International Journal of Fatigue最新文献_第7页

Prediction of multiaxial fatigue life with a data-driven knowledge transfer model 利用数据驱动的知识转移模型预测多轴疲劳寿命

IF 5.7 2区材料科学

International Journal of Fatigue Pub Date : 2024-10-04 DOI: 10.1016/j.ijfatigue.2024.108636

Lei Gan , Zhi-Ming Fan , Hao Wu , Zheng Zhong

引用次数: 0

Fatigue life prediction of cold expansion hole using physics-enhanced data-driven method 利用物理增强数据驱动法预测冷胀孔的疲劳寿命

IF 5.7 2区材料科学

International Journal of Fatigue Pub Date : 2024-10-04 DOI: 10.1016/j.ijfatigue.2024.108634

Jian-Xing Mao , Zhi-Fan Xian , Xin Wang , Dian-Yin Hu , Jin-Chao Pan , Rong-Qiao Wang , Shi-Kun Zou , Yang Gao

引用次数: 0

Mechanisms of deformation, damage and life behavior of inconel 617 alloy during creep-fatigue interaction at 700 °C inconel 617 合金在 700 °C 蠕变-疲劳相互作用过程中的变形、损伤和寿命行为机理

IF 5.7 2区材料科学

International Journal of Fatigue Pub Date : 2024-10-03 DOI: 10.1016/j.ijfatigue.2024.108635

Qingtong Wang , Jingtai Yu , Bingbing Li , Yuguang Li , Kang Wang , Xu Chen

引用次数: 0

Prediction of fatigue crack damage using in-situ scanning electron microscopy and machine learning 利用原位扫描电子显微镜和机器学习预测疲劳裂纹损伤

IF 5.7 2区材料科学

International Journal of Fatigue Pub Date : 2024-10-03 DOI: 10.1016/j.ijfatigue.2024.108637

Jianli Zhou , Yixu Zhang , Ni Wang , Wenjie Gao , Ling’en Liu , Liang Tang , Jin Wang , Junxia Lu , Yuefei Zhang , Ze Zhang

{"title":"Prediction of fatigue crack damage using in-situ scanning electron microscopy and machine learning","authors":"Jianli Zhou , Yixu Zhang , Ni Wang , Wenjie Gao , Ling’en Liu , Liang Tang , Jin Wang , Junxia Lu , Yuefei Zhang , Ze Zhang","doi":"10.1016/j.ijfatigue.2024.108637","DOIUrl":"10.1016/j.ijfatigue.2024.108637","url":null,"abstract":"<div><div>Nickel-based single crystal superalloys, as engine blade materials, are prone to fatigue damage due to repeated startups and shutdowns. Therefore, monitoring and quantitatively estimating fatigue cracks are essential for engineering structures to ensure safety. In this study, we proposed a method for fatigue crack segmentation and damage prediction based on deep learning and in-situ high-temperature scanning electron microscopy (SEM). Sequential SEM images describing the crack initiation and propagation under near-service conditions were obtained by conducting in-situ high-temperature fatigue experiments. A fatigue crack dataset with high-quality was thus constructed for further dynamic and real-time crack segmentation and damage assessment. Deep learning-based models were used to segment cracks and predict damage behavior (i.e., crack area, length, width, and stress intensity factors) at future based on prior damage information. The short-term and long-term damage prediction capability were validated by comparing model performance when predicting damage at different future time points. Additionally, we compared the model performance when predicting damage at specific time point based on varying lengths of input sequence. Results demonstrated that the model could segment cracks and scales with different sizes accurately. The model performed well in short-term damage prediction. The long-term predictive performance showed decrease than that of short-term, which could be improved by feeding long length of input sequence. The proposed approach demonstrates the feasibility and effectiveness of deep learning-based crack segmentation and damage prediction, which facilitates the move toward real-time analysis and rapid diagnosis of material damage in the future.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"190 ","pages":"Article 108637"},"PeriodicalIF":5.7,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fatigue mechanisms at 450°C of a highly twined (>70%) and HIP-densified IN718 superalloy additively manufactured by laser beam powder bed fusion 通过激光束粉末床熔融技术添加制造的高扭曲度（>70%）和 HIP 致密化 IN718 超合金在 450°C 下的疲劳机理

IF 5.7 2区材料科学

International Journal of Fatigue Pub Date : 2024-10-03 DOI: 10.1016/j.ijfatigue.2024.108629

Marcus C. Lam , Carla M.C. Cruz , Alexis Loustaunau , Anthony Koumpias , Amberlee S. Haselhuhn , Andrew Wessman , Sammy Tin

{"title":"Fatigue mechanisms at 450°C of a highly twined (>70%) and HIP-densified IN718 superalloy additively manufactured by laser beam powder bed fusion","authors":"Marcus C. Lam , Carla M.C. Cruz , Alexis Loustaunau , Anthony Koumpias , Amberlee S. Haselhuhn , Andrew Wessman , Sammy Tin","doi":"10.1016/j.ijfatigue.2024.108629","DOIUrl":"10.1016/j.ijfatigue.2024.108629","url":null,"abstract":"<div><div>Fatigue resistance at elevated temperatures is crucial for certifying aerospace structures additively manufactured by the laser beam powder bed fusion (PBF-LB) method with IN718 superalloy. This study employed a multi-step, supersolvus heat treatment process with hot isostatic pressing (HIP), called RHSA, to minimize pores and brittle phases. Stress intensity factor (△K) calculations using data from X-ray computed tomography and shape factors referencing finite element analysis (FEA) studies confirmed the suppression of △K below the threshold of conventional IN718 (∼5 MPa√m), shifting fatigue behavior to grain-structure-dominated. Despite a very high twin boundary (TB) fraction (>70%), fatigue tests at 450°C and R = 0.1 demonstrated low scatter. Slip trace analysis and high-resolution electron backscatter diffraction (EBSD) revealed that TB-induced strain concentration became prominent only at high △K, causing cracking at 45⁰ to the loading direction. The randomly oriented TBs with higher angles (60⁰) compared to high-angle grain boundaries (HAGBs) (30–40⁰) likely enhanced slip resistance and provided a net strengthening effect, which can explain the lower-than-average TB% along fracture paths. These insights suggest that a high TB fraction is not detrimental if fatigue stress is not excessive, alleviating concerns about annealing twins during defect minimization in AM IN718, allowing novel processes to improve fatigue resistance in PBF-LB IN718.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"190 ","pages":"Article 108629"},"PeriodicalIF":5.7,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fatigue reliability analysis of bogie frames considering parameter uncertainty 考虑参数不确定性的转向架框架疲劳可靠性分析

IF 5.7 2区材料科学

International Journal of Fatigue Pub Date : 2024-10-02 DOI: 10.1016/j.ijfatigue.2024.108632

Dongxu Zhang , Yonghua Li , Zhenliang Fu , Yufeng Wang , Kangjun Xu

{"title":"Fatigue reliability analysis of bogie frames considering parameter uncertainty","authors":"Dongxu Zhang , Yonghua Li , Zhenliang Fu , Yufeng Wang , Kangjun Xu","doi":"10.1016/j.ijfatigue.2024.108632","DOIUrl":"10.1016/j.ijfatigue.2024.108632","url":null,"abstract":"<div><div>With the increasing service life of bogie frames, the risk of fatigue failure becomes significant, making fatigue reliability analysis crucial for ensuring operational safety. However, accurately analyzing fatigue reliability presents a significant challenge with uncertain factors such as load fluctuations, unstable material shaping, and dimensional manufacturing deviations. To address this, this paper establishes a comprehensive active learning reliability framework based on surrogate models, enabling high-fidelity modeling and precise fatigue reliability analysis of welded frames under parameter uncertainty. The material utilization method was developed using APDL for secondary development to efficiently evaluate frame fatigue failure indicators. The effectiveness of this method was validated by combining the improved Goodman-Smith fatigue limit diagram and test bench fatigue tests, which helped identify the locations on the frame most prone to fatigue fractures. An Atom Search Optimization-BP Neural Network surrogate model was established with the objective of maximum material utilization, and the fatigue reliability of the bogie frame was obtained by combining the active learning function and the Monte Carlo method. The results show that the uncertainty design parameters greatly impact the fatigue reliability of critical welded structures. The proposed method improves the accuracy and efficiency of the fatigue reliability analysis of the bogie frame.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"190 ","pages":"Article 108632"},"PeriodicalIF":5.7,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Predicting fatigue life of multi-defect materials using the fracture mechanics-based physics-informed neural network framework 利用基于断裂力学的物理信息神经网络框架预测多缺陷材料的疲劳寿命

IF 5.7 2区材料科学

International Journal of Fatigue Pub Date : 2024-10-02 DOI: 10.1016/j.ijfatigue.2024.108626

Yingxuan Dong , Xiaofa Yang , Dongdong Chang , Qun Li

{"title":"Predicting fatigue life of multi-defect materials using the fracture mechanics-based physics-informed neural network framework","authors":"Yingxuan Dong , Xiaofa Yang , Dongdong Chang , Qun Li","doi":"10.1016/j.ijfatigue.2024.108626","DOIUrl":"10.1016/j.ijfatigue.2024.108626","url":null,"abstract":"<div><div>To address the limitations of traditional methods (such as the S-N curves and Paris’s law) in evaluating the fatigue life of multi-defect materials, this study developed a fracture mechanics-based physics-informed neural network (PINN) to predict the lifetime of multi-defect materials using cyclic loading (Δσ) and the equivalent damage area (<em>A<sub>D</sub></em>). Influences of multiple defects were unified characterized through the equivalent damage area, which was calculated based on the <em>M</em>−integral fatigue model. This model reflects the energy evolution of multi-defect fatigue damage. By embedding the prior knowledge of fracture mechanics derived from the <em>M</em>−integral fatigue model into the loss function of PINN, crucial physical information was captured during the training progress, enhancing the interpretability of the neural network. By integrating the advantage of the <em>M</em>−integral fatigue model in characterizing the fatigue performance of multi-defect materials and the nonlinear fitting ability of neural networks, the proposed approach effectively improves the generalization ability and predictive accuracy of limited fatigue data. The presented PINN models accurately forecast the fatigue life of multi-defect materials, with a squared correlation coefficient (<em>R</em><sup>2</sup>) exceeding 0.9. The presented methodological framework addresses the existing gap in methods for evaluating the fatigue performance of multi-defect materials and reliance on fatigue testing.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"190 ","pages":"Article 108626"},"PeriodicalIF":5.7,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Damage mechanics coupled with a transfer learning approach for the fatigue life prediction of bronze/steel diffusion welded bimetallic material 损伤力学与迁移学习法结合用于青铜/钢扩散焊接双金属材料的疲劳寿命预测

IF 5.7 2区材料科学

International Journal of Fatigue Pub Date : 2024-10-02 DOI: 10.1016/j.ijfatigue.2024.108631

Qianyu Xia , Chenhao Ji , Zhixin Zhan , Xiaojia Wang , Zhi Bian , Weiping Hu , Qingchun Meng

{"title":"Damage mechanics coupled with a transfer learning approach for the fatigue life prediction of bronze/steel diffusion welded bimetallic material","authors":"Qianyu Xia , Chenhao Ji , Zhixin Zhan , Xiaojia Wang , Zhi Bian , Weiping Hu , Qingchun Meng","doi":"10.1016/j.ijfatigue.2024.108631","DOIUrl":"10.1016/j.ijfatigue.2024.108631","url":null,"abstract":"<div><div>The bronze/steel diffusion welded (BSDW) bimetallic material is often applied in the rotors of piston pumps to withstand complex alternating loads under high-speed operating conditions. Although diffusion welding is a type of solid-phase welding method to achieve high-quality material connections, the fatigue problems still deserve our attention, especially the very high cycle fatigue (VHCF) and high cycle fatigue (HCF) problems. However, due to the high cost of obtaining data, it is necessary to find an efficient and high-precision fatigue life prediction method for diffusion welded materials with a small sample size. In this study, a novel method continuum damage mechanics − transfer learning method (CDM-TLM) for fatigue life prediction of BSDW material is proposed based on the transfer learning (TL) and continuum damage mechanics − finite element method (CDM-FEM). In comparison with the test results, the predicted values of BSDW material fatigue life all fall within the twice error band of the median values of the test life. The influence of frozen layers during TL and training samples in source and target models on the prediction performance is further discussed. CDM-TLM is an effective life prediction method for high-precision life prediction of BSDW material with a small sample size.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"190 ","pages":"Article 108631"},"PeriodicalIF":5.7,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

3D in situ observations of stress redistribution in Ti-6Al-4V within rogue grain neighborhoods during monotonic and cyclic loading 单调加载和循环加载过程中 Ti-6Al-4V 晶粒邻域内应力再分布的三维原位观测

IF 5.7 2区材料科学

International Journal of Fatigue Pub Date : 2024-10-01 DOI: 10.1016/j.ijfatigue.2024.108630

Kenneth M. Peterson , Michelle Harr , Adam Pilchak , S. Lee Semiatin , Nathan Levkulich , Jacob Ruff , Darren C. Pagan

{"title":"3D in situ observations of stress redistribution in Ti-6Al-4V within rogue grain neighborhoods during monotonic and cyclic loading","authors":"Kenneth M. Peterson , Michelle Harr , Adam Pilchak , S. Lee Semiatin , Nathan Levkulich , Jacob Ruff , Darren C. Pagan","doi":"10.1016/j.ijfatigue.2024.108630","DOIUrl":"10.1016/j.ijfatigue.2024.108630","url":null,"abstract":"<div><div>Grain-scale stress redistribution events are characterized within the Ti-6Al-4V (Ti64) hexagonal close-packed <span><math><mi>α</mi></math></span> phase using far-field high-energy X-ray diffraction microscopy. Specimens were deformed in monotonic uniaxial tension and under cyclic tensile loading with approximately 7000 grains probed in each specimen. Analyses focused on the evolution of the resolved shear stresses applied to the basal <span><math><mrow><mo>〈</mo><mi>a</mi><mo>〉</mo></mrow></math></span>, prismatic <span><math><mrow><mo>〈</mo><mi>a</mi><mo>〉</mo></mrow></math></span>, and pyramidal <span><math><mrow><mo>〈</mo><mi>c</mi><mo>+</mo><mi>a</mi><mo>〉</mo></mrow></math></span> slip systems, as well as normal stresses applied to basal planes, within individual grains. Slip system softening is observed in the basal <span><math><mrow><mo>〈</mo><mi>a</mi><mo>〉</mo></mrow></math></span> and prismatic <span><math><mrow><mo>〈</mo><mi>a</mi><mo>〉</mo></mrow></math></span> slip systems across the ensemble, while hardening is observed for the pyramidal <span><math><mrow><mo>〈</mo><mi>c</mi><mo>+</mo><mi>a</mi><mo>〉</mo></mrow></math></span> slip systems during both monotonic and cyclic loading. In addition, discrete stress redistribution events in which increases of normal stresses in grains not favorably oriented for slip that may lead to crack initiation are analyzed. It is observed that these increases in normal stresses are correlated to crystallographic slip in multiple neighboring grains favorably oriented for slip.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"190 ","pages":"Article 108630"},"PeriodicalIF":5.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fatigue crack growth rate behaviour of aluminium matrix composites reinforced with hollow glass microsphere 用空心玻璃微球增强的铝基复合材料的疲劳裂纹增长率特性

IF 5.7 2区材料科学

International Journal of Fatigue Pub Date : 2024-09-29 DOI: 10.1016/j.ijfatigue.2024.108628

Karthick Ganesan , Ganesan Somasundaram Marimuthu , Shekhar Hansda , Vasantha Kumar Ramesh , Satheesh Mani , Balaji Thangapandi

{"title":"Fatigue crack growth rate behaviour of aluminium matrix composites reinforced with hollow glass microsphere","authors":"Karthick Ganesan , Ganesan Somasundaram Marimuthu , Shekhar Hansda , Vasantha Kumar Ramesh , Satheesh Mani , Balaji Thangapandi","doi":"10.1016/j.ijfatigue.2024.108628","DOIUrl":"10.1016/j.ijfatigue.2024.108628","url":null,"abstract":"<div><div>This study investigates nanoindentation and fatigue crack growth rates of pure aluminium and aluminium hollow glass microsphere metal matrix composite (Al + HGM MMCs) cast plates. Using the stir casting method, pure aluminium, and Al + HGM MMCs were fabricated with hollow glass microsphere (HGM) additions ranging from 5 % to 30 % by weight. Nanoindentation techniques were utilized to assess fundamental mechanical properties such as hardness and elastic modulus. This study primarily focuses on analyzing fatigue crack growth behaviour within the linear region of da/dN vs. ΔK graphs for these stir-cast plates. Chevron-notch CT specimens were prepared following ASTM E-647 standards, and the constant amplitude increasing ΔK method was employed to generate Paris curves. Furthermore, the research investigated the influence of stress ratios (R=0.1, 0.2, and 0.3) on the fatigue crack growth rate in both Pure Al and Al + HGM MMCs. The study also determined the threshold and critical stress intensity factor ranges (ΔK<sub>th</sub> and ΔK<sub>c</sub>) for these plates. Additionally, Paris constants (C, m) were calculated to characterize the fatigue behaviour of the cast plates. X-ray diffraction analysis was conducted to reveal dislocation densities, crystalline sizes, and micro-strain responses of the fatigue-fractured specimens. Moreover, SEM fractography analysis provided insights into the fracture behaviour and crack branching observed in both pure aluminium and Al + HGM MMCs plates.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"190 ","pages":"Article 108628"},"PeriodicalIF":5.7,"publicationDate":"2024-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0