Fatigue life prediction of structural steel using acoustic birefringence and characteristics of persistent slip bands

被引:7
作者
Gonchar, Alexander Victorovich [1 ]
Kurashkin, Konstantin Vladimirovich [1 ]
Andreeva, Olga Vyacheslavovna [2 ]
Anosov, Maxim Sergeevich [2 ]
Klyushnikov, Vyacheslav Alexandrovich [1 ]
机构
[1] Russian Acad Sci, Fed Res Ctr, Inst Appl Phys, Mechan Engn Res Inst, 85 Belinsky St, Nizhnii Novgorod 603024, Russia
[2] Nizhny Novgorod State Tech Univ na RE Alekseev, Inst Mfg Technol Machine Bldg, Nizhnii Novgorod, Russia
基金
俄罗斯基础研究基金会;
关键词
acoustic birefringence; fatigue life prediction; low-cycle fatigue; nondestructive evaluation; persistent slip bands; DAMAGE; MICROCRACK; ANISOTROPY; EVOLUTION; FAILURE; GROWTH; STRAIN; ALLOY;
D O I
10.1111/ffe.13586
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Nondestructive evaluation methods provide additional information about the material fatigue behavior and enhance the comprehension of damage evolution thanks to relationship between microstructure and physical properties. This paper deals with optical and ultrasonic investigations of structural steel specimens tested for low-cycle fatigue. The development of persistent slip bands observed on the surface with an optical microscope was quantified using a previously trained neural network and fractal analysis. A surface damage parameter was defined as the ratio of total area of detected slip bands to the area of observed surface. Relationships between the rate of change and critical value of the damage parameter, the strain range, and the fatigue life were established. A single square relationship between relative number of cycles and ratio of the surface damage parameter to its critical value was obtained. Acoustic birefringence was measured by the echo method. The effect of the strain range on the rate of change in acoustic birefringence was investigated. A single linear relationship between relative number of cycles and change in acoustic birefringence was established. An algorithm for predicting the material remaining life, combining optical and ultrasonic data, was proposed.
引用
收藏
页码:101 / 112
页数:12
相关论文
共 48 条
[1]  
Andreev Vyacheslav, 2020, E3S Web of Conferences, V209, DOI 10.1051/e3sconf/202020903003
[2]  
[Anonymous], 1954, NACA Report 1170
[3]   Estimating the Plastic Strain with the Use of Acoustic Anisotropy [J].
Belyaev, A. K. ;
Lobachev, A. M. ;
Modestov, V. S. ;
Pivkov, A. V. ;
Polyanskii, V. A. ;
Semenov, A. S. ;
Tret'yakov, D. A. ;
Shtukin, L. V. .
MECHANICS OF SOLIDS, 2016, 51 (05) :606-611
[4]   Investigation of the correlation between acoustic anisotropy, damage and measures of the stress-strain state [J].
Belyaev, Alexander K. ;
Polyanskiy, Vladimir A. ;
Semenov, Artem S. ;
Tretyakov, Dmitry A. ;
Yakovlev, Yuriy A. .
XXVII INTERNATIONAL CONFERENCE: MATHEMATICAL AND COMPUTER SIMULATION IN MECHANICS OF SOLIDS AND STRUCTURES - FUNDAMENTALS OF STATIC AND DYNAMIC FRACTURE (MCM 2017), 2017, 6 :201-207
[5]   Surface damage evolution of engineering steel [J].
Besel, M. ;
Brueckner-Foit, A. .
FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES, 2008, 31 (10) :885-891
[6]  
Cantrell JH, 2001, INT J FATIGUE, V23, pS487, DOI 10.1016/S0142-1123(01)00162-1
[7]  
Chen E. Y., 1997, International Journal of Fatigue, V19, pS75, DOI 10.1016/S0142-1123(97)00015-7
[8]  
Coffin LF, 1954, T AM SOC MECH ENG, V76, P931, DOI DOI 10.1115/1.4015020
[9]   Machine learning-based accelerated property prediction of two-phase materials using microstructural descriptors and finite element analysis [J].
Ford, Emily ;
Maneparambil, Kailasnath ;
Rajan, Subramaniam ;
Neithalath, Narayanan .
COMPUTATIONAL MATERIALS SCIENCE, 2021, 191
[10]   Study of fatigue failure of construction steels by using modern methods of digital processing of microstructural images [J].
Gonchar, A., V ;
Andreeva, O., V ;
Anosov, M. S. .
MATERIALS TODAY-PROCEEDINGS, 2021, 38 :1701-1705