首页|Algorithm for cavity flow in a new-born goaf and experimental verification

Algorithm for cavity flow in a new-born goaf and experimental verification

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Prevention and control measures of spontaneous combustion of coal and gas accumulation in a goaf require an accurate description of its gas flow state.However,the commonly used fluid dynamics in por-ous media is not suitable for the new-born goaf with fracture cavity combination,multi-scale,and large blocks.In this study,we propose a cavity flow algorithm to accurately describe the gas flow state in the new-born goaf.The genetic algorithm(GA)is used to randomly generate the binary matrix of a goaf cav-ing shape.The difference between the gas flow state calculated by the lattice Boltzmann method(LBM)and the measured data at the boundary or internal measuring points of the real goaf is taken as the GA fitness value,and the real goaf caving shape and the gas flow state are quickly addressed by GA.The experimental model of new-born goaf is established,and the laser Doppler anemometry(LDA)experi-ment is carried out.The results show that the Jaccard similarity coefficient between the reconstructed caving shape and the real caving shape is 0.7473,the mean square error between the calculated wind speed and the LDA-measured value is 0.0244,and the R2 coefficient is 0.8986,which verify the feasibility of the algorithm.

Cavity flowLattice Boltzmann methodLaser Doppler anemometryNew-born goafGenetic algorithm

Jian Liu、Qichao Zhou、Dong Wang、Lijun Deng、Ke Gao

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College of Safety Science&Engineering,Liaoning Technical University,Huludao 125105,China

Key Laboratory of Mine Thermo-motive Disaster&Prevention,Ministry of Education,Huludao 125105,China

Natural Science Foundation of ChinaNatural Science Foundation of ChinaNational Key Research and Development Program of China

51774169515741422017YFC0804401

2023

矿业科学技术学报(英文版)
中国矿业大学

矿业科学技术学报(英文版)

CSTPCDCSCD北大核心EI
影响因子：1.222
ISSN：2095-2686
年,卷(期)：2023.33(3)
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