摘要
为研究综采工作面灾害气体的运移弥散规律,分析灾害气体运移过程中峰值体积分数及分布的影响因素,在综采工作面内开展示踪气体(SF_(6))现场试验,应用一维对流—弥散模型定量分析示踪气体运移特征,使用粒子群算法(PSO)对数学模型中的巷道平均风速和纵向弥散系数进行最优参数估计。结果表明:综采工作面监测到的示踪气体呈现偏态分布,随着运移距离的增加,示踪气体分布影响区域增大;影响监测点处的示踪气体浓度曲线峰值和波形的主要因素是平均风速,其次是纵向弥散系数。对比模拟与试验测试值可以看出,使用一维对流—弥散模型可以准确描述灾害气体在综采工作面内的弥散运移规律。
In order to study the migration and dispersion law of disaster gas in fully mechanized mining face and analyze the influencing factors of peak volume fraction and distribution of disaster gas during migration,using the method of field test of tracer gas(SF_6) in fully mechanized mining face,a one-dimensional convection-dispersion model was used to quantitatively analyze the migration characteristics of tracer gas.Particle swarm optimization(PSO) was used to estimate the average wind speed and longitudinal dispersion coefficient of roadway in the mathematical model.The results show that the tracer gas in fully mechanized mining face shows a skewed distribution,and the influence area of tracer gas distribution increases with the increase of migration distance.The main influencing factor of the peak value and waveform of the tracer gas concentration curve at the monitoring point is the average wind speed,followed by the longitudinal dispersion coefficient.By comparing the simulation and test values,it can be seen that the dispersion migration law of disaster gas in fully mechanized mining face can be accurately described by using one-dimensional convection-dispersion model.
作者
雷柏伟
王劲博
吴兵
党素娜
LEI Baiwei;WANG Jinbo;WU Bing;DANG Suna(School of Emergency Management and Safety Engineering,China University of Mining and Technology(Beijing),Beijing 100083,China;Key Laboratory for Precise Mining of Intergrown Energy and Resources,China University of Mining&Technology(Beijing),Beijing 100083,China)
出处
《矿业安全与环保》
CAS
北大核心
2023年第4期1-6,共6页
Mining Safety & Environmental Protection
基金
中央基本科研业务费项目(2022YQAQ09)。
关键词
综采工作面
示踪试验
对流弥散模型
粒子群算法
fully mechanized mining face
tracer test
convective dispersion model
particle swarm optimization
