...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Tunnelling and underground space technology >Prediction of time-dependent tunnel convergences using a Bayesian updating approach
【24h】

Prediction of time-dependent tunnel convergences using a Bayesian updating approach

机译：使用贝叶斯更新方法预测时变隧道收敛

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

Convergences caused by tunnel excavation may increase with time. The prediction of these time-dependent convergences is important for the safe design and construction of tunnels. This study proposes a Bayesian approach to improve time-dependent convergence predictions, updating them with new information provided by successive convergence measurements. The proposed approach can consider various sources of uncertainties such as model uncertainty, model parameters uncertainty and measurement uncertainty. Three real tunnel projects-the Frejus road tunnel, the Babolak water conveyance tunnel, and the GCS drift of the Underground Research Laboratory (URL) of the French National Radioactive Waste Management Agency (Andra)-are used to demonstrate the applicability and performance of the proposed approach. Results show that the accuracy of predictions is improved, and that their uncertainty is reduced, after the measured convergences are employed to update prior predictions; and results also show that such predictive improvements due to the updating become more significant as the measurement accuracy increases.
机译：隧道开挖引起的收敛性可能会随着时间而增加。这些时间相关收敛的预测对于隧道的安全设计和施工很重要。这项研究提出了一种贝叶斯方法来改进与时间有关的收敛预测，并用连续收敛测量提供的新信息更新它们。所提出的方法可以考虑各种不确定性来源，例如模型不确定性，模型参数不确定性和测量不确定性。三个真实的隧道项目-弗雷瑞斯公路隧道，巴博拉克输水隧道和法国国家放射性废物管理署（Andra）地下研究实验室（URL）的GCS漂移-用于证明该隧道的适用性和性能建议的方法。结果表明，在使用测得的收敛性来更新先前的预测之后，预测的准确性得以提高，不确定性降低。结果还表明，随着测量精度的提高，这种更新带来的预测性改进变得更加重要。

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