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Extraction of Irregularly Shaped Coal Mining Area Induced Ground Subsidence Prediction Based on Probability Integral Method

机译:基于概率积分法的不规则形状煤挖掘地面沉降预测的提取

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Underground coal mining-induced ground subsidence (or major ground vertical settlement) is a major concern to the mining industry, government and people affected. Based on the probability integral method, this paper presents a new ground subsidence prediction method for predicting irregularly shaped coal mining area extraction-induced ground subsidence. Firstly, the Delaunay triangulation method is used to divide the irregularly shaped mining area into a series of triangular extraction elements. Then, the extraction elements within the calculation area are selected. Finally, the Monte Carlo method is used to calculate extraction element-induced ground subsidence. The proposed method was tested by two experimental data sets: the simulation data set and direct leveling-based subsidence observations. The simulation results show that the prediction error of the proposed method is proportional to mesh size and inversely proportional to the amount of generated random points within the auxiliary domain. In addition, when the mesh size is smaller than 0.5 times the minimum deviation of the inflection point of the mining area, and the amount of random points within an auxiliary domain is greater than 800 times the area of the extraction element, the difference between the proposed method-based subsidence predictions and the traditional probability integral method-based subsidence predictions is marginal. The measurement results show that the root-mean-square error of the proposed method-based subsidence predictions is smaller than 3 cm, the average of absolute deviations of the proposed method-based subsidence predictions is 2.49 cm, and the maximum absolute deviation is 4.05 cm, which is equal to 0.75% of the maximum direct leveling-based subsidence observation.
机译:地下煤矿诱导地下沉降(或主要地面垂直解决)是矿业,政府和人民影响的主要问题。基于概率积分法,本文提出了一种新的地下沉降预测方法,用于预测不规则形状的煤矿区域提取诱导的地下沉降。首先,DELAUNay三角测量方法用于将不规则形状的挖掘区域划分为一系列三角形提取元件。然后,选择计算区域内的提取元件。最后,Monte Carlo方法用于计算提取元素诱导的地下沉降。所提出的方法由两个实验数据集进行测试:模拟数据集和基于直接的升级的沉降观测。仿真结果表明,所提出的方法的预测误差与网格尺寸成比例,并与辅助域内的产生随机点的量成反比。另外,当网格尺寸小于矿区拐点的最小偏差的0.5倍时,辅助域内的随机点的量大于提取元件区域的800倍,差异所提出的基于方法的沉降预测和传统的概率积分法的沉降预测是边缘的。测量结果表明,基于方法的沉降预测的根均方误差小于3cm,所提出的基于方法的沉降预测的绝对偏差的平均值为2.49cm,最大绝对偏差为4.05 CM,其等于最大直接平整的沉降观察的0.75%。

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