermore,it proves to be more scientifically and logically sound than the traditional safety factor method.Thus,this method holds promise for wide-ranging applications in practical engineering scenarios.