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Vectorial generative adversarial surrogate modeling reliability evaluation framework for engineering structural systems

Author

Listed:
  • Teng, Da
  • Feng, Yun-Wen
  • Lu, Cheng
  • Liu, Jia-Qi
  • Chen, Jun-Yu

Abstract

To effectively evaluate the multi-objective reliability of engineering structural systems, the vectorial generative adversarial surrogate modeling (VGASM) reliability evaluation concept is proposed by integrating the surrogate model, matrix theory, generate adversarial strategy, Copula thought, and linkage sampling technology. In this concept, the surrogate model is employed as a basis function; the matrix theory is applied to establish the vectors and cell arrays of variables and hyperparameters; the generate adversarial strategy is adopted to determine the hyperparameters; the Copula thought and linkage sampling technology are utilized to simultaneously implement multi-objective correlated reliability analysis. Under this concept, the vectorial generative adversarial Kriging (VGAK) reliability evaluation method is developed by combining the Kriging model with VGASM reliability evaluation concept. In addition, a mathematical example and two engineering cases (i.e., aeroengine exhaust gas temperature and turbine blisk multi-failures) are employed to validate the proposed method. The reliability devel of aeroengine exhaust gas temperature and turbine blisk are 0.9989 and 0.9984, when the allowable values of EGT, deformation, and strain are 950 °C, 1.9253 × 10−3 m, and 5.2898 × 10−3 m. Besides, the presented method holds excellent modeling and simulation properties by comparing multiple methods. The study can provide theoretical references for the multi-objective reliability evaluation of engineering structural systems.

Suggested Citation

  • Teng, Da & Feng, Yun-Wen & Lu, Cheng & Liu, Jia-Qi & Chen, Jun-Yu, 2024. "Vectorial generative adversarial surrogate modeling reliability evaluation framework for engineering structural systems," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
  • Handle: RePEc:eee:reensy:v:247:y:2024:i:c:s0951832024001509
    DOI: 10.1016/j.ress.2024.110076
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    References listed on IDEAS

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    1. Zhang, Weibin & Jiang, Weiyang & Liu, Qing & Wang, Weifeng, 2023. "AIS data repair model based on generative adversarial network," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
    2. He, Jingjing & Huang, Min & Wang, Wei & Wang, Shaohua & Guan, Xuefei, 2021. "An asymptotic stochastic response surface approach to reliability assessment under multi-source heterogeneous uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    3. Teng, Da & Feng, Yun-Wen & Chen, Jun-Yu & Liu, Jia-Qi & Lu, Cheng, 2024. "Multi-polynomial chaos Kriging-based adaptive moving strategy for comprehensive reliability analyses," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    4. Liu, Wenli & Shao, Yixiao & Li, Chen & Li, Chengqian & Jiang, Zehao, 2023. "Development of a non-Gaussian copula Bayesian network for safety assessment of metro tunnel maintenance," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
    5. Yaqun, Qi & Ping, Jin & Ruizhi, Li & Sheng, Zhang & Guobiao, Cai, 2020. "Dynamic reliability analysis for the reusable thrust chamber: A multi-failure modes investigation based on coupled thermal-structural analysis," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    6. Luo, Changqi & Zhu, Shun-Peng & Keshtegar, Behrooz & Niu, Xiaopeng & Taylan, Osman, 2023. "An enhanced uniform simulation approach coupled with SVR for efficient structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    7. Sun, Quan & Peng, Fei & Yu, Xianghai & Li, Hongsheng, 2023. "Data augmentation strategy for power inverter fault diagnosis based on wasserstein distance and auxiliary classification generative adversarial network," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
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