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  • 标题:Using Sigma-Points to Identify Optimal Experimental Design for Dike Monitoring ⁎
  • 本地全文:下载
  • 作者:Raoul Hölter ; Elham Mahmoudi ; Maria Datcheva
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:2
  • 页码:759-764
  • DOI:10.1016/j.ifacol.2018.04.005
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn geotechnical engineering, using monitored data for model validation is common practice. However, a model-based optimal experimental design for parameter identification is unusual when planning a monitoring set-up. As soils are subjected to large parameter uncertainties, model validation is of high interest to enable a precise prediction of the system behaviour. Due to the complexity of considered cases and employed FE-models, time-efficient solutions are of interest. For the case of a dike subjected to a rapid drawdown of the current water level, a Monte-Carlo based approach was previously employed. In the present study, it is intended to improve the efficiency by applying the so-called sigma-Points method that substitutes random sampling by defined characteristics of model response distribution to set-up a monitoring design that allows to identify the relevant system parameters.
  • 关键词:KeywordsParameter estimationUncertaintyFinite element analysisSensitivity analysisStochastic approximation
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