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    A physics-informed deep learning approach for combined cycle fatigue life prediction

    New search for: Feng, Chao
    New search for: Long, Zhiping
    New search for: Su, Molin
    New search for: Xu, Lianyong
    New search for: Zhao, Lei
    New search for: Han, Yongdian

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    A physics-informed deep learning approach for combined cycle fatigue life prediction

    New search for: Feng, Chao
    New search for: Long, Zhiping
    New search for: Su, Molin
    New search for: Xu, Lianyong
    New search for: Zhao, Lei
    New search for: Han, Yongdian

    Access

    Check access
    Check availability in my library
    Order at Subito €

    A physics-informed deep learning approach for combined cycle fatigue life prediction

    New search for: Feng, Chao
    New search for: Long, Zhiping
    New search for: Su, Molin
    New search for: Xu, Lianyong
    New search for: Zhao, Lei
    New search for: Han, Yongdian

    Access

    Check access
    Check availability in my library
    Order at Subito €

    Access

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    Check availability in my library
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    Document information
    Title:

    A physics-informed deep learning approach for combined cycle fatigue life prediction

    Additional title:

    Journal of Constructional Steel Research

    Contributors:

    Feng, Chao (author) / Long, Zhiping (author) / Su, Molin (author) / Xu, Lianyong (author) / Zhao, Lei (author) / Han, Yongdian (author)

    Published in:

    Journal of Constructional Steel Research ; 222 ; 109000

    Publication date:

    2024-11-01

    ISSN:

    0143-974X

    DOI:

    https://doi.org/10.1016/j.jcsr.2024.109000

    Type of media:

    Article (Journal)

    Type of material:

    Electronic Resource

    Language:

    English

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