Abstract To effectively realize the reliability design of engineering structural system, a generative adversarial surrogate modeling (GASM) concept is proposed by innovating generative adversarial theory into surrogate modeling methods, which realize the aerospace engineering structural system reliability design adversarial modeling. In this concept, the surrogate model is adopted as a basis function to describe the functional relationship between input variables and output response; the generative adversarial theory is employed to obtain hyper-parameters of basis functions by continuous confrontation and evolution between the generation model and discrimination model. Under the GASM concept, the generative adversarial polynomial chaos expansion (GAPCE) method is developed to achieve aerospace engineering structural system reliability design. The effectiveness of presented GAPCE is verified by three examples including the nonlinear functions approximation, reliability design of flap deflection angle, and reliability estimation for turbine blisk radial deformation. The reliability level of flap deflection angle and turbine blisk radial deformation are 0.9998 and 0.9984, when the allowable values are 9° and 1.9222 × 103 m. Besides, the introduced approach possesses advantages of modeling performance (i.e., modeling accuracy and efficiency) and simulation properties (i.e., simulation precision and efficiency) by comparing with various methods. The efforts of this paper can provide a valuable reference for the operational safety of flap systems and engine structures and the development of reliability design theory.


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    Titel :

    Generative adversarial surrogate modeling framework for aerospace engineering structural system reliability design


    Beteiligte:
    Teng, Da (Autor:in) / Feng, Yun-Wen (Autor:in) / Lu, Cheng (Autor:in) / Keshtegar, Behrooz (Autor:in) / Xue, Xiao-Feng (Autor:in)


    Erscheinungsdatum :

    2023-11-24




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch







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