Reliability-based design optimization of fluid-conveying pipeline structure subjected to in-service loadings

Zhenghong Yao, Jin Hao, Changyou Li, Zhiyuan Jiang and Jinsong Zhao

Reliability Engineering and System Safety, 2025, vol. 256, issue C

Abstract: Fluid-conveying pipeline structure is essential component in aircraft engine. The ratcheting failure of pipe is inevitably accompanied by oil leakage and catastrophic accidents. Regarding that, this paper proposes a ratcheting fatigue reliability-based design optimization (RFRBDO) model to obtain the optimal design of the pipeline structure. The objectives of the optimization are to maximize ratcheting fatigue life and minimize the amount of production consumables. A ratcheting fatigue life prediction model of the pipeline structure subjected to in-service loadings is developed based on ductility exhaustion theory and finite element method (FEM). In addition, an innovative testing system is constructed to validate the accuracy of the life prediction model. Subsequently, the geometric correlation, loading condition variation, and ratcheting fatigue reliability are determined as constraints. Considering the parameter uncertainties, a Kriging surrogate model for evaluating ratcheting fatigue reliability of the pipeline structure is established to reduce the computational burden. Eventually, the effectiveness and robustness of the proposed RFRBDO problem are demonstrated by applying it to pipeline structure. Compared with the ratcheting fatigue deterministic design optimization (RFDDO) results, the target ratcheting fatigue reliability and optimal design of pipeline structure that offer the best compromise between performance, cost, and safety are achieved by the proposed RFRBDO approach.

Keywords: Fluid-conveying pipeline structure; Ratcheting fatigue life prediction model; Ratcheting fatigue reliability-based design optimization; Kriging surrogate model (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:256:y:2025:i:c:s0951832024008123

DOI: 10.1016/j.ress.2024.110741

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