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A hybrid approach of adaptive surrogate model and sampling method for reliability assessment in multidisciplinary design optimization

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  • Keramatinejad, Mahdi
  • Karbasian, Mahdi
  • Alimohammadi, Hamidreza
  • Atashgar, Karim

Abstract

Uncertainty is an inherent element of multidisciplinary design optimization (MDO), often leading to undesirable performance and potentially infeasible designs. Reliability-Based Multidisciplinary Design Optimization (RBMDO) aims to deliver solutions that achieve desirable performance metrics while remaining resilient to uncertainties. However, the RBMDO process is computationally intensive and can be impractical for launch vehicle (LV) design optimization. This paper presents an innovative hybrid approach that integrates Adaptive Response Surface Methodology (ARSM) with Directional Sampling (DS) to enhance the efficiency of reliability analysis. The ARSM-DS method yields faster and more effective results compared to traditional Monte Carlo Simulation (MCS) techniques. The study specifically focuses on the reliability assessment of a two-stage launch vehicle in its conceptual design phase. The methodology encompasses several critical steps: defining the reliability problem, identifying potential failure modes, establishing target reliability at the system level, modeling reliability, allocating reliability to subsystems, formulating the RBMDO problem, analyzing subsystem reliability using the ARSM-DS method, conducting multidisciplinary optimization based on reliability criteria, predicting overall system reliability, and evaluating computed reliability against the established target. This approach not only enhances the reliability analysis process but also significantly increases the feasibility of design optimization efforts in aerospace applications.

Suggested Citation

  • Keramatinejad, Mahdi & Karbasian, Mahdi & Alimohammadi, Hamidreza & Atashgar, Karim, 2025. "A hybrid approach of adaptive surrogate model and sampling method for reliability assessment in multidisciplinary design optimization," Reliability Engineering and System Safety, Elsevier, vol. 261(C).
    • Handle: RePEc:eee:reensy:v:261:y:2025:i:c:s0951832025002157
    DOI: 10.1016/j.ress.2025.111014
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    References listed on IDEAS

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    1. Zhang, Jian & Gong, Weijie & Yue, Xinxin & Shi, Maolin & Chen, Lei, 2022. "Efficient reliability analysis using prediction-oriented active sparse polynomial chaos expansion," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    2. 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).
    3. Li, Wenxiong & Geng, Rong & Chen, Suiyin, 2024. "CSP-free adaptive Kriging surrogate model method for reliability analysis with small failure probability," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    4. Jing, Zhao & Chen, Jianqiao & Li, Xu, 2019. "RBF-GA: An adaptive radial basis function metamodeling with genetic algorithm for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 42-57.
    5. Meng, Debiao & Yang, Shiyuan & Jesus, Abílio M.P. de & Zhu, Shun-Peng, 2023. "A novel Kriging-model-assisted reliability-based multidisciplinary design optimization strategy and its application in the offshore wind turbine tower," Renewable Energy, Elsevier, vol. 203(C), pages 407-420.
    6. Chen, Junhua & Chen, Zhiqun & Jiang, Wei & Guo, Hun & Chen, Longmiao, 2025. "A reliability-based design optimization strategy using quantile surrogates by improved PC-kriging," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    7. Tao, Haohan & Jia, Peng & Wang, Xiangyu & Wang, Liquan, 2024. "Reliability analysis of subsea control module based on dynamic Bayesian network and digital twin," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    8. Song, Chaolin & Xiao, Rucheng & Zhang, Chi & Zhao, Xinwei & Sun, Bo, 2024. "Simulation-free reliability analysis with importance sampling-based adaptive training physics-informed neural networks: Method and application to chloride penetration," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    9. Tang, Xueyang & Cai, Xiaopei & Wang, Yuqi & Wang, Pu & Yang, Fei, 2025. "Advanced VTSDREF for vehicle-turnout system dynamic reliability analysis: Integration of hybrid deep learning and adaptive probability density evolution method," Reliability Engineering and System Safety, Elsevier, vol. 256(C).
    10. Lou, Ping & Shi, Tao & Yang, T.Y., 2025. "Reliability analysis for running safety of vehicle on slab track via an improved second-order fourth-moment approach," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    11. Mei, Fabin & Chen, Hao & Yang, Wenying & Zhai, Guofu, 2024. "A hybrid physics-informed machine learning approach for time-dependent reliability assessment of electromagnetic relays," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
    12. Song, Chaolin & Shafieezadeh, Abdollah & Xiao, Rucheng & Sun, Bin, 2024. "Analytical robust design optimization for hybrid design variables: An active-learning methodology based on polynomial chaos Kriging," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
    13. Brahim Lafifi & Ammar Rouaiguia, 2021. "Investigation of reliability analysis of shallow foundation by combining Hasofer-Lind index, response surface methodology and multi-objective genetic algorithm," International Journal of Reliability and Safety, Inderscience Enterprises Ltd, vol. 15(1/2), pages 18-36.
    14. Guo, Tiexin & Wang, Hongji & Li, Jinglai & Wang, Hongqiao, 2024. "Sampling-based adaptive design strategy for failure probability estimation," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    15. Li, Zai-Wei & Zhou, Yun-Lai & Liu, Xiao-Zhou & Abdel Wahab, Magd, 2023. "Service reliability assessment of ballastless track in high speed railway via improved response surface method," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    16. Zhang, Qin & Liu, Yu & Xiang, Yisha & Xiahou, Tangfan, 2024. "Reinforcement learning in reliability and maintenance optimization: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    17. Nannapaneni, Saideep & Mahadevan, Sankaran, 2020. "Probability-space surrogate modeling for fast multidisciplinary optimization under uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    18. Alimohammadi, H.R. & Naseh, H. & Ommi, F., 2023. "An integrated methodology applied for reliability based multi-disciplinary design optimization in EPFE with LOX/kerosene," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
    19. Lu, Ning & Li, Yan-Feng & Huang, Hong-Zhong & Mi, Jinhua & Niazi, Sajawal Gul, 2023. "AGP-MCS+D: An active learning reliability analysis method combining dependent Gaussian process and Monte Carlo simulation," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
    20. Ding, Rui & Liu, Zehua & Xu, Jintao & Meng, Fanpeng & Sui, Yang & Men, Xinhong, 2021. "A novel approach for reliability assessment of residual heat removal system for HPR1000 based on failure mode and effect analysis, fault tree analysis, and fuzzy Bayesian network methods," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    21. Oszczypała, Mateusz & Konwerski, Jakub & Ziółkowski, Jarosław & Małachowski, Jerzy, 2024. "Reliability analysis and redundancy optimization of k-out-of-n systems with random variable k using continuous time Markov chain and Monte Carlo simulation," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    22. Lu, Yixin & Lu, Zhenzhou, 2025. "A novel cross-entropy-based importance sampling method for cumulative time-dependent failure probability function," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    23. Hu, Huanhuan & Wang, Pan & Xin, Fukang & Zhang, Lei & Yang, Weizhu & Li, Lei, 2024. "Hybrid adaptive moment estimation based performance measure approach for complex reliability-based design optimization," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
    24. Weng, Ye-Yao & Liu, Teng & Zhang, Xuan-Yi & Zhao, Yan-Gang, 2025. "Probability density estimation of polynomial chaos and its application in structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    25. Xu, Yanwen & Bansal, Parth & Wang, Pingfeng & Li, Yumeng, 2025. "Physics-informed machine learning for system reliability analysis and design with partially observed information," Reliability Engineering and System Safety, Elsevier, vol. 254(PB).
    26. Zhang, Tianyuan & Xing, Liudong & Mo, Yuchang, 2025. "A multi-valued decision diagrams-based method for reliability analysis of performance-sharing k-out-of-n: G system considering component degradation," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    27. Zhan, Hongyou & Xiao, Ning-Cong, 2025. "A new active learning surrogate model for time- and space-dependent system reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
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    2. Feng, Shichao & Wang, Lei & Dong, Haibo & Li, Yanqing & Wan, Zhengquan & Guedes Soares, C., 2026. "An active-learning method based on hierarchical Kriging model for multi-fidelity reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 266(PB).
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