Numerical assessment of the water-flow hazard to workers in the water disaster of underground mine

Abstract

Understanding the details of the water-flow hazard (WH) to workers in water disasters is extremely important in disaster-risk management. This paper aims to develop a numerical assessment model for the WH affecting worker safety. An assessment model of WH is proposed for water disasters in the underground mine, which includes two characteristics: (a) from water-disaster environment to WH of workers and (b) from multiple influencing factors to quantitative comprehensive quantification. To verify the feasibility of WH, it is applied to a water disaster in an underground coal mine. The simulation results highlight that the WH model can assess the hazard value of worker-1 (m = 72 kg, H = 1.72 m) at paragraph – 6134 and paragraph – 8840 of roadway, with different water-flow conditions, in the whole time of the disaster. Meanwhile, the differences between WH for three workers, worker-1, worker-2 (m = 95 kg, H = 1.82 m), and worker-3 (m = 60 kg, H = 1.62 m), under the same flow conditions are provided by the curve. Moreover, dynamic visualization of WH is achieved, which shows how the hazard of worker-1 changes into the time of 2, 5, 11, 19, and 27 h after a disaster in the full mine. Therefore, this numerical assessment can be used to evaluate the hazards posed by water flow to workers, which meets the urgent demands of water-disaster management for underground mines.

Trends in forecasting groundwater ingresses into underground structures

“…It is recognized that efficiency and success of underground engineering projects rely on the accurate forecast of groundwater inflows. 7,[29][30][31][32] Regarding analytical solutions, Peng et al 25 explained in detail the key factors that need to be carefully considered to reasonably improve the accuracy of predicting groundwater ingresses in the excavated areas of underground structures. While numerical solutions, applied artificial intelligence that involves machine learning-based solutions, as well as other solutions require enormous data to provide reasonable results.…”