岩土力学 ›› 2024, Vol. 45 ›› Issue (2): 577-587.doi: 10.16285/j.rsm.2023.0287

• 岩土工程研究 • 上一篇    下一篇

深部开采地表移动延续时间预测模型及其参数分析

张亮亮1,程桦1, 2,姚直书1,王晓健1   

  1. 1. 安徽理工大学 土木建筑学院,安徽 淮南 232001;2. 安徽大学 资源与环境工程学院,安徽 合肥 230022
  • 收稿日期:2023-03-07 接受日期:2023-04-19 出版日期:2024-02-11 发布日期:2024-02-07
  • 作者简介:张亮亮,男,1992年生,博士,讲师,主要从事煤层开采地表沉陷方面的研究。zllaust@163.com
  • 基金资助:
    安徽省高校科研资助项目(No. 2023AH051203);安徽理工大学高层次引进人才科研启动基金(No. 2022yjrc32);国家自然科学基金 (No. 51874005)。

Prediction model and parameter analysis of surface movement duration in deep coal mining

ZHANG Liang-liang1, CHENG Hua1, 2, YAO Zhi-shu1, WANG Xiao-jian1   

  1. 1. School of Civil Engineering and Architecture, Anhui University of Science and Technology, Huainan, Anhui 232001,China; 2. School of Resources and Environmental Engineering, Anhui University, Hefei, Anhui 230022, China
  • Received:2023-03-07 Accepted:2023-04-19 Online:2024-02-11 Published:2024-02-07
  • Supported by:
    This work was supported by the Natural Science Research Project of Anhui Educational Committee (2023AH051203), the Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology (2022yjrc32) and the National Natural Science Foundation of China (51874005).

摘要: 基于改进Knothe时间模型,根据地表移动延续时间定义,建立能够综合考虑采高、平均采深、松散层厚度、基岩层厚度和开采速度等因素的深部开采地表移动延续时间理论预测模型,并根据概率积分法给出了模型参数确定方法。采用24个深部工作面开采地表移动延续时间监测数据对预测模型的合理性和精确性进行验证。结果表明:地表移动延续时间模型预测结果与24个工作面监测结果基本吻合,两者平均绝对误差仅38 d,均方根误差仅为47 d,平均绝对误差百分比仅为9%,远小于现有3种经验模型的预测误差,验证了地表移动延续时间预测模型的精确性;地表移动延续时间受采高、平均采深、松散层厚度、基岩层厚度和开采速度的影响,随采高的增加而非线性增加,随平均采深、松散层厚度、基岩层厚度的增加而线性增加,但随开采速度的增加而非线性减小。该研究可为深部开采地表移动变形稳定性评估和科学制定开采计划提供理论指导。

关键词: 地表移动延续时间, 改进Knothe时间模型, 预测, 动态沉降, 开采速度

Abstract: This paper presents a theoretical prediction model for the surface movement duration in coal mining, which takes into account various factors such as coal seam mining height, average mining depth, loose layer thickness, bedrock layer thickness, and mining speed. The model is based on the improved Knothe time model and incorporates the definition of surface movement duration. Additionally, a method for determining the model parameters using the probability integration method is provided. To validate the rationality and accuracy of the prediction model, monitoring data from 24 deep working faces are utilized. The results demonstrate that the predicted surface movement duration aligns well with the monitoring results from the working faces. The mean absolute error is only 38 days, the root mean square error is only 47 days, and the mean absolute percentage error is only 9%. These values indicate a significantly lower prediction error compared to existing empirical models. The accuracy of the surface movement duration prediction model is confirmed. The study further reveals that the duration is influenced by coal seam mining height, average mining depth, loose layer thickness, bedrock layer thickness, and mining speed. Specifically, it increases nonlinearly with coal seam mining height, linearly with average mining depth, loose layer thickness, and bedrock layer thickness, but decreases nonlinearly with mining speed. This research provides theoretical guidance for evaluating the stability of surface movement and deformation in coal mining and formulating scientifically sound mining plans.

Key words: surface movement duration, improved Knothe time model, prediction, dynamic subsidence, mining speed

中图分类号: TD 821
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