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An integrated methodology applied for reliability based multi-disciplinary design optimization in EPFE with LOX/kerosene

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  • Alimohammadi, H.R.
  • Naseh, H.
  • Ommi, F.

Abstract

Early approaches are based on classical Response Surface Methodology (RSM) using systematic designs of experiments (DoE) and polynomial regression models. In order to improve the approximation quality around the optimum, adaptive methods are very efficient. This work proposes an Adaptive Response Surface Method-Directional Sampling (ARSM-DS) to compute the probability of failure. The method first samples a set of parameters by Latin Hypercube Sampling (LHS). Due to its efficiency, the ARSM is the method of choice for optimization problems. Then for optimal design, a preceding sensitivity analysis as start design for the ARSM has been used. The probability of failure is computed by DS. Directional Sampling yields points on the failure surface of the surrogate model. Hence in the subsequent steps, these points are updated by passing the input values to the solver and computing the respective responses. Finally, Electro-Pump-Fed Engine (EPFE) is studied to illustrate the effectiveness of the proposed method. The computational efficiency and accuracy of the proposed method is elucidated by its comparison with some existing methods. The results show that the proposed method can effectively and accurately evaluate the Reliability-Based Multidisciplinary Optimization (RBMDO) of complex systems and can be used for other engineering applications as well.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:reensy:v:240:y:2023:i:c:s0951832023004842
    DOI: 10.1016/j.ress.2023.109570
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    References listed on IDEAS

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    1. Jung, Yongsu & Lee, Ikjin, 2021. "Optimal design of experiments for optimization-based model calibration using Fisher information matrix," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
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    1. Braga, Joaquim A.P. & Costa, João N. & Ambrósio, Jorge & Frey, Daniel & Andrade, António R., 2024. "Robust assessment of railway vehicle safety risks in operation using a proposed data-driven wheel profile generation approach: Design of computer experiments and surrogate models," Reliability Engineering and System Safety, Elsevier, vol. 249(C).

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