Multiaxial fatigue behavior of EQ56 marine high-strength steel under different strain ratios

被引:2
作者
Zhu, Hongmei [1 ]
Gao, Xudong [1 ]
Shao, Yongbo [2 ]
Li, Kangshuai [2 ]
Zong, Liang [3 ]
Chen, Cheng [2 ]
机构
[1] Southwest Petr Univ, Sch Mechatron Engn, Chengdu 610500, Peoples R China
[2] Southwest Petr Univ, Sch Civil Engn & Geomatics, Chengdu 610500, Peoples R China
[3] Tianjin Univ, Sch Civil Engn, Tianjin 300072, Peoples R China
基金
中国国家自然科学基金;
关键词
EQ56 high-strength steel; Low-cycle multiaxial fatigue; Multiaxial strain ratio; Fractography; Life prediction; LOW-CYCLE FATIGUE; LIFE PREDICTION; DEFORMATION; CRITERIA; DUCTILE; STRESS;
D O I
10.1016/j.jcsr.2025.109368
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Multiaxial low-cycle fatigue tests were conducted on EQ56 high-strength steel for offshore platforms, investi root root root root gating the effects of multiaxial strain ratios (lambda = 3 /2, 3 , 1.5 3 , 2 3 ) and strain amplitudes (Delta epsilon/2 = +0.29 %, +0.35 %, +0.42 %, +0.57 %, +0.75 %) on cyclic behavior. The material exhibits pronounced cyclic hardening at high strain ratios and amplitudes, while at low strain ratios and amplitudes, the hardening behavior is not observed. Throughout the fatigue life, the material predominantly exhibits cyclic softening. Fractographic analysis using 3D depth-of-field imaging reveals a transition from tensile to shear failure modes with increasing strain ratio, indicating a mixed failure mode. Scanning electron microscopy (SEM) observations further confirm this transition through tire-like traces and increasingly blurred cleavage features, attributed to the influence of shear components. A comparative analysis of four critical plane multiaxial fatigue life prediction models was conducted. The Wu-Hu-Song (WHS) model, which accounts for mixed failure modes, achieved 78 % prediction accuracy with a mean relative error (MRE) of 22.8 %. The modified Kandil-Brown-Miller (KBM) model and WHS model (i.e., KBM-M, WHS-M), which incorporate the effect of multiaxial strain ratios and show improved accuracy and reduced prediction dispersion, with MRE values of 12.6 % and 15 %, respectively.
引用
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页数:21
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