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主办单位:煤炭科学研究总院有限公司、中国煤炭学会学术期刊工作委员会
采空区CO涌出量预测模型
  • Title

    Prediction model of CO emission volume from goaf

  • 作者

    齐庆杰赵尤信李兴华周新华

  • Author

    QI Qingjie,ZHAO Youxin,LI Xinghua,ZHOU Xinhua

  • 单位

    辽宁工程技术大学安全科学与工程学院矿山热动力灾害与防治教育部重点实验室

  • Organization
    1.School of Safety Science and Engineering,Liaoning Technical University,Fuxin ,China;2.MOE Key Lab of Mine Thermodynamic Disasters and Prevention,Fuxin ,China
  • 摘要
    为研究综放工作面CO涌出规律,以指导工作面通风及解决采空区自燃防治问题,以瑞安煤矿1煤层首采层014N1-1综放工作面为原型,采用COMSOL Multiphysics 5.0建立采空区CO涌出量模型,并开展正交试验设计及数值模拟计算。然后,采用SPSS软件对模拟结果进行逐步回归,建立了CO涌出量关于CO源项强度、CH4源项强度、CO反应速率、推进速度、风速等5个因素的回归模型,并采用现场实测数据对其进行修正。结果表明:CO涌出量与5个因素间均有极显著相关性,修正后的CO涌出量预测结果与现场实测数据吻合度较高,可以采用该模型进行采空区CO涌出预测,有利于指导矿井通风、防灭火的现场实践工作。
  • Abstract
    In order to study the CO emission law of the fully-mechanized coal mining face,to guide the ventilation of the coal mining face and to solve the spontaneous combustion prevention and control of the goaf,based on No. 014N1-1 fully-mechanized top coal caving mining face in the first mining seam-No. 1 seam of Rui’an Mine as a prototype,COMSOL Multiphysics 5.0 was applied to establish a CO numerical model of the goaf. And an orthogonal experimental design and a numerical simulation calculation were conducted. Then the SPSS software was applied to the stepwise regression of the simulation results. A regression model of the CO emission volume with five factors of the CO sources intensity,CH4 source intensity,CO reaction velocity,pushing forward speed and air velocity and the site measured data were applied to correct the CO emission. The results showed that,there was an ultra obvious correlation between the CO emission volume and the five factors. The predicted results of the corrected CO emission volume could have a high fitting with the site measured data. The model could be applied to predict the CO emission from the goaf and favorable to guide the site practice work of the mine ventilation and the fire prevention and control.
  • 关键词

    采空区CO涌出量预测模型矿井通风

  • KeyWords

    goaf; CO emission volume; prediction model; mine ventilation

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主办单位:煤炭科学研究总院有限公司 中国煤炭学会学术期刊工作委员会

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