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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基于先验知识的LCF寿命预测框架及其在多轴载荷下的轴类部件应用

预测复杂载荷条件下的低周疲劳（LCF）寿命一直是一个挑战。可靠的疲劳寿命预测是工业零部件疲劳可靠性评估的关键。提出了一种基于先验知识的多轴载荷下LCF寿命预测框架。该框架集成了物理知识和部分已知关系。受基于可靠性的设计优化（RBDO）概念的启发，该框架能够以更高的效率和准确性预测确定性和概率LCF寿命。在此基础上，通过引入多轴疲劳参数，讨论了存活率下构件LCF寿命退化问题。该参数能有效描述椭圆多轴加载路径下LCF寿命变化趋势。进一步研究了结构构件的危险率和疲劳可靠性。本文的研究可以为实际工业环境中的应用提供有价值的指导。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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.