首页> 外文期刊>Journal of Mines, Metals & Fuels >Development of a new methodology for evaluation of spontaneous fire risk potential and rating of underground coal mine panels in bord and pillar method of mining in India
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Development of a new methodology for evaluation of spontaneous fire risk potential and rating of underground coal mine panels in bord and pillar method of mining in India

机译:开发一种新的方法,用于评估自然采掘风险,并以印度的“柱头法”和“柱头法”对地下煤矿板进行评级

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This is an innovative user-fhendly prediction model developed for evaluation of spontaneous fire risk potential and rating of underground coal mine panels in bord and pillar workings. It is based on qualitative effect of fire risk parameters on underground panels, and to some extent dependent on experience of the user. Here, major fire risk parameters associated with spontaneous heating of panels are short-listed and divided into three broad groups in accordance with the nature of their contribution. The paper describes vividly the procedure for estimation of fire risk rating of individual groups using separate objective type models developed for this purpose and then it evaluates the overall fire risk potential and rating of the concerned panel by combining the fire risk ratings of all the three groups. This model may be applied to a panel where extraction is carried out using any of the techniques: (i) depillaring with formation of small pillars as final operation, (ii) extraction by broadening of galleries, (iii) depillaring with hydraulic sand stowing, and (iv) depillaring with caving. The model is tested with the field data collected from different collieries spreading across the country and the laboratory data for critical assessment of fitness. Some results showing the validity of the model are also cited here.
机译:这是一种创新的用户综合预测模型,用于评估自发火灾风险以及对博尔德和支柱工作中的地下煤矿面板的评级。它基于火灾风险参数对地下面板的定性影响,并在一定程度上取决于用户的经验。在这里,与面板自热相关的主要火灾风险参数被短名单,并根据其贡献的性质分为三大类。本文生动地描述了使用为此目的开发的独立目标类型模型估算各个组的火灾风险等级的程序,然后通过结合所有三个组的火灾风险等级来评估相关小组的总体火灾风险潜力和等级。该模型可以应用于采用以下任何一种技术进行提取的面板:(i)在最终操作中以形成小支柱的方式脱毛,(ii)通过加宽画廊的提取,(iii)用水力沙堆进行脱毛, (iv)崩塌脱毛。该模型使用从遍布全国的不同煤矿收集的现场数据和用于适应性关键评估的实验室数据进行测试。这里还引用了一些显示模型有效性的结果。

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