A data-driven roadmap for creep-fatigue reliability assessment and its implementation in low-pressure turbine disk at elevated temperatures. (September 2022)

• Record Type: Journal Article
• Authors: Wang, Run-Zi; Gu, Hang-Hang; Zhu, Shun-Peng; Li, Kai-Shang; Wang, Ji; Wang, Xiao-Wei; Hideo, Miura; Zhang, Xian-Cheng; Tu, Shan-Tung
• Is Part Of: Reliability engineering & system safety. Volume 225(2022)
• Publication Date: 2022-09
• Subjects: Creep-fatigue -- Reliability assessment -- Turbine disk -- Surrogate model -- Probabilistic safety design; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2022.108523
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: Constructing creep-fatigue reliability assessment roadmap for probabilistic design. Achieving association between material and component-level turbine disk application. Introducing surrogate modeling into probabilistic analysis to enhance efficiency. Providing reasonable reliability assessment results based on proposed PDID method. Implementing joint failure evaluation to consider potential failure occurrences. Abstract: High-reliability life design process not only can ensure system safety in service, but also can provide scientific life management during the maintenance period. The objective of the present work is to develop a roadmap for creep-fatigue reliability assessment. Material-level data accumulations and theoretical foundations of creep-fatigue including creep-fatigue constitutive and multi-axial damage models are introduced. Afterwards, a low-pressure turbine disk under a typical creep-fatigue load waveform is applied as a case study to demonstrate how to perform creep-fatigue reliability assessment by using this roadmap in practice. Precise weakness hotspots are identified at the mortise joint of turbine disk. Based on hotspot-based strategy, it is found that the surrogate model assisted by an optimized machine learning method enhances significantly the computational efficiency. Accordingly, the probabilistic creep-fatigue life with considering multi-sources uncertainty obeys lognormal distributions. In the aspect of failure probability analysis, the current probabilistic damage interaction diagram method with creep-fatigue interaction gives conservative reliability assessments and excellent universality as compared to traditional ones mainly used in the low cycle fatigue field. Last but not least, joint failure evaluation of the turbine disk is discussed to comprehensively consider potential failure occurrence in an averaged hot region instead of a single hotspot. Graphical abstract: Image, graphical abstract