Low cycle fatigue test and enhanced lifetime estimation of high-strength steel S550 under different strain ratios

被引:53
|
作者
Feng, Liuyang [1 ]
Qian, Xudong [1 ]
机构
[1] Natl Univ Singapore, Dept Civil & Environm Engn, Ctr Offshore Res & Engn, Singapore 117576, Singapore
基金
新加坡国家研究基金会;
关键词
Low-cycle fatigue; Mean stress relaxation; High-strength steel; Cyclic plasticity; Microstructure; Energy-based fatigue prediction model; Damage mechanics; Finite element; MEAN STRESS-RELAXATION; CRACK-GROWTH; BEHAVIOR; SIMULATION; ENERGY; DEFORMATION; PLASTICITY; CRITERIA; JOINTS;
D O I
10.1016/j.marstruc.2018.06.011
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
This study investigates the low-cycle fatigue (LCF) behavior of the high-strength steel S550 (commonly used in ship and floating structures) under different strain amplitudes with different strain ratios at a room temperature. The test results characterize the cyclic stress-strain relationship, the mean stress relaxation behavior and the cyclic plasticity parameters of S550 steels. The scanning electron microscopy (SEM) examinations on the failure surface reveal the fatigue crack initiation and growth mechanism. Based on the experimental results, this study presents two enhanced approaches to estimate the low-cycle fatigue life of 5550 steels. The energy-based approach modifies the original Smith-Watson-Topper model using the applied energy calculated in the first cycle to enhance the accuracy and facilitate engineering implementations. The damage mechanics-based approach calibrates the material parameters from the measured total fatigue life by combining the fatigue crack initiation model and the damage growth model. The computed fatigue life using the calibrated material parameters demonstrates a close agreement with the measured fatigue life in the experiment.
引用
收藏
页码:343 / 360
页数:18
相关论文
共 50 条
  • [31] Energy-Based Prediction of Low Cycle Fatigue Life of High-Strength Structural Steel
    Luo Yun-rong
    Huang Chong-xiang
    Guo Yi
    Wang Qing-yuan
    JOURNAL OF IRON AND STEEL RESEARCH INTERNATIONAL, 2012, 19 (10) : 47 - 53
  • [32] High-Strength Reinforcing Steel Bars: Low Cycle Fatigue Behavior Using RGB Methodology
    Jorge E. Egger
    Fabian R. Rojas
    Leonardo M. Massone
    International Journal of Concrete Structures and Materials, 2021, 15
  • [33] Low-cycle fatigue performance of high-strength steel rebars in concrete bridge columns
    Aldabagh, Saif
    Rodriguez, Jhordy
    Alam, M. Shahria
    EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS, 2022, 51 (05): : 1115 - 1132
  • [34] Short crack behavior during low-cycle fatigue in high-strength bainitic steel
    Marinelli, M. C.
    Alvarez-Armas, I.
    Krupp, U.
    XVIII INTERNATIONAL COLLOQUIUM ON MECHANICAL FATIGUE OF METALS (ICMFM XVIII), 2016, 160 : 183 - 190
  • [35] Energy-Based Prediction of Low Cycle Fatigue Life High-Strength Structural Steel
    Yun-rong Luo
    Chong-xiang Huang
    Yi Guo
    Qing-yuan Wang
    Journal of Iron and Steel Research International, 2012, 19 : 47 - 53
  • [36] High-Strength Reinforcing Steel Bars: Low Cycle Fatigue Behavior Using RGB Methodology
    Egger, Jorge E.
    Rojas, Fabian R.
    Massone, Leonardo M.
    INTERNATIONAL JOURNAL OF CONCRETE STRUCTURES AND MATERIALS, 2021, 15 (01)
  • [37] Energy-Based Prediction of Low Cycle Fatigue Life of High-Strength Structural Steel
    LUO Yun-rong1
    2. College of Mechanical Engineering
    Journal of Iron and Steel Research(International), 2012, 19 (10) : 47 - 53
  • [38] Rapid S-N type life estimation for low cycle fatigue of high-strength steels at a low ambient temperature
    Feng, Liuyang
    Qian, Xudong
    STEEL AND COMPOSITE STRUCTURES, 2019, 33 (06): : 777 - 792
  • [39] Experimental study on high-cycle fatigue performance of LQ550 cold-rolled high-strength steel sheet
    Wang Y.
    Li Y.
    Jianzhu Jiegou Xuebao/Journal of Building Structures, 2024, 45 (04): : 189 - 197
  • [40] Low-cycle fatigue parameters and fatigue life estimation of high-strength steels with artificial neural networks
    Soyer, Mehmet Alperen
    Kalayci, Can Berk
    Karakas, Ozler
    FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES, 2022, 45 (12) : 3764 - 3785