A prior knowledge-guided predictive framework for LCF life and its implementation in shaft-like components under multiaxial loading

IF 9.4 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

Reliability Engineering & System Safety Pub Date : 2025-03-25 DOI:10.1016/j.ress.2025.111044

Butong Li, Junjie Zhu, Xufeng Zhao

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引用次数: 0

Abstract

Predicting low-cycle fatigue (LCF) life under complex loading conditions has long been a challenge. Reliable fatigue life prediction is crucial for the fatigue reliability assessment of industrial components. This paper proposes a prior knowledge-guided framework for predicting LCF life under multiaxial loading conditions. The framework integrates physical knowledge and partial known relationships. Inspired by concepts from reliability-based design optimization (RBDO), the framework is capable of predicting deterministic and probabilistic LCF life with greater efficiency and accuracy. Building on this, we discuss the LCF life degradation of components under survival rates by introducing the multiaxial fatigue parameter. The parameter can effectively describe the trends of LCF life under elliptical multiaxial loading paths. Furthermore, the hazard rate and fatigue reliability of structural components is investigated. The research presented in this paper can offer valuable guidance for applications in practical industrial contexts.

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来源期刊

Reliability Engineering & System Safety 管理科学-工程：工业

CiteScore

15.20

自引率

39.50%

发文量

621

审稿时长

67 days

期刊介绍： Elsevier publishes Reliability Engineering & System Safety in association with the European Safety and Reliability Association and the Safety Engineering and Risk Analysis Division. The international journal is devoted to developing and applying methods to enhance the safety and reliability of complex technological systems, like nuclear power plants, chemical plants, hazardous waste facilities, space systems, offshore and maritime systems, transportation systems, constructed infrastructure, and manufacturing plants. The journal normally publishes only articles that involve the analysis of substantive problems related to the reliability of complex systems or present techniques and/or theoretical results that have a discernable relationship to the solution of such problems. An important aim is to balance academic material and practical applications.