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Reduced-order modelling of a bluff body turbulent wake flow field using hierarchical convolutional neural network autoencoder
更新时间：2025-05-26

    • Reduced-order modelling of a bluff body turbulent wake flow field using hierarchical convolutional neural network autoencoder

    • “According to a report by a technology media reporter, researchers used a nonlinear layered convolutional autoencoder to perform a reduced order analysis on the turbulent wake flow of a three-dimensional cylindrical blunt body, and found that it has stronger restoration ability at low layers and latent vector numbers.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 54, Issue 4, Pages: 874-882(2024)
    • 作者机构：

      1.同济大学 汽车学院，上海 201804

      2.同济大学 上海地面交通工具风洞中心，上海 201804

      3.同济大学 铁道与城市轨道交通研究院，上海 201804

      4.北京民用飞机技术研究中心，北京 102211

    • DOI：10.13229/j.cnki.jdxbgxb.20220611    

      CLC： U462

    • Received：19 May 2022，

      Published：01 April 2024

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  • XIA Chao,WANG Meng-jia,Zhu Jian-yue,et al.Reduced-order modelling of a bluff body turbulent wake flow field using hierarchical convolutional neural network autoencoder[J].Journal of Jilin University(Engineering and Technology Edition),2024,54(04):874-882. DOI： 10.13229/j.cnki.jdxbgxb.20220611.

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