娄高中, 郭文兵, 高金龙. 基于量纲分析的非充分采动导水裂缝带高度预测[J]. 煤田地质与勘探, 2019, 47(3): 147-153. DOI: 10.3969/j.issn.1001-1986.2019.03.023
引用本文: 娄高中, 郭文兵, 高金龙. 基于量纲分析的非充分采动导水裂缝带高度预测[J]. 煤田地质与勘探, 2019, 47(3): 147-153. DOI: 10.3969/j.issn.1001-1986.2019.03.023
LOU Gaozhong, GUO Wenbing, GAO Jinlong. Prediction of the height of water flowing fractured zone under subcritical mining based on dimensional analysis[J]. COAL GEOLOGY & EXPLORATION, 2019, 47(3): 147-153. DOI: 10.3969/j.issn.1001-1986.2019.03.023
Citation: LOU Gaozhong, GUO Wenbing, GAO Jinlong. Prediction of the height of water flowing fractured zone under subcritical mining based on dimensional analysis[J]. COAL GEOLOGY & EXPLORATION, 2019, 47(3): 147-153. DOI: 10.3969/j.issn.1001-1986.2019.03.023

基于量纲分析的非充分采动导水裂缝带高度预测

Prediction of the height of water flowing fractured zone under subcritical mining based on dimensional analysis

  • 摘要: 为准确预测非充分采动导水裂缝带高度,选取开采厚度M、煤层埋深H、工作面倾斜长度L、煤层倾角α、覆岩力学性质R、覆岩结构特征S为非充分采动导水裂缝带高度主要影响因素。采用量纲分析建立了导水裂缝带高度与M,H,L,α,S间的无量纲关系式。结合30组实测数据,采用多元回归得到无量纲关系式的最优函数关系式。选取2个非充分采动工作面导水裂缝带现场实例对预测模型进行了工程验证,预测模型预测结果与实测结果吻合良好,其相对误差分别为3.64%和2.93%,预测模型的预测精度可以满足煤矿安全生产现场需要。

     

    Abstract: In order to accurately predict the height of water flowing fractured zone under subcritical mining, mining thickness M, mining depth H, inclined length of working face L, dip angle of coal seam α, overburden mechanical properties R, overburden structure characteristics S were selected as the main influencing factors on the height of water flowing fractured zone under subcritical mining. Dimensionless relations between the height of water flowing fractured zone and M, H, L, α, S were established by dimensional analysis. Based on 30 sets of measured data, the optimal function relation of dimensionless relation was obtained by multiple regression. The prediction model is validated with field examples from two subcritical working faces, the prediction values are in good agreement with the measured values, and the relative errors are 3.64% and 2.93% respectively, the prediction accuracy of the prediction model can meet the field requirements of safe production in coal mine.

     

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