Microstructure-based fatigue modelling with residual stresses: Prediction of the fatigue life for various inclusion sizes

被引:34
|
作者
Gu, Chao [1 ,3 ]
Lian, Junhe [2 ,4 ]
Bao, Yanping [1 ]
Xie, Qingge [5 ]
Muenstermann, Sebastian [3 ]
机构
[1] Univ Sci & Technol Beijing, State Key Lab Adv Met, Beijing 100083, Peoples R China
[2] Aalto Univ, Dept Mech Engn, Adv Mfg & Mat, Espoo 02150, Finland
[3] Rhein Westfal TH Aachen, Steel Inst, Intzestr 1, D-52074 Aachen, Germany
[4] MIT, Dept Mech Engn, Impact & Crashworthiness Lab, 77 Massachusetts Ave, Cambridge, MA 02139 USA
[5] Univ Sci & Technol Beijing, Collaborat Innovat Ctr Steel Technol, Beijing 100083, Peoples R China
关键词
Microstructure-sensitive modelling; Residual stress; Defects; Fatigue life; Inclusion size; HIGH-STRENGTH STEELS; FINITE-ELEMENT METHOD; CRACK INITIATION; HIGH-CYCLE; DAMAGE INITIATION; GRAIN-BOUNDARIES; STRAIN RATIO; PLASTICITY; FRACTURE; DEFORMATION;
D O I
10.1016/j.ijfatigue.2019.06.018
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
In this study, the inclusion induced fatigue failure of a high-carbon bearing steel was investigated. The experimental results showed that the size of calcium aluminate inclusions observed near the fatigue crack initiation site ranges from 12.5 mu m to 33.2 mu m and the size has a pronounced impact on the fatigue life. A microstructurebased model that considers the residual stresses between the steel matrix and inclusions induced by the heat treatment of the steel was developed and applied to investigate the effect the inclusion size on fatigue properties. The detailed model parameter calibration strategy and its validation were illustrated. It is concluded that the model considering the residual stress showed very good predictive capability of the S-N curves for different inclusion sizes, while the model without residual stresses failed to reflect the inclusion size effect on the S-N curve. In addition, based on the simulation data with accurate inclusion size control, an analytical relation between fatigue life, fatigue stress, and inclusion size was proposed for the investigated steel.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] Microstructure-based life prediction of thermal barrier coatings
    Eriksson, Robert
    Yuan, Kang
    Johansson, Sten
    Peng, Ru Lin
    MATERIALS STRUCTURE & MICROMECHANICS OF FRACTURE VII, 2014, 592-593 : 413 - 416
  • [42] Prediction of residual fatigue life using nonlinear ultrasound
    Amura, Mikael
    Meo, Michele
    SMART MATERIALS AND STRUCTURES, 2012, 21 (04)
  • [43] Microstructure-based fatigue life modeling methodology for ferritic-pearlitic hypo-eutectoid steels
    Park, Minwoo
    Kim, Hyunki
    Kang, Minwoo
    Hong, Seunghyun
    Choi, Yoon Suk
    JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T, 2022, 19 : 2356 - 2368
  • [44] Influence of residual stresses on fretting fatigue life prediction in Ti-6AI-4V
    Golden, Patrick J.
    Buchanan, Dennis
    Naboulsi, Sam
    Journal of ASTM International, 2008, 5 (08):
  • [45] Unified fatigue life prediction of bolts with different sizes and lengths under various axial loading conditions
    Nam, Juhyun
    Kim, Dongwon
    Kim, Kyungjae
    Choi, Sungwon
    Oh, Je Hoon
    ENGINEERING FAILURE ANALYSIS, 2022, 131
  • [47] ROLE OF MICROSTRUCTURE AND RESIDUAL-STRESSES ON FATIGUE CRACK INITIATION OF CARBONITRIDED STEELS
    LESAGE, J
    CHICOT, D
    ALKARAISHI, M
    STEEL RESEARCH, 1989, 60 (08): : 370 - 374
  • [48] Residual Fatigue Life Prediction of Ball Bearings Based on Paris Law and RMS
    Xu Dong
    Huang Jin'e
    Zhu Qin
    Chen Xun
    Xu Yongcheng
    Wang Shuang
    CHINESE JOURNAL OF MECHANICAL ENGINEERING, 2012, 25 (02) : 320 - 327
  • [49] Residual fatigue life prediction of ball bearings based on Paris law and RMS
    Dong Xu
    Jin’e Huang
    Qin Zhu
    Xun Chen
    Yongcheng Xu
    Shuang Wang
    Chinese Journal of Mechanical Engineering, 2012, 25 : 320 - 327
  • [50] Fatigue Crack and Residual Life Prediction Based on an Adaptive Dynamic Bayesian Network
    Chen, Shuai
    Ma, Yinwei
    Wang, Zhongshu
    Liu, Minjing
    Wu, Zhanjun
    APPLIED SCIENCES-BASEL, 2024, 14 (09):