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Adaptive vectorial surrogate modeling framework for multi-objective reliability estimation

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  • Lu, Cheng
  • Teng, Da
  • Chen, Jun-Yu
  • Fei, Cheng-Wei
  • Keshtegar, Behrooz

Abstract

Vectorial modeling concept is proposed in this paper by introducing the matrix theory into the point modeling concept (surrogate modeling strategy), and an adaptive vectorial surrogate modeling framework (AVSMF, short for) is developed based on the vectorial modeling concept and adaptive modeling strategy. Herein, the adaptive modeling strategy is adopted to determine the form of mathematical model of each objective in line with the cost function, the surrogate modeling strategy is regarded as the basis function for reflecting the relationship of the output of single-objective between the relevant inputs, and the matrix theory is used to ascertain the vectors and cell arrays of undetermined parameters and to establish the performance function of multi-objective structures. To validate the proposed method, we use three examples including approximate and probabilistic analysis of nonlinear function with multiple responses, reliability evaluation of landing gear brake system temperature and reliability assessment of aeroengine high-pressure turbine blisk stress, strain and deformation, to demonstrate the effectiveness of the developed AVSMF. Besides, the modeling and simulation properties are verified by comparison of different methods. The results show that the proposed AVSMF has obvious advantages in the computational efficiency and precision.

Suggested Citation

  • Lu, Cheng & Teng, Da & Chen, Jun-Yu & Fei, Cheng-Wei & Keshtegar, Behrooz, 2023. "Adaptive vectorial surrogate modeling framework for multi-objective reliability estimation," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    • Handle: RePEc:eee:reensy:v:234:y:2023:i:c:s0951832023000637
    DOI: 10.1016/j.ress.2023.109148
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    1. Jia-Qi, Liu & Yun-Wen, Feng & Cheng, Lu & Wei-Huang, Pan, 2024. "Decomposed-coordinated framework with intelligent extremum network for operational reliability analysis of complex system," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    2. 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).
    3. Pan, Wei-Huang & Feng, Yun-Wen & Lu, Cheng & Liu, Jia-Qi, 2023. "Analyzing the operation reliability of aeroengine using Quick Access Recorder flight data," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    4. Jia-Qi, Liu & Yun-Wen, Feng & Da, Teng & Jun-Yu, Chen & Cheng, Lu, 2023. "Operational reliability evaluation and analysis framework of civil aircraft complex system based on intelligent extremum machine learning model," Reliability Engineering and System Safety, Elsevier, vol. 235(C).

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