{"title":"An Analytical Approach for the Near-Tip Field Around V-Notch in Orthotropic Materials","authors":"Adel Esmaeili, Amin Kuhzadmohammadi, Majid Safarabadi","doi":"10.1111/ffe.14475","DOIUrl":"https://doi.org/10.1111/ffe.14475","url":null,"abstract":"<div>\u0000 \u0000 <p>This study introduces a novel theoretical framework for determining the notch stress intensity factors (NSIFs) in composite materials. The approach involves utilizing Irwin's complex stress functions for Mode I and Mode II loading conditions. By investigating displacement and singular stress components around V-notch tips, the research aims to provide a comprehensive understanding of NSIFs in composite materials. Three different composite materials were considered in the study to explore the relationship between stress and material properties. The stress singularity order, denoted as \u0000<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>λ</mi>\u0000 </mrow>\u0000 <annotation>$$ lambda $$</annotation>\u0000 </semantics></math>, is determined through eigenequations. Moreover, explicit solutions for displacement and singular stress fields are derived for a more thorough understanding of the behavior around notches in composite materials. To validate the proposed theoretical framework, a rigorous numerical study is conducted using FEM on finite-size notches. The results obtained from the numerical simulations are compared with theoretical predictions to assess the accuracy and reliability of the developed approach.</p>\u0000 </div>","PeriodicalId":12298,"journal":{"name":"Fatigue & Fracture of Engineering Materials & Structures","volume":"48 1","pages":"487-501"},"PeriodicalIF":3.1,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142868108","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}
{"title":"Feature Transfer Learning for Fatigue Life Prediction of Additive Manufactured Metals With Small Samples","authors":"Hao Wu, Zhi-Ming Fan, Lei Gan","doi":"10.1111/ffe.14497","DOIUrl":"https://doi.org/10.1111/ffe.14497","url":null,"abstract":"<div>\u0000 \u0000 <p>A feature transfer learning (FTL)-based model is proposed to address small-sample problems in fatigue life prediction of additively manufactured (AM) metals. Transfer component analysis (TCA) is studied for data alignment before model training. Correspondingly, two TCA improvement strategies are further considered to aggregate training data from distinct AM processing conditions. An experimental database consisting of 103 fatigue data is built for model evaluation. The results demonstrate that the proposed model outperforms conventional machine learning models and other transfer learning-based models in terms of accuracy and data demand, showing good applicability for AM fatigue life assessment.</p>\u0000 </div>","PeriodicalId":12298,"journal":{"name":"Fatigue & Fracture of Engineering Materials & Structures","volume":"48 1","pages":"467-486"},"PeriodicalIF":3.1,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142868004","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}
Brenno L. Nascimento, Iris S. Santos, Luiara L. Santos, Matheus M. S. Reis, Ihana G. C. de Jesus, Sandro Griza
{"title":"Effect of Cyclic Load Frequency on the Fatigue Crack Nucleation and Growth of Annealed and Prestrained Austenitic SS 304","authors":"Brenno L. Nascimento, Iris S. Santos, Luiara L. Santos, Matheus M. S. Reis, Ihana G. C. de Jesus, Sandro Griza","doi":"10.1111/ffe.14484","DOIUrl":"https://doi.org/10.1111/ffe.14484","url":null,"abstract":"<div>\u0000 \u0000 <p>The austenitic stainless steels are widely used in several engineering fields due to their high ductility, corrosion and high temperature performance. Despite its noble properties, components manufactured in austenitic stainless steel are subject to fatigue failure. Studies indicate that loading frequency can impact the austenitic stainless steel fatigue performance. In this scenario, the present study aims to evaluate the effect of frequencies of 3 and 30 Hz on the fatigue behavior of SS 304 alloy under load control in order to identify in which fatigue stage the effect is outstanding. Therefore, fatigue and fracture mechanics tests were evaluated on the alloy annealed at 1000°C. Furthermore, fatigue tests were also applied to the alloy after previous tensile plastic strain of 0.5. The analyses denoted a significant reduction in fatigue strength with increasing frequency, especially for the strained alloy. Fatigue crack nucleation is encouraged with greater load frequency. This behavior may be attributed to strain-induced martensite and other strain mechanisms such as twinning and slip bands that are encouraged by lower strain rates but are relieved by auto-heating achieved in higher frequencies, as mentioned in the literature, which decrease the strength to fatigue nucleation.</p>\u0000 </div>","PeriodicalId":12298,"journal":{"name":"Fatigue & Fracture of Engineering Materials & Structures","volume":"48 1","pages":"441-453"},"PeriodicalIF":3.1,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869265","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}
Felipe Klein Fiorentin, Rita Dantas, Roya Darabi, Grzegorz Lesiuk, Miguel Figueiredo, Paulo Tavares de Castro, Abílio de Jesus
{"title":"Relation Between Striations Spacing and Fatigue Crack Growth Rates for Additive Manufactured Inconel 625","authors":"Felipe Klein Fiorentin, Rita Dantas, Roya Darabi, Grzegorz Lesiuk, Miguel Figueiredo, Paulo Tavares de Castro, Abílio de Jesus","doi":"10.1111/ffe.14493","DOIUrl":"https://doi.org/10.1111/ffe.14493","url":null,"abstract":"<div>\u0000 \u0000 <p>The principles of the mechanisms for fatigue crack propagation in metals have been established several decades ago. By definition, fatigue might be summarized as a damage process imparted to a material under the action of cyclic loads. The relation between fatigue crack growth rates (FCGRs) and formation of striation marks has been a controversial topic. Some authors stated that, in certain fatigue regimes, several fatigue cycles are required to form a single striation. The disagreement found was the motivation for the present work. This study's main goal is to provide a comparison between the striation spacing and the respective FCGR. These analyses will be performed in a Nickel superalloy, Inconel 625, obtained via directed energy deposition. Investigation of the striations spacing are compared with data obtained from FCGR tests. A good agreement between striation spacing and FCGRs was found to intermediate and large values of stress intensity factor.</p>\u0000 </div>","PeriodicalId":12298,"journal":{"name":"Fatigue & Fracture of Engineering Materials & Structures","volume":"48 1","pages":"454-466"},"PeriodicalIF":3.1,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869262","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}
Yazhou Xu, Yue Wu, Fang Yuan, Yangmin Feng, Bin Hao
{"title":"A Two-Scale Model of Fretting Fatigue Crack Initiation Life Based on Long Short-Term Memory Networks Improved by Genetic Algorithm","authors":"Yazhou Xu, Yue Wu, Fang Yuan, Yangmin Feng, Bin Hao","doi":"10.1111/ffe.14487","DOIUrl":"https://doi.org/10.1111/ffe.14487","url":null,"abstract":"<div>\u0000 \u0000 <p>Fretting fatigue is a common engineering failure phenomenon, often resulting in a shorter lifespan compared to plain fatigue. To consider the interaction between different scales, this study proposes a fully coupled two-scale model based on continuum damage mechanics (CDM) and the crystal plastic finite element method (CPFEM) for the fretting fatigue crack initiation. Furthermore, the life data series are generated by employing feature engineering and long short-term memory (LSTM) networks optimized with a genetic algorithm, ensuring the minimization of redundancy. Additionally, the genetic algorithm, enhanced by the Markov chain Monte Carlo method, was used to optimize the hyperparameters of the LSTM network. Simulation results indicate that the two-scale model offers improved accuracy in predicting crack initiation life and provides physical information of crack initiation from different scales simultaneously.</p>\u0000 </div>","PeriodicalId":12298,"journal":{"name":"Fatigue & Fracture of Engineering Materials & Structures","volume":"48 1","pages":"423-440"},"PeriodicalIF":3.1,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869264","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}
{"title":"Impact of SCB Specimen Size, Temperature, Loading Rate, and Loading Mode on Fracture Behavior of Asphalt Mixture Using Response Surface Method","authors":"Zahra Vaseghi, Sadjad Pirmohammad, Ramin Momeni","doi":"10.1111/ffe.14474","DOIUrl":"https://doi.org/10.1111/ffe.14474","url":null,"abstract":"<div>\u0000 \u0000 <p>This study aimed to investigate the influence of semicircular bend (SCB) specimen size (<i>R</i>), loading mode (<i>M</i><sup>e</sup>), and loading rate (<i>Lr</i>) on fracture resistance indicators, namely, fracture work (<i>W</i><sub>f</sub>), fracture energy (<i>G</i><sub>f</sub>), and fracture strength (<i>K</i><sub>f</sub>), of asphalt concrete at three different temperatures (−30°C, −20°C, and 10°C). Using Minitab software, response surface methodology (RSM) under central composite design (CCD) was employed to design experiments and develop predictive models for <i>W</i><sub>f</sub>, <i>G</i><sub>f</sub>, and <i>K</i><sub>f</sub> in terms of <i>R</i>, <i>M</i><sup>e</sup>, and <i>Lr</i> at each temperature. The results demonstrated that the RSM models accurately predicted the fracture test data for all temperatures. The analysis of variance (ANOVA) revealed that <i>R</i>, <i>M</i><sup>e</sup>, and <i>Lr</i> significantly influenced <i>W</i><sub>f</sub>, <i>G</i><sub>f</sub>, and <i>K</i><sub>f</sub> at each temperature, whereas the square terms <i>R</i><sup>2</sup>, <i>M</i><sup>e2</sup>, and <i>Lr</i><sup>2</sup> were not significant. The significance of two-way interaction terms varied across different responses and temperatures. Overall, the experiments conducted at −30°C, −20°C, and 10°C indicated that varying <i>R</i>, <i>Lr</i>, and <i>M</i><sup>e</sup> had notable effects on <i>W</i><sub>f</sub>, <i>G</i><sub>f</sub>, and <i>K</i><sub>f</sub>. Increasing <i>R</i> and <i>M</i><sup>e</sup> while decreasing <i>Lr</i> resulted in an increase in <i>W</i><sub>f</sub> and <i>G</i><sub>f</sub>. Furthermore, <i>K</i><sub>f</sub> exhibited a direct relationship with <i>R</i> and <i>Lr</i> but an inverse relationship with <i>M</i><sup>e</sup>.</p>\u0000 </div>","PeriodicalId":12298,"journal":{"name":"Fatigue & Fracture of Engineering Materials & Structures","volume":"48 1","pages":"382-403"},"PeriodicalIF":3.1,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869227","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}
{"title":"Research on the P-S-N Curve Fitting Method of Notched Specimens Considering Small Sample Properties","authors":"Ziyang Zhang, Jianhui Liu, Juntai Hu, Qingjun Wu, Shenglei Wu","doi":"10.1111/ffe.14490","DOIUrl":"https://doi.org/10.1111/ffe.14490","url":null,"abstract":"<div>\u0000 \u0000 <p>Aiming at the issue of fatigue test data for large-scale mechanical components of building steel are very limited, a method for fitting <i>P-S-N</i> curves under small sample data of notched specimens is proposed to predict fatigue life. First, a fatigue life subsample augmented and its reliability assessment method are established, based on Bayesian hierarchical modeling and modified Monte Carlo method. Second, a clustering combination weighting method is proposed, to define weights of hidden variables of the binomial mixture Weibull distribution, and the expectation–maximization algorithm is used to determine probability density function of the distribution. Finally, the <i>P-S-N</i> curves under various failure probabilities are fitted with Weibull distributed life models, and the convergence and prediction accuracy of the different models are compared. The results show that the fatigue data of small samples can be predicted better by using mixed Weibull distribution, and the fitting <i>P-S-N</i> curve is more reliable and accurate.</p>\u0000 </div>","PeriodicalId":12298,"journal":{"name":"Fatigue & Fracture of Engineering Materials & Structures","volume":"48 1","pages":"404-422"},"PeriodicalIF":3.1,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869228","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}
{"title":"Statistical Lifetime of Composites Subjected to Random and Ordered Block Loadings","authors":"Alberto D'Amore, Luigi Grassia","doi":"10.1111/ffe.14488","DOIUrl":"https://doi.org/10.1111/ffe.14488","url":null,"abstract":"<div>\u0000 \u0000 <p>This study presents a procedure based on constant amplitude (CA) fatigue data to predict the statistical fatigue lifetime of glass/orthopolyester composites subjected to repeated ordered and random two, three, and six sequences of block loadings. A numerical routine was developed to detect cycle-by-cycle the statistical strength degradation progression until failure, assuming that the strength at the end of a block cycle equals the strength at the start of the successive one and that the individual samples' static strength, the amount of degraded strength, and fatigue life share the same rank in their respective cumulative distribution function. Predictions conform to the statistically undetectable loading sequence effects and lightly overestimate the lifetimes of random and ordered high-to-low (1/100 cycles) repeated two-block loadings. The vanishing effect of the loading sequence when the block extents remain fixed, the block extent effects for a given three-block sequence, and the lifetimes of three-block loadings were fully predicted. The six-block sequence's experimental lifetimes with different block loading orders and block extent fell within the predicted lifetimes' cumulative distribution function. A reliable damage rule based on residual strength was proposed and compared to the Miner's rule.</p>\u0000 </div>","PeriodicalId":12298,"journal":{"name":"Fatigue & Fracture of Engineering Materials & Structures","volume":"48 1","pages":"359-370"},"PeriodicalIF":3.1,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869225","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}
{"title":"Effect of Surface Roughness and Compressive Residual Stress on the Fatigue Performance of TC4 Titanium Alloy Subjected to Laser Shock Wave Planishing","authors":"Lei Wu, FengZe Dai, XiZhang Chen","doi":"10.1111/ffe.14472","DOIUrl":"https://doi.org/10.1111/ffe.14472","url":null,"abstract":"<div>\u0000 \u0000 <p>The milled surface of TC4 titanium alloy was treated by laser shock peening (LSP) and laser shock wave planishing (LSWP) to investigate the effect of compressive residual stress (CRS) and surface roughness (SR) on the vibration fatigue performance. The results demonstrate that although the amplitude of CRS induced by LSWP is lower than that of LSPed specimens, the vibration fatigue life of LSWPed specimens increased by 63.78% due to a significant reduction in SR from Sa 14.1 μm to Sa 4.21 μm. When the SR is low, increasing the amplitude of CRS is more advantageous to enhance fatigue life. The fractographic analysis further confirmed that compared with LSPed and T0.2-LSWPed specimens, T0.1-LSWPed specimens have considerably less initial fatigue crack initiation, and the crack initiation location is deeper. The fatigue striation spacing of T0.1-LSWPed specimens is the smallest (0.25 μm), greatly lowering the fatigue crack growth rate.</p>\u0000 </div>","PeriodicalId":12298,"journal":{"name":"Fatigue & Fracture of Engineering Materials & Structures","volume":"48 1","pages":"371-381"},"PeriodicalIF":3.1,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869226","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}
Congzhuo Fang, Yanfu Chen, Zihao Yang, Yiyuan Zhang, Xindang He
{"title":"Prediction of Rubber Fatigue Life Using an Assimilation-based Learning Approach and Incremental Crack Propagation Model","authors":"Congzhuo Fang, Yanfu Chen, Zihao Yang, Yiyuan Zhang, Xindang He","doi":"10.1111/ffe.14495","DOIUrl":"https://doi.org/10.1111/ffe.14495","url":null,"abstract":"<div>\u0000 \u0000 <p>Accurately and efficiently predicting the fatigue life of rubber materials has been a long-standing challenge due to limited understanding of the fatigue mechanism. In this study, a variational assimilation-based machine learning method assisted with incremental crack propagation model is proposed to predict the fatigue life of rubber materials. Firstly, according to the fracture mechanics theory, a new rubber fatigue life prediction model based on incremental crack propagation and sparse experimental data is established, which owns higher accuracy than the classical crack energy density model. Further, a rubber fatigue life solver coupled incremental crack propagation model and nonlinear finite element method is introduced to generate a dense fatigue life dataset of rubber materials with high accuracy. Finally, the artificial neural network model is trained, cross-validated, and tested using the dense dataset, and the three-dimensional variational assimilation model is employed to merge the predicted values of artificial neural network with experimental data. By comparing against the experimental data, the effectiveness of the proposed method was verified; thereby, we offer an accurate and efficient approach to predict the rubber fatigue life.</p>\u0000 </div>","PeriodicalId":12298,"journal":{"name":"Fatigue & Fracture of Engineering Materials & Structures","volume":"48 1","pages":"312-323"},"PeriodicalIF":3.1,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869211","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}