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首页> 外文期刊>Advances in civil engineering >Space-Time Distribution Laws of Tunnel Excavation Damaged Zones (EDZs) in Deep Mines and EDZ Prediction Modeling by Random Forest Regression
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Space-Time Distribution Laws of Tunnel Excavation Damaged Zones (EDZs) in Deep Mines and EDZ Prediction Modeling by Random Forest Regression

机译:随机森林回归中,隧道挖掘隧道挖掘损坏区(EDZS)的时空分布规律

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摘要

The formation process of EDZs (excavation damaged zones) in the roadways of deep underground mines is complex, and this process is affected by blasting disturbances, engineering excavation unloading, and adjustment of field stress. The range of an excavation damaged zone (EDZ) changes as the time and space change. These changes bring more difficulties in analyzing the stability of the surrounding rock in deep engineering and determining a reasonable support scheme. In a layered rock mass, the distribution of EDZs is more difficult to identify. In this study, an ultrasonic velocity detector in the surrounding rock was used to monitor the range of EDZs in a deep roadway which was buried in a layered rock mass with a dip angle of 20-30 degrees. The space-time distribution laws of the range of EDZs during the excavation process of the roadway were analyzed. The monitoring results showed that the formation of an EDZ can be divided into the following stages: (1) the EDZ forms immediately after the roadway excavation, which accounts for approximately 82%-95% of all EDZs. The main factors that affect the EDZ are the blasting load, the excavation unloading, and the stress adjustment; (2) as the roadway excavation continues, the range of the EDZs increases because of the blasting excavation and stress adjustment; (3) the later excavation zone has a comparatively larger EDZ value; and (4) an asymmetric supporting technology is necessary to ensure the stability of roadways buried in layered rocks. Additionally, the predictive capability of random forest modeling is evaluated for estimating the EDZ. The root-mean-square error (RMSE) and mean absolute error (MAE) are used as reliable indicators to validate the model. The results indicate that the random forest model has good prediction capability (RMSE=0.1613 and MAE=0.1402).
机译:埃兹斯(挖掘损坏区)在深层地区的道路上的形成过程很复杂,这一过程受到爆破干扰,工程挖掘卸载和场压调整的影响。挖掘损坏区域(EDZ)的范围随着时间和空间的变化而变化。这些变化带来了更多困难,在深入工程中分析周围岩石的稳定性并确定合理的支持方案。在层状岩石质量中,EDZ的分布更难以识别。在这项研究中,在周围的岩石的超声波速度检测器来监测EDZs的范围中被埋没在层状岩体的20-30度的倾角深巷道。分析了道路挖掘过程中EDZ系列的时空分布规律。监测结果表明,EDZ的形成可分为以下阶段:(1)EDZ在道路挖掘后立即形成,占所有EDZ的约82%-95%。影响EDZ的主要因素是爆破载荷,挖掘卸载和应力调节; (2)随着巷道挖掘的继续,由于爆破挖掘和应力调节,EDZ的范围增加; (3)后来的挖掘区具有相对较大的EDZ值; (4)不对称的支持技术是必要的,以确保埋在层状岩石中的道路稳定性。另外,评估随机林建模的预测能力以估计EDZ。根均方误差(RMSE)和平均绝对误差(MAE)被用作可靠的指标来验证模型。结果表明,在随机森林模型具有良好的预测能力(RMSE = 0.1613和MAE = 0.1402)。

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  • 来源
    《Advances in civil engineering》 |2019年第8期|6505984.1-6505984.13|共13页
  • 作者

    Xie Qiang; Peng Kang;

  • 作者单位

    Cent S Univ Sch Civil Engn Changsha 410075 Hunan Peoples R China|Hunan City Univ Yiyang 413000 Peoples R China;

    Chongqing Univ State Key Lab Coal Mine Disaster Dynam & Control Chongqing 400044 Peoples R China|Chongqing Univ Coll Resources & Environm Sci Chongqing 400044 Peoples R China;

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