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  • 标题:Modelling vortex-induced loads using Recurrent Neural Networks ⁎
  • 本地全文:下载
  • 作者:Joshua A. Foster ; Tim De Troyer ; Mark C. Runacres
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:20
  • 页码:32-37
  • DOI:10.1016/j.ifacol.2021.11.149
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this work recurrent neural networks of the LSTM type are used to describe unsteady fluid loading. Indirect load measurements are especially useful for structural health monitoring applications. Relying on discrete spatiotemporal measurements of the velocity field, both the forces and the corresponding displacement of a cylinder subjected to vortex shedding are modelled.
  • 关键词:KeywordsMachine learningLong Short-Term Memory Recurrent Neural Networksunsteady fluid dynamicsvortex-induced vibrations
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