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

作　　者：Jian Liu Qichao Zhou Dong Wang Lijun Deng Ke Gao 

机构地区：[1]College of Safety Science&Engineering,Liaoning Technical University,Huludao 125105,China [2]Key Laboratory of Mine Thermo-motive Disaster&Prevention,Ministry of Education,Huludao 125105,China

出　　处：《International Journal of Mining Science and Technology》2023年第3期351-361,共11页矿业科学技术学报（英文版）

基　　金：This work was supported by the Natural Science Foundation of China(Nos.51774169 and 51574142);the National Key Research and Development Program of China(No.2017YFC0804401).

摘　　要：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 porous 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 caving 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)experiment 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.

关 键 词：Cavity flow Lattice Boltzmann method Laser Doppler anemometry New-born goaf Genetic algorithm 

分 类 号：TD752.2[矿业工程—矿井通风与安全] TD712