方位(导航)
微观结构
材料科学
硬化(计算)
残余应力
耐久性
可塑性
使用寿命
结构工程
微观力学
冶金
复合材料
工程类
计算机科学
图层(电子)
复合数
人工智能
作者
Muhammad Usman Abdullah,Zulfiqar Ahmad Khan
出处
期刊:Materials
[MDPI AG]
日期:2022-08-26
卷期号:15 (17): 5885-5885
被引量:3
摘要
During service, bearing components experience rolling cyclic fatigue (RCF), resulting in subsurface plasticity and decay of the parent microstructure. The accumulation of micro strains spans billions of rolling cycles, resulting in the continuous evolution of the bearing steel microstructure. The bearing steel composition, non-metallic inclusions, continuously evolving residual stresses, and substantial work hardening, followed by subsurface softening, create further complications in modelling bearing steel at different length scales. The current study presents a multiscale overview of modelling RCF in terms of plastic deformation and the corresponding microstructural alterations. This article investigates previous models to predict microstructural alterations and material hardening approaches widely adopted to mimic the cyclic hardening response of the evolved bearing steel microstructure. This review presents state-of-the-art, relevant reviews in terms of this subject and provides a robust academic critique to enhance the understanding of the elastoplastic response of bearing steel under non-proportional loadings, damage evolution, and the formation mechanics of microstructural alterations, leading to the increased fatigue life of bearing components. It is suggested that a multidisciplinary approach at various length scales is required to fully understand the micromechanical and metallurgical response of bearing steels widely used in industry. This review will make significant contributions to novel design methodologies and improved product design specifications to deliver the durability and reliability of bearing elements.
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