Dynamic Escape Path Optimization Model Study Based on Spatio-Temporal Evolution of Coal Mine Water Inrush

To reduce the risk of coal mine water inrush, a dynamic escape path optimization model based on the spatio-temporal evolution of the water inrush is studied. The actual coal mine is simplified into roadway nodes and segments to meet the real-time simulation of the coal mine water inrush, where the computational cost is reduced significantly while the accuracy is acceptable. To solve the control equations of the open channel flow and full channel flow efficiently, the lattice Boltzmann method is adopted to simulate the spatio-temporal evolution of the water inrush. Different from the previous studies, the spatio-temporal evolution of the water inrush is taken into account, which is closer to the actual case. The escape speed is not static, which is affected by the water depth dynamically; meanwhile, the effect of the physical energy reduction is considered. To validate the dynamic escape path optimization model based on the spatio-temporal evolution of the coal mine water inrush, three case studies are conducted. In the first case, there is one water inrush point and one person, while in the second case, there are two water inrush points and four persons; the third case is an actual coal mine with multiple water inrush points. We defined two indicators to evaluate the risk of the escape path quantitatively; they are the window escape time and rescue priority. By conducting the dynamic programming of the escape path, the optimal escape path is selected, where the effectiveness of the dynamic escape path optimization model is validated. The present work is helpful in reducing the risk of coal mine water inrush and improving the safety of the early warning system.

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Publication Details

Journal
Processes
Published
2025-11-12
DOI
https://doi.org/10.3390/pr13113666
Primary Topic
Rock Mechanics and Modeling
Type
article
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article

Dynamic Escape Path Optimization Model Study Based on Spatio-Temporal Evolution of Coal Mine Water Inrush

Zaibing Liu, Junjie Hu, Shaolong Wang, Wenming Liu et al.
Processes
Rock Mechanics and Modeling
article

Dynamic Escape Path Optimization Model Study Based on Spatio-Temporal Evolution of Coal Mine Water Inrush

Zaibing Liu, Junjie Hu, Shaolong Wang, Wenming Liu, Weiming Chen, Lin An, Xinmiao Wang, Tao Fan, Liang Ma
article en

Abstract

To reduce the risk of coal mine water inrush, a dynamic escape path optimization model based on the spatio-temporal evolution of the water inrush is studied. The actual coal mine is simplified into roadway nodes and segments to meet the real-time simulation of the coal mine water inrush, where the computational cost is reduced significantly while the accuracy is acceptable. To solve the control equations of the open channel flow and full channel flow efficiently, the lattice Boltzmann method is adopted to simulate the spatio-temporal evolution of the water inrush. Different from the previous studies, the spatio-temporal evolution of the water inrush is taken into account, which is closer to the actual case. The escape speed is not static, which is affected by the water depth dynamically; meanwhile, the effect of the physical energy reduction is considered. To validate the dynamic escape path optimization model based on the spatio-temporal evolution of the coal mine water inrush, three case studies are conducted. In the first case, there is one water inrush point and one person, while in the second case, there are two water inrush points and four persons; the third case is an actual coal mine with multiple water inrush points. We defined two indicators to evaluate the risk of the escape path quantitatively; they are the window escape time and rescue priority. By conducting the dynamic programming of the escape path, the optimal escape path is selected, where the effectiveness of the dynamic escape path optimization model is validated. The present work is helpful in reducing the risk of coal mine water inrush and improving the safety of the early warning system.

ProcessesVol. 13(11)
China University of Geosciences (CN), Shaanxi Coal Chemical Industry Technology Research Institute (CN), China Coal Research Institute (China) (CN)
Openalex Percentile: Top 61%
Rock Mechanics and Modeling
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