International Journal of Fatigue最新文献

{"title":"Influence of preprocessing on the fatigue life prediction of scanned weld topologies","authors":"Georg Veile ,&nbsp;Julius Lotz ,&nbsp;Daniel Klöss ,&nbsp;Stefan Weihe","doi":"10.1016/j.ijfatigue.2026.109536","DOIUrl":"10.1016/j.ijfatigue.2026.109536","url":null,"abstract":"<div><div>This work quantifies the influence of preprocessing scanned weld topologies on the accuracy and scatter of fatigue life prediction. Based on 13 welded fatigue specimens, 99 weld topologies were created using different settings in preprocessing. Mesh convergence was achieved in FEA using elastic plastic material models. Common fatigue damage parameters (FDP), such as von Mises (vM), Smith-Watson-Topper (SWT), Fatemi-Socie (FS), and their gradient-based extensions were used to create 1089 fatigue life predictions for comparison with experimental fatigue life. The deviation of fatigue life prediction is defined as the logarithmic fraction of experimental and predicted fatigue life. This paper examines the influence of different approaches when scan data is transformed to a solid in FEA. Increasing the number of Non-Uniform Rational B-Splines (NURBS) patches in preprocessing to 250 resulted in smaller radii r (in mm) {r| 0.05 ≤ r ≤ 0.19}. Reducing this number to 10 increased the interval to {r| 0.07 ≤ r ≤ 0.44}. With a reduction of NURBS nodes the deviation of common FDP of ca. 3 decreased by a third. Gradient based FDP were not affected to a comparable magnitude with a deviation closer to null. By manual displacement of NURBS nodes the radii increased to {r| 0.76 ≤ r ≤ 2.24}. Here, deviation of common FDP decreased over 50 % while gradient based extension of SWT resulted in the best deviation of 0.042. It is evident that the user-influence on the preprocessing stage, whether conscious or unconscious, has a substantial impact on the fatigue life prediction.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"208 ","pages":"Article 109536"},"PeriodicalIF":6.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134464","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":"Experimental investigation and modeling of the superalloy crack growth behavior under combined high and low cycle fatigue","authors":"Han Yan ,&nbsp;Dawei Huang ,&nbsp;Aofei Li ,&nbsp;Zhenyu He ,&nbsp;Heming Xu ,&nbsp;Naixian Hou ,&nbsp;Xiaojun Yan","doi":"10.1016/j.ijfatigue.2026.109553","DOIUrl":"10.1016/j.ijfatigue.2026.109553","url":null,"abstract":"<div><div>The disk groove structure of aero engines is affected by combined high and low cycle fatigue (CCF) loads during service, and the crack growth rate model is a critical input condition for the damage tolerance analysis of the disk. In this study, the crack propagation behavior of the Inconel 718 superalloy, a commonly used material for disks, is investigated under the CCF loads. Firstly, crack propagation tests are conducted on the superalloy under three loading conditions: pure low cycle fatigue (LCF), pure high cycle fatigue (HCF), and CCF. The influence of different loads on the crack growth rate is analyzed. Then, considering the coupling effect of the HCF and LCF loads, a CCF equivalent stress intensity factor <em>K</em>_eq is proposed. A crack growth rate model is developed based on the <em>K</em>_eq. The predicted crack growth rates fall within the 1.7-fold dispersion band. Furthermore, the influence mechanism of the stress ratio and CCF loads on crack propagation is explored through fracture analysis, revealing that under CCF loads, the high cycle component significantly governs the crack propagation process. This study can provide valuable methods and data support for evaluating the crack propagation life of the groove structure.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"208 ","pages":"Article 109553"},"PeriodicalIF":6.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135261","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":"Influence of inelastic strain in meso-structure on fatigue behavior of polyamide glass fiber woven composites","authors":"Ebrahim Ebrahimi ,&nbsp;Mohammad Nazmus Saquib ,&nbsp;Edwing Chaparro-Chavez ,&nbsp;Diego Pedrazzoli ,&nbsp;Mingfu Zhang ,&nbsp;Oleksandr G. Kravchenko","doi":"10.1016/j.ijfatigue.2026.109551","DOIUrl":"10.1016/j.ijfatigue.2026.109551","url":null,"abstract":"<div><div>This study investigates the fatigue behavior and evolution of inelastic effects in 2/2 twill PA6 woven glass fiber composites under low-cycle fatigue (LCF) and high-cycle fatigue (HCF) regimes. A hybrid fatigue life model combining power-law and exponential components was developed to improve fatigue life prediction. To characterize the role of viscoplasticity and damage in fatigue mechanisms, a comprehensive experimental and modeling approach was adopted. Cyclic stress–strain responses, secant modulus evolution, and energy dissipation were used to capture stiffness degradation and inelastic effects. Digital image correlation (DIC) was employed to map local strain distributions and identify regions of elevated viscoplastic deformation within the woven <em>meso</em>-structure, particularly between the longitudinal and transverse yarns. Finite element analysis (FEA) provided <em>meso</em>-scale insights into local stress and strain fields, while micro-computed tomography (microCT) was used to assess internal damage accumulation and validate the modeling framework. The integration of DIC, FEA, and microCT enabled a detailed investigation of the relationships between local deformation, <em>meso</em>-structural features, and global fatigue response. At a high level, the results reveal distinct damage mechanisms governing LCF and HCF, highlighting the roles of viscoplasticity, yarn orientation, and gradual stiffness degradation.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"208 ","pages":"Article 109551"},"PeriodicalIF":6.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134460","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":"A Bayesian physics-informed neural network model for probabilistic fatigue life assessment considering the size effect in additively manufactured materials","authors":"Qia Zhao ,&nbsp;Jing Cao ,&nbsp;Boda Wang ,&nbsp;Yuan Tao ,&nbsp;Xiang Xie ,&nbsp;Weixing Yao","doi":"10.1016/j.ijfatigue.2026.109526","DOIUrl":"10.1016/j.ijfatigue.2026.109526","url":null,"abstract":"<div><div>This study investigates the pronounced size effect in high-cycle fatigue of additively manufactured metallic specimens and proposes a probabilistic fatigue life assessment approach that combines a size-effect physical model with a Bayesian neural network (BNN). The model takes two physical-model parameters and the applied stress level as inputs, with these two parameters jointly capturing the influences of specimen size, defect characteristics, and Vickers hardness. By normalizing these inputs, the BNN is able to learn fatigue response patterns in a concise yet comprehensive manner. Statistical fatigue test data are used to construct training, validation, and test sets, followed by a systematic hyperparameter search to determine the optimal model configuration for the dataset in this study. Cross-validation is then performed on three different materials with a total of eight specimen sizes. The results show that the proposed Bayesian Physics-Informed Neural Network model delivers reliable fatigue life predictions across multi-material and multi-size conditions, demonstrating strong generalization capability.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"208 ","pages":"Article 109526"},"PeriodicalIF":6.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134455","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":"Progressive fatigue damage modeling for FRP in high cycle and very high cycle fatigue regimes","authors":"Gen Li ,&nbsp;Xiaorui Liu ,&nbsp;Hao Li ,&nbsp;Tianyu Chen ,&nbsp;Zhengmao Yang ,&nbsp;Huan Tu ,&nbsp;Rubing Zhang","doi":"10.1016/j.ijfatigue.2026.109543","DOIUrl":"10.1016/j.ijfatigue.2026.109543","url":null,"abstract":"<div><div>A progressive fatigue damage model is proposed in this paper to model the FRP fatigue behaviors and damage progression in high cycle and very high cycle fatigue (HCF and VHCF) regimes. Firstly, a new stiffness degradation model is proposed and validated for FRP stiffness degradation behaviors in HCF and VHCF regimes. Then the progressive fatigue damage model is generated by combining anisotropic elastic equations, the new stiffness degradation model, strength degradation model and failure criterion. The progressive fatigue damage model is applicable to model uniaxial and bending fatigue behavior of FRP, and determine different failure modes as fiber tensile failure, matrix tensile failure and interface shear failure. The HCF and VHCF fatigue behaviors of GFRP and CFRP under uniaxial and bending fatigue loads are modeled by the progressive fatigue damage model on finite element software. The full field stress and stiffness data for the simulated fatigue specimens are provided, and the damage progression in HCF and VHCF regimes is quantified efficiently. The S-N curves, stiffness degradation process and failure behavior achieve good consistency with the uniaxial and bending fatigue test results. The proposed progressive fatigue damage model effectively extends the analysis approach for FRP fatigue behaviors and damage progression in HCF and VHCF regimes.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"208 ","pages":"Article 109543"},"PeriodicalIF":6.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134456","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":"Prediction of residual life and critical crack length using the forward/inverse machine learning based on the configurational force fatigue model","authors":"Yingxuan Dong ,&nbsp;Ran Liu ,&nbsp;Qun Li","doi":"10.1016/j.ijfatigue.2026.109525","DOIUrl":"10.1016/j.ijfatigue.2026.109525","url":null,"abstract":"<div><div>For mixed-mode fatigue cracks commonly found in engineering structures, classical empirical fatigue models struggle to accurately assess nonlinear propagation characteristics and fatigue life under complex stress states. To address this limitation, this study develops a physics-informed neural network (PINN) integrated with a configurational force fatigue model to predict mixed-mode fatigue crack propagation and remaining life in ductile metallic materials via a forward/inverse machine-learning framework. The proposed methodology overcomes the limited applicability of traditional fatigue models to mixed-mode cracking while enhancing the extrapolation capability of purely data-driven methods through physics-based constraints derived from fatigue crack growth mechanisms. Numerical results demonstrate accurate remaining life predictions for both mode-I and I-II mixed-mode fatigue cracks. Furthermore, based on the established correlation between the crack length and the residual life, a genetic algorithm is employed to perform the inverse machine learning process. The critical fatigue crack lengths for I-II mixed-mode cracks at various deflection angles are inversely identified from the zero remaining life. This work establishes a novel PINN framework based on the configurational force theory, achieving integrated and accurate predictions of both the propagation and remaining life of mixed-mode fatigue cracks.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"208 ","pages":"Article 109525"},"PeriodicalIF":6.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146095822","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":"Physical information-enhanced machine learning method for high cycle fatigue strength prediction of foreign object damaged aeroengine blades","authors":"Yuming Huang ,&nbsp;Yibo Shang ,&nbsp;Yu Fu ,&nbsp;Chen Wang ,&nbsp;Qiang Chen ,&nbsp;Yun He ,&nbsp;Qingyang Shen ,&nbsp;Weisi Gao ,&nbsp;Shifeng Wen ,&nbsp;Weifeng He ,&nbsp;Ming Li ,&nbsp;Zhifen Zhang ,&nbsp;Liucheng Zhou ,&nbsp;Zhenhua Zhao","doi":"10.1016/j.ijfatigue.2026.109540","DOIUrl":"10.1016/j.ijfatigue.2026.109540","url":null,"abstract":"<div><div>Foreign object damage (FOD) induced fatigue strength attenuation of aeroengine blades is a critical challenge in reliability design, as it is affected by the coupling of multiple factors such as foreign object characteristics, impact angle, and damage morphology. Experimental data in this context often suffer from limited sample size, significant noise, and incomplete feature coverage. Traditional physical empirical methods rely on simplified assumptions, struggling to adapt to nonlinear evolution of complex damage, while pure data-driven models lack physical constraints, tending to overfit or produce physically implausible predictions. To address these limitations, this study proposes a physics-informed enhanced machine learning method for FOD fatigue strength prediction. The core of physical information enhanced-XGBoost (PIE-XGBoost) lies in embedding physical priors from the Peterson empirical formula into the XGBoost loss function and precomputing theoretical fatigue strength using parameters such as damage depth and foreign object diameter as physical constraints throughout training. Additionally, an adaptive physical constraint strength mechanism is introduced to dynamically adjust regularization coefficients via training error, balancing physical constraint guidance in the early stages with data-driven optimization in the later stages. Finally, based on the simulated blade experimental data verification and analysis of FOD blades, the average error of PIE-XGBoost is 3.2%. Compared with the traditional physical empirical formula’s average error of 41.47%, PIE-XGBoost reduces the error by 38.27%, thus verifying the effectiveness of the method. Further application of this method to actual aeroengine blades can provide technical support for aeroengine maintenance, which has high engineering practical significance and application prospects.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"208 ","pages":"Article 109540"},"PeriodicalIF":6.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146769","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":"Achieving superior high-cycle fatigue resistance of an extruded TiAl alloy","authors":"Jiaqi Sheng ,&nbsp;Junke Ren ,&nbsp;Xiaodong Wang ,&nbsp;Hongwei Wang ,&nbsp;Yongfeng Liang ,&nbsp;Junpin Lin","doi":"10.1016/j.ijfatigue.2026.109532","DOIUrl":"10.1016/j.ijfatigue.2026.109532","url":null,"abstract":"<div><div>Herein, we present a significant breakthrough in processing TiAl alloys by demonstrating that a large-ratio hot extrusion process alone, without any subsequent heat treatment or surface treatment, can yield an exceptional strength-ductility, superior creep and fatigue resistance. The as-extruded TiAl alloy exhibits remarkably high fatigue strength of 700 MPa at room temperature and 648 MPa at 700°C, with a minimal performance gap between these temperatures indicating outstanding microstructural stability. Contrary to conventional wisdom, the absence of post-processing treatment did not compromise performance; instead, the finely tuned as-extruded microstructure provided superior resistance to thermal–mechanical degradation. The results showed that surface and subsurface crack nucleation failures were identified as two competing mechanisms that influenced the fatigue life of TiAl alloys. When failure was dominated by the subsurface cracks, the TiAl alloys exhibited a significantly longer fatigue life compared to failures initiated by surface cracks. The deformation mechanisms of dislocations and intersecting nanotwins in the γ phase were observed to play crucial roles in the fatigue fracture process. Concurrently, dislocations and antiphase domains within equiaxed α₂ grains were found to provide additional deformation capacity. There was a sharp drop in fatigue limit in high-temperature high-cycle fatigue. Transmission electron microscopy analysis revealed that this scatter primarily correlates with the degradation of the α₂ laths and the transformation of the ω₀ phase, when the critical stress value was exceeded.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"208 ","pages":"Article 109532"},"PeriodicalIF":6.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134454","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":"Fatigue of additively manufactured 18Ni300 maraging steel","authors":"Paschalis Adamidis,&nbsp;Antonios Tsakiris,&nbsp;Georgios Savaidis","doi":"10.1016/j.ijfatigue.2026.109529","DOIUrl":"10.1016/j.ijfatigue.2026.109529","url":null,"abstract":"<div><div>This study investigates the fatigue behavior of 18Ni300 maraging steel fabricated via Laser Powder Bed Fusion (LPBF) and subjected to a novel, cost-effective two-stage heat treatment performed in an air atmosphere. The specimens underwent solution annealing at 940°C for 1 h followed by aging at 490°C for 6 h. Monotonic tensile tests revealed that this thermal treatment significantly enhances mechanical strength, increasing the yield strength by 86% and the ultimate tensile strength by 70% compared to the as-built condition, although ductility decreases from 4.7% to 2.6%. Fatigue test results demonstrated superior fatigue resistance compared to similar datasets from literature for both as-built and conventionally heat-treated conditions. Microstructural analysis confirmed that the studied air-atmosphere thermal process effectively dissolved the laser-induced melt pool boundaries, resulting in a homogenized martensitic matrix, but with a notable fraction of reverted austenite. Fractographic examination identified that fatigue failure was driven predominantly by non-metallic inclusions located just beneath the surface. The findings suggest that while air-furnace heat treatment is a viable, low-cost method for restoring static strength, the fatigue life of AM maraging steel remains sensitive to oxide inclusions which persist as stress concentrators within the hardened matrix.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"208 ","pages":"Article 109529"},"PeriodicalIF":6.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089478","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":"Progressive fatigue failure analysis of open-hole composite laminates: High-fidelity simulations and an experimental study","authors":"Peyman Shabani ,&nbsp;Lucy Li ,&nbsp;Jeremy Laliberte","doi":"10.1016/j.ijfatigue.2026.109531","DOIUrl":"10.1016/j.ijfatigue.2026.109531","url":null,"abstract":"<div><div>A high-fidelity progressive fatigue damage model was developed to predict static strength, fatigue life, and post-fatigue residual strength of open-hole composite laminates. The framework integrates continuum damage mechanics with inter- and intralaminar cohesive zone modeling to capture intralaminar matrix cracking, delamination, and their interactions. The enhanced LaRC05 failure criteria were implemented to simulate fiber breakage, pull-out, kinking, crushing, splitting, and matrix cracking. To enable rapid model preparation, an Abaqus pre-processing plugin was created. The developed fatigue damage model can predict the behavior of the multidirectional laminate under arbitrary stress levels, stress ratios, and loading sequences using a limited experimental dataset of unidirectional laminates tested in the longitudinal, transverse, and shear directions. A block-loading approach combined with an adaptive cyclic-jump method was employed to reduce the computational costs of high-cycle fatigue simulations while preserving physical fidelity. The framework also enables element-wise tracking of residual stiffness and strength, which is valuable during the design stage for identifying fatigue-prone regions. The model was validated via experimental testing of IM7/977–3 [0/45/90/-45]_2s open-hole specimens under tensile and compressive static loadings, tension–tension (R = 0.1) and tension–compression (R = -1) fatigue loadings, as well as tensile and compressive residual static strengths of fatigued laminates. The predicted stress–strain responses, S–N curves, and residual tensile and compressive strengths agreed closely with the experimental results, demonstrating the model’s accuracy for virtual testing and life prediction of composite structures containing stress concentrators.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"208 ","pages":"Article 109531"},"PeriodicalIF":6.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134461","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}