首页> 外文期刊>Engineering with Computers >A novel probabilistic simulation approach for forecasting the safety factor of slopes: a case study
【24h】

A novel probabilistic simulation approach for forecasting the safety factor of slopes: a case study

机译:一种预测边坡安全系数的新型概率模拟方法:一个案例研究

获取原文
获取原文并翻译 | 示例

摘要

Stabilization of slopes is considered as the aim of the several geotechnical applications such as embankment, tunnel, highway, building and railway and dam. Therefore, evaluation and precise prediction of the factor of safety (FoS) of slopes can be useful in designing these important structures. This research is carried out to evaluate the ability of Monte Carlo (MC) technique for the forecasting the FoS of many homogenous slopes in the static condition. Moreover, the sensitivity of the FoS on the effective parameters was identified. To do this, the most important factors on FoS, such as angle of internal friction (empty set), slope angle () and cohesion (C) were investigated and used as the inputs to forecast the FoS. Then, a regression analysis was performed, and the results were used for the FoS prediction using MC. The obtained results of MC simulation were very close with the actual FoS values. The mean of the simulated FoS by MC was achieved as 1.32, while, according to actual FoSs, it was 1.27. These results showed that MC is an acceptable technique to estimate the FoS of slopes with high level of accuracy. Moreover, based on the results of correlation and regression sensitivity analyses, it was concluded that angle of internal friction, was the most influential one on the results of FoS in both types of sensitivity analyses.
机译:斜坡的稳定被认为是诸如路堤,隧道,公路,建筑,铁路和大坝等多种岩土工程应用的目标。因此,对斜坡安全系数(FoS)的评估和精确预测在设计这些重要结构时可能很有用。进行这项研究以评估蒙特卡洛(MC)技术在静态条件下预测许多均匀斜坡的FoS的能力。此外,还确定了FoS对有效参数的敏感性。为此,调查了影响FoS的最重要因素,例如内摩擦角(空集),倾斜角()和内聚力(C),并将其用作预测FoS的输入。然后,进行回归分析,并将结果用于使用MC的FoS预测。 MC仿真获得的结果与实际FoS值非常接近。 MC得出的模拟FoS的平均值为1.32,而根据实际FoS的平均值为1.27。这些结果表明,MC是用于以高准确度估算斜坡的FoS的可接受技术。此外,根据相关性和回归灵敏度分析的结果,可以得出结论,在两种类型的灵敏度分析中,内摩擦角对FoS结果影响最大。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号