International Journal of Fatigue最新文献

{"title":"An automated method for interpreting fatigue fracture surfaces with marker load based on computer vision and artificial neural networks","authors":"Jinyu Wang,&nbsp;Xiaofan He,&nbsp;Hao Xin,&nbsp;Zhongwen Tao,&nbsp;Zhen Jia","doi":"10.1016/j.ijfatigue.2025.109471","DOIUrl":"10.1016/j.ijfatigue.2025.109471","url":null,"abstract":"<div><div>The marker load method, recognized as one of the most effective approaches for reproducing the three-dimensional fatigue crack growth process in alloys, has been widely applied in theoretical and experimental studies of fatigue crack gross in reusable flight vehicle structures. However, this method suffers from low efficiency and poor accuracy in interpreting marker lines on fatigue fracture surfaces. In this study, an automatic method for marker line recognition and local defect completion is developed based on computer vision and artificial neural network techniques to enhance the efficiency and accuracy of crack interpretation, thereby strengthening the capability of the marker load method in extracting crack front (effective only for single-source cracks, multi-source cracks require further investigation.). Specifically, a convolutional neural network algorithm (constructed on the <em>you only look once</em> (YOLO) v8 framework) is first employed to identify continuous marker lines as a series of discrete coordinate points according to their geometric features. Subsequently, the density-based spatial clustering of applications with noise (DBSCAN) algorithm, combined with a newly developed scatter cluster matching algorithm, is used to cluster and match the points belonging to the same crack front. Finally, a long short term memory (LSTM) neural network model is utilized to reconstruct incomplete marker lines, establishing an automatic interpretation method for fatigue fracture marker lines and compensating for the loss of crack information caused by marker line defects (crack source need to be selected manually).</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"206 ","pages":"Article 109471"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881309","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":"Multi-mechanism crystal plasticity-based finite element framework uncovering the tensile and fatigue behavior of Ni-based single crystal superalloy","authors":"Yuanyuan Wang ,&nbsp;Donghai Yu ,&nbsp;Changjian Geng ,&nbsp;Xianglin Zhou ,&nbsp;Shilei Li ,&nbsp;Yan-Dong Wang","doi":"10.1016/j.ijfatigue.2025.109456","DOIUrl":"10.1016/j.ijfatigue.2025.109456","url":null,"abstract":"<div><div>A multi-mechanism crystal plasticity finite element (CPFE) model is developed to capture the micromechanical deformation and fatigue behavior of <em>γ</em>′-strengthened [001]-oriented Ni-based single-crystal (Ni-based SX) superalloy across a wide temperature range. The model integrates lattice friction and dislocation resistance for both <em>γ</em> and <em>γ</em>′ phases to reproduce hardening characteristics. In the <em>γ</em> matrix, microstructual features such as <em>γ</em> channel width are introduced to determine the initial slip resistance, while the strengthening effect associated with dislocation bypass of <em>γ</em>′ precipitate is incorporated through an Orowan mechanism. The critical <em>γ</em>/<em>γ</em>′ phase interaction is represented by back stress arising from dislocation pileup at the phase boundary. For the <em>γ</em>′ phase, the resistance to anti-phase boundary (APB) shearing is explicitly considered to account for the additional stress required for dislocation motion within the ordered structure. Model parameters are calibrated through temperature-dependent tensile tests using the genetic algorithm (GA) to minimize discrepancies between simulated and experimental stress–strain responses. The model reliably reproduces the stress–strain response, clarifying the contribution of distinct deformation mechanisms, and accurately captures the evolution of hysteresis loops, which exhibit a plastic-to-elastic transition at 760 ℃ and a fully elastic regime at 900 ℃. Finally, an empirical energy-based approach is employed to predict fatigue life across different temperatures and strain amplitudes, achieving good agreement with our experimental results.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"206 ","pages":"Article 109456"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823057","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":"Mechanism of high-cycle fatigue enhancement of TiAl alloys via shot peening","authors":"Jiaqi Sheng ,&nbsp;Lin Song ,&nbsp;Dong Lu ,&nbsp;Chao Yang ,&nbsp;Yongfeng Liang ,&nbsp;Junpin Lin","doi":"10.1016/j.ijfatigue.2025.109420","DOIUrl":"10.1016/j.ijfatigue.2025.109420","url":null,"abstract":"<div><div>This work comprehensively investigates the enhancement mechanism of shot peening (SP) from multiple perspectives, aiming to provide a systematic approach to improving the high-cycle fatigue performance of TiAl alloys. Experimental results demonstrate that SP treatment of 0.45 mmN increased the fatigue life by up to 2.8 times at a high stress of 800 MPa. At the macroscopic level, stress concentration factors and surface roughness were quantitatively analyzed to evaluate the surface quality of TiAl alloys. Fatigue fracture analysis indicated that cracks originated exclusively subsurface in SP samples due to the introduction of residual compressive stress (RCS). Furthermore, the beneficial effects of residual compressive stress were found to outweigh the adverse effects of increased surface roughness at higher SP intensities. At the microstructure level, this study reports for the first time that the long-period stacking ordered (LPSO) structure in TiAl alloys subjected to SP originates from severe plastic deformation caused by high-velocity projectile impact. Two distinct LPSO phase distributions were identified: (i) 6H-type laths within equiaxed α grains, and (ii) 9R/18R-type laths in the γ phase. When the strain increases, the complex crystal defect networks formed by intersection nanotwins and LPSO phases acts as an effective “pinning” mechanism and worked synergistically with RCS, enhancing fatigue resistance.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"206 ","pages":"Article 109420"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145657135","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 pseudo-damage-constrained data–model fusion method for dynamic load spectrum estimation in electric-drive assemblies","authors":"Peng Liu,&nbsp;Haoyuan Li,&nbsp;Hailong Tian,&nbsp;Lai Wei,&nbsp;Yunshenghao Qiu","doi":"10.1016/j.ijfatigue.2025.109445","DOIUrl":"10.1016/j.ijfatigue.2025.109445","url":null,"abstract":"<div><div>Dynamic load spectra for electric-drive assemblies are difficult to estimate from road tests because the signals are non-stationary, non-Gaussian, and noisy. We propose a pseudo-damage-constrained data–model fusion framework that reconstructs torque/load histories while preserving rainflow counting and fatigue consistency. The approach combines trend extraction with nonlinear state estimation and an innovation-based adaptive step that enforces pseudo-damage equivalence to the raw signal within a controlled tolerance. Extreme-value fits are used only as tail diagnostics to verify that rare high-load behavior is preserved; they are not involved in cycle counting. On representative road data, the method achieved a Peak–Valley Preservation Rate ≈93% and the lowest weighted-MAPE (26.2%) among EKF, PF, KalmanNet, and LSTM baselines, with clear gains in fatigue-critical mid–high levels and no inflation of the spectrum tail. The results indicate that the proposed framework yields higher-fidelity spectra for durability analysis and test-bench replay while keeping established fatigue rules (four-point rainflow with Goodman correction) unchanged.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"206 ","pages":"Article 109445"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145784901","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 new empirical model for mode I fatigue delamination of composite laminates considering fiber bridging and stress ratio effects","authors":"Luohuan Zou ,&nbsp;Yu Gong ,&nbsp;Dingli Tian ,&nbsp;Sizhuo Hao ,&nbsp;Jianyu Zhang ,&nbsp;Libin Zhao ,&nbsp;Ning Hu","doi":"10.1016/j.ijfatigue.2025.109469","DOIUrl":"10.1016/j.ijfatigue.2025.109469","url":null,"abstract":"<div><div>Delamination usually occurs and grows in composite laminates under fatigue loading. The stress ratio is an important factor, while its influence law has no consensus yet. In this paper, to fully investigate the influence of fiber bridging and stress ratio on the fatigue delamination behavior, mode I fatigue delamination tests under two stress ratios (0.1 and 0.5) are conducted. Test results reveal that, the initial and steady-state values of the fatigue R-curve are consistent with those of quasi-static ones, while there are significant differences in the growth stage of fiber bridging. Furthermore, it is found that, the slope and intercept of the d<em>a</em>/d<em>N</em>-<em>G_max</em> curves vary under different stress ratios. A novel four-parameter fatigue model considering fiber bridging and stress ratio effects is proposed. The proposed model is compared with other classical models in literatures using the fatigue data of two stress ratios (0.1 and 0.5). It is found that the proposed model can well characterize fatigue delamination behavior. To further verify the model applicability, fatigue tests under stress ratio of 0.3 are supplemented. The predicted d<em>a</em>/d<em>N</em>-<em>G_max</em> curves by the model and experimental results are compared with a 95% confidence interval, which indicates that the proposed model has good applicability and can provide an effective method for fatigue delamination prediction.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"206 ","pages":"Article 109469"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145895491","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 physics-informed machine learning approach for onset life prediction of mode I fatigue delamination in CFRP laminates","authors":"Liheng Tian ,&nbsp;Yu Gong ,&nbsp;Hao Liu ,&nbsp;Sizhuo Hao ,&nbsp;Jianyu Zhang ,&nbsp;Libin Zhao ,&nbsp;Ning Hu","doi":"10.1016/j.ijfatigue.2025.109442","DOIUrl":"10.1016/j.ijfatigue.2025.109442","url":null,"abstract":"<div><div>This study proposes a physics-informed machine learning framework to predict the delamination onset life of unidirectional carbon fiber-reinforced plastic laminates under mode I fatigue loading. Traditional methods are limited by the simplified assumptions of physical models or the risks of underfitting caused by purely data-driven models, making it challenging to achieve high-precision predictions under small-sample conditions. By combining experimental data obtained from quasi-static test and fatigue test, this study develops a normalized <em>G-N</em> curve model considering fiber bridging effect, which is incorporated into the loss function of the neural networks to improve predictive robustness and model transparency. Predictions demonstrate that the physics-informed machine learning model exhibits significantly lower prediction deviations in the low-life region (around <em>N</em> = 10³) compared to both purely data-driven machine learning model and the proposed physical model, while maintaining stable predictive capability in the high-life region (<em>N</em> &gt; 10⁴). Compared to the pure data-driven model (R² = 0.8462), the R² value of the physics-informed machine learning increases to 0.9823, demonstrating the validity of the physics-data fusion approach. This method provides a high-precision solution for fatigue life prediction of unidirectional CFRP laminates, particularly suitable for rapid evaluation in engineering scenarios with insufficient data.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"206 ","pages":"Article 109442"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145731769","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":"Creep-fatigue interaction and hygrothermal aging effect on the fatigue behavior of carbon/glass hybrid fiber filament-wound tubes","authors":"Kangnan Zhu,&nbsp;Jiajun Shi,&nbsp;Anji Wang,&nbsp;Guijun Xian,&nbsp;Chenggao Li","doi":"10.1016/j.ijfatigue.2025.109470","DOIUrl":"10.1016/j.ijfatigue.2025.109470","url":null,"abstract":"<div><div>Carbon/glass hybrid fiber reinforced polymer (C/GFRP) tubes, which offer both high performance and cost-effectiveness, are often subjected to the synergistic effects of fatigue and creep during their service life as transportation carriers, which reduces the safety of the structure. This study investigates the tension–tension fatigue behavior of C/GFRP tubes under constant stress ratio at different stress levels. The influence of a hygrothermal environment on fatigue failure modes, fatigue life, and stiffness degradation was examined via laboratory accelerated aging (150 days of immersion in distilled water at 60 °C). The creep displacement evolution was investigated by experimental and analytical means. Finally, a modified fatigue stiffness degradation model accounting for creep effects was proposed based on the creep growth curve. During fatigue loading, the primary load-bearing responsibility gradually shifts from the resin to the fibers as the resin deforms. This transition alters the material’s viscoelastic behavior, evolving from resin-dominated viscoelasticity toward fiber-dominated elasticity. Consequently, the total energy dissipated per loading cycle significantly decreases. Hygrothermal aging alters the failure mode, causing irregular serrated matrix fractures due to interface degradation, and significantly reduces fatigue life. After 150 days of accelerated aging, the fatigue life retention rates of the C/GFRP tubes at stress levels of 0.50, 0.45, 0.40, and 0.38 were 16.3 %, 61.6 %, 57.1 %, and 45.8 %, respectively. Creep effects lead to increased stiffness during fatigue in tubes. The modified stiffness degradation model effectively characterizes the actual stiffness evolution of C/GFRP tubes during fatigue process by separating the cyclic creep.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"206 ","pages":"Article 109470"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881308","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":"Crack initiation mechanisms of linear friction welded dissimilar Ti60/TC17 joint in very high cycle fatigue regime at different temperatures","authors":"Tian Xu ,&nbsp;Huwei Qiu ,&nbsp;Wentao Huang ,&nbsp;Delong He ,&nbsp;Yao Chen ,&nbsp;Chong Wang ,&nbsp;Qingyuan Wang ,&nbsp;Jinbo Bai ,&nbsp;Fulin Liu ,&nbsp;Yongjie Liu","doi":"10.1016/j.ijfatigue.2025.109478","DOIUrl":"10.1016/j.ijfatigue.2025.109478","url":null,"abstract":"<div><div>To meet the application requirements for aero-engine Blisks, very high cycle fatigue (VHCF) behavior of Ti60/TC17 linear friction welded (LFW) joints was investigated at room temperature (RT) and high temperatures (HT). The results indicate that fatigue strength decreases with increasing temperature. Fatigue fractures predominantly occur in the weaker Ti60 base material at all test temperatures. Nearly all fatigue crack initiation sites are characterized by facet morphologies formed through the cleavage of α grains. Specifically, subsurface failures originate from an oversized facet, whereas internal failures arise from facet clusters. Microstructural analysis reveals that cracks primarily nucleate at the α/β phase interface and along slip bands within equiaxed α grains. Notably, high temperature significantly influences the crack initiation mechanism, causing a transition in facet formation from basal slip dominance at RT to synergistic basal and prismatic slip at HT. Furthermore, for subsurface crack initiation at HT, the synergistic effect of prolonged high-temperature exposure and dislocation-assisted oxygen diffusion facilitates brittle oxide formation at the crack tips, thereby accelerating fatigue failure.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"206 ","pages":"Article 109478"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894531","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 damage development and mechanical property degradation of pearlitic rail steel under loaded traffic","authors":"Manjiang Yu ,&nbsp;Ye Wang ,&nbsp;Fangli Duan ,&nbsp;Chaofeng Lü","doi":"10.1016/j.ijfatigue.2025.109474","DOIUrl":"10.1016/j.ijfatigue.2025.109474","url":null,"abstract":"<div><div>The service failure evaluation of the damaged rail can provide theoretical guidance for the routine maintenance of existing railway lines. In this work, U71MnG rail that failed under traffic loading is selected to investigate the fatigue damage mechanism of pearlitic rail steel. In addition to the conventional surface crack, the branch crack characterized by the ‘Y’ at the subsurface inclusion is also observed. Among them, the leading crack aligned with the rolling direction forms and propagates first, followed by the two trailing cracks propagating in the reverse rolling direction. Driven by the plastic ratcheting at the surface layer and the deeper bending deformation, these two trailing cracks may converge with other adjacent leading cracks, resulting in the formation of the spalling pit hundreds of μm deep. Moreover, the sliding friction in the transverse direction of the rail promotes the formation of wavy pearlite, which reduces the fracture toughness of the outside rail. In the predictive maintenance of rails, it is essential to promptly identify and address potential hazards of surface spalling and transverse fracture.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"206 ","pages":"Article 109474"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894535","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 life prediction of rocks under cyclic uniaxial compression using XGBoost and GBM based on Bayesian optimization","authors":"Pinduo Zhu ,&nbsp;Feng Dai ,&nbsp;Zelin Yan ,&nbsp;Dingran Song ,&nbsp;Hao Tan ,&nbsp;Pan Zhou","doi":"10.1016/j.ijfatigue.2025.109438","DOIUrl":"10.1016/j.ijfatigue.2025.109438","url":null,"abstract":"<div><div>In major underground engineering projects, rocks are frequently subjected to cyclic loadings, causing various engineering disasters. Therefore, accurately predicting the rock fatigue behaviors is important for rock engineering safety. Current methodologies like laboratory testing and numerical analysis all have limits like excessive test costs, limited applicability etc., demonstrating insufficient capability in predicting rock fatigue life. While artificial intelligence (AI) has brought new opportunities to such researches. In this study, six machine learning (ML) models including gradient boosting machine (GBM), extreme gradient boosting (XGBoost), along with other four models combined with bayesian optimization (BO) method are used to predict rock fatigue life. Initially, a dataset with 213 rock fatigue life experimental data is built with 8 parameters including maximum cyclic stress and its ratio, cyclic loading amplitude and its ratio, uniaxial compressive strength (UCS), frequency, waveform and rock type. Meanwhile, three error correlation coefficients including the mean absolute error (MAE), the root mean square error (RMSE) and the coefficient of determination (R²) are selected. The results indicate that prediction accuracy and feature importance are significantly influenced by algorithm types. Specifically, XGBoost and GBM demonstrate the superior predictive accuracy than other algorithms, with mean R² values of 0.9 and 0.88. For the eight parameters, maximum cyclic stress and its ratio exert substantial influence with mean importance factors of 0.22 and 0.3, then follows cyclic loading amplitude (0.14) and UCS (0.17). SHapley Additive exPlanations analysis indicates that ML models can correctly capture the complex relationship between major parameters and fatigue life. This study shows that, after carefully considering the algorithms and input parameters, ML can effectively predict the fatigue life of rocks.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"206 ","pages":"Article 109438"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749975","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}