用数值方法定量评价地下采煤能量变化

Chunchen Wei, Chengguo Zhang, Onur Vardar, John Watson, Ismet Canbulat
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引用次数: 2

摘要

煤爆是由采矿过程中过度应力的岩体/煤炭内能量的动态和不稳定释放引起的。虽然煤爆的发生是多种因素复杂影响的结果,但煤爆机制的一个主要组成部分与能量的储存和释放有关。这项研究回顾了可能导致煤爆的能量来源,主要是储存在挖掘周围煤块中的应变和势能,以及地质不连续性释放的辐射地震能。[1]提出的能量平衡概念被用于数值建模,以计算建模系统中的辐射地震能和给定爆破场景下喷出的岩石/煤的动能。模拟结果表明,随着开采深度的增加,采场周围的应变能密度(SED)增加,最大应变能密度区域向更深的煤层迁移。考虑到地质特征对巷道和长壁工作面的影响,可以考虑所提出的能量项来评估煤的爆裂风险倾向性。根据挖掘中能量变化的结果,模型预测,对于喷射深度2​m和3​m爆破的动能随着开采深度从100增加而增加​m至1000​m、 但对于喷射深度1​m只会增加,直到开采深度达到700​m,然后减小。所提出的基于能源的模型指标可以加深对不同开采条件下能源变化和相关煤爆风险的理解。
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Quantitative assessment of energy changes in underground coal excavations using numerical approach

Coal burst is caused by a dynamic and unstable release of energy within the overstressed rock mass/coal during the mining process. Although the occurrence of coal burst is a result of the complex impacts of many factors, a major component of coal burst mechanism is associated with energy storage and release. This study reviewed the sources of energy that can contribute to a coal burst, principally strain and potential energy stored in the coal mass around excavations, and radiated seismic energy released by geological discontinuities. The energy balance concept proposed by [1] was utilised in numerical modellings to compute the radiated seismic energy in a modelling system and the kinetic energy of ejected rock/coal for a given burst scenario. The modelling results showed that the strain energy density (SED) around excavations increases with increasing mining depth and the maximum SED area migrates deeper into the coal. For the effect of geological features on both roadway and longwall face, the coal burst risk proneness can be assessed considering the proposed energy terms. According to the results of energy changes in excavations, the modelling predicts that for depths of ejection 2 ​m and 3 ​m the kinetic energy of a burst increases as the mining depth increases from 100 ​m to 1000 ​m, but for depth of ejection 1 ​m only increases until mining depth reaches 700 ​m and then decreases. The proposed energy-based model indicators can deepen the understanding of energy changes and the associated coal burst risks for different mining conditions.

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