...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>International journal of geomechanics >Exploring Passive and Active Metamodeling-Based Reliability Analysis Methods for Soil Slopes: A New Approach to Active Training
【24h】

Exploring Passive and Active Metamodeling-Based Reliability Analysis Methods for Soil Slopes: A New Approach to Active Training

机译：探索基于被动和主动基于元模型的土质边坡可靠性分析方法：一种主动训练的新方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

For geotechnical systems involving complex behaviors and significant uncertainties, metamodeling-based reliability methods based on fixed designs of experiment (passive metamodeling methods) are frequently applied. However, because of the passive nature of these methods, they do not guarantee accurate probability estimates. This issue also persists in estimates obtained from active metamodeling methods (metamodeling methods that update the design of experiment iteratively) if a global stopping criterion or a nonoptimal learning function is used for the type of problem. This study highlights the importance of addressing these issues by investigating an example of failure analysis of soil slopes and concludes that the stopping criteria for development and refinement of metamodels need to be objective and locally defined with respect to the limit state function (LSF) and with a direct link to the accuracy of the reliability estimates. To address these challenges, this study established an effective sampling region that optimally ignores candidate design samples with weak probability densities. This enabled the development of an effective learning function that facilitates the active learning process. Moreover, an analytical upper bound for the error in failure probability estimation, proposed by the authors, was adopted here to arrive at a local and objective stopping criterion. This method was applied on two soil slopes, the stability of which was evaluated by the strength reduction method (SRM) in FLAC3D. The results highlight that passive and active methods with global stopping criteria cannot guarantee an accurate estimate of the failure probability. Furthermore, the developed method can considerably reduce the computational demands while achieving accurate estimates of failure probabilities of soil slopes.
机译：对于涉及复杂行为和重大不确定性的岩土系统，经常采用基于固定实验设计的基于元模型的可靠性方法（被动元模型方法）。但是，由于这些方法的被动性质，它们不能保证准确的概率估计。如果针对问题类型使用全局停止准则或非最优学习功能，则从主动元建模方法（迭代地更新实验设计的元建模方法）获得的估计值中也仍然存在此问题。这项研究通过调查一个土质边坡的破坏分析实例，强调了解决这些问题的重要性，并得出结论，关于极限模型和极限状态函数的建立和完善元模型的停止标准必须是客观和局部的。与可靠性估算的准确性直接相关。为了解决这些挑战，本研究建立了一个有效的采样区域，该区域最佳地忽略了概率密度较弱的候选设计样本。这样就可以开发有效的学习功能，从而促进主动学习过程。此外，本文采用了作者提出的失效概率估计误差的解析上限，以得出局部和客观的停车准则。该方法应用于两个土质边坡，其稳定性通过FLAC3D中的强度折减法（SRM）进行评估。结果表明，具有全局停止标准的被动和主动方法不能保证对故障概率的准确估计。此外，开发的方法可以大大减少计算需求，同时实现对土质边坡破坏概率的准确估计。

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