{"title":"TC4钛合金激光电弧复合焊接接头疲劳裂纹萌生机理及寿命预测","authors":"Zheng Lei , Long He , Ruilin Liu , Xu Zhao","doi":"10.1016/j.ijfatigue.2025.109308","DOIUrl":null,"url":null,"abstract":"<div><div>Titanium alloy welded structures in aerospace applications frequently undergo high-cycle fatigue (HCF) failure under high-frequency cyclic loading. Microstructural inhomogeneity in weld zones induces divergent deformation mechanisms, while welding defects compromise the accuracy of conventional life prediction models. This study systematically investigates HCF failure mechanisms in laser-arc hybrid welded TC4 titanium alloy joints under varying maximum cyclic stresses (σ<sub>max</sub> = 410–450 MPa). Microstructural characterization reveals: The weld zone comprises predominantly acicular α′ martensite (≈43 μm) and basket-weave structures, while the heat-affected zone (HAZ) exhibits refined α′ phase (≈22 μm). At low σ<sub>max</sub> (410 MPa), dense basket-weave structures surrounding pores obstruct dislocation slip and induce crack deflection, forming tortuous propagation paths that extend HCF life. Conversely, high σ<sub>max</sub> (450 MPa) triggers severe dislocation pile-up at α colony interfaces, accelerating crack propagation through colony channels and significantly reducing HCF life. To address prediction uncertainties caused by defect-induced life scatter, a physics-informed neural network (PINN) model is developed. This framework integrates defect parameters (size √area, distance d, circularity Cir) with physical laws via penalty-function-constrained loss functions. Compared to conventional BPNN, the PINN model improves test-set prediction accuracy by 16 % (R<sup>2</sup> = 0.86), mitigates over-fitting, and confines nearly all predictions within triple-error bands. This research has achieved rapid and precise assessment of the fatigue life of welded titanium alloy components, providing critical technical support for lightweight design and reliability assurance in aerospace equipment.</div></div>","PeriodicalId":14112,"journal":{"name":"International Journal of Fatigue","volume":"203 ","pages":"Article 109308"},"PeriodicalIF":6.8000,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fatigue crack initiation mechanism and life prediction of laser-arc hybrid welded TC4 titanium alloy joints\",\"authors\":\"Zheng Lei , Long He , Ruilin Liu , Xu Zhao\",\"doi\":\"10.1016/j.ijfatigue.2025.109308\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Titanium alloy welded structures in aerospace applications frequently undergo high-cycle fatigue (HCF) failure under high-frequency cyclic loading. Microstructural inhomogeneity in weld zones induces divergent deformation mechanisms, while welding defects compromise the accuracy of conventional life prediction models. This study systematically investigates HCF failure mechanisms in laser-arc hybrid welded TC4 titanium alloy joints under varying maximum cyclic stresses (σ<sub>max</sub> = 410–450 MPa). Microstructural characterization reveals: The weld zone comprises predominantly acicular α′ martensite (≈43 μm) and basket-weave structures, while the heat-affected zone (HAZ) exhibits refined α′ phase (≈22 μm). At low σ<sub>max</sub> (410 MPa), dense basket-weave structures surrounding pores obstruct dislocation slip and induce crack deflection, forming tortuous propagation paths that extend HCF life. Conversely, high σ<sub>max</sub> (450 MPa) triggers severe dislocation pile-up at α colony interfaces, accelerating crack propagation through colony channels and significantly reducing HCF life. To address prediction uncertainties caused by defect-induced life scatter, a physics-informed neural network (PINN) model is developed. This framework integrates defect parameters (size √area, distance d, circularity Cir) with physical laws via penalty-function-constrained loss functions. Compared to conventional BPNN, the PINN model improves test-set prediction accuracy by 16 % (R<sup>2</sup> = 0.86), mitigates over-fitting, and confines nearly all predictions within triple-error bands. This research has achieved rapid and precise assessment of the fatigue life of welded titanium alloy components, providing critical technical support for lightweight design and reliability assurance in aerospace equipment.</div></div>\",\"PeriodicalId\":14112,\"journal\":{\"name\":\"International Journal of Fatigue\",\"volume\":\"203 \",\"pages\":\"Article 109308\"},\"PeriodicalIF\":6.8000,\"publicationDate\":\"2025-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Fatigue\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0142112325005055\",\"RegionNum\":2,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Fatigue","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0142112325005055","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
Fatigue crack initiation mechanism and life prediction of laser-arc hybrid welded TC4 titanium alloy joints
Titanium alloy welded structures in aerospace applications frequently undergo high-cycle fatigue (HCF) failure under high-frequency cyclic loading. Microstructural inhomogeneity in weld zones induces divergent deformation mechanisms, while welding defects compromise the accuracy of conventional life prediction models. This study systematically investigates HCF failure mechanisms in laser-arc hybrid welded TC4 titanium alloy joints under varying maximum cyclic stresses (σmax = 410–450 MPa). Microstructural characterization reveals: The weld zone comprises predominantly acicular α′ martensite (≈43 μm) and basket-weave structures, while the heat-affected zone (HAZ) exhibits refined α′ phase (≈22 μm). At low σmax (410 MPa), dense basket-weave structures surrounding pores obstruct dislocation slip and induce crack deflection, forming tortuous propagation paths that extend HCF life. Conversely, high σmax (450 MPa) triggers severe dislocation pile-up at α colony interfaces, accelerating crack propagation through colony channels and significantly reducing HCF life. To address prediction uncertainties caused by defect-induced life scatter, a physics-informed neural network (PINN) model is developed. This framework integrates defect parameters (size √area, distance d, circularity Cir) with physical laws via penalty-function-constrained loss functions. Compared to conventional BPNN, the PINN model improves test-set prediction accuracy by 16 % (R2 = 0.86), mitigates over-fitting, and confines nearly all predictions within triple-error bands. This research has achieved rapid and precise assessment of the fatigue life of welded titanium alloy components, providing critical technical support for lightweight design and reliability assurance in aerospace equipment.
期刊介绍:
Typical subjects discussed in International Journal of Fatigue address:
Novel fatigue testing and characterization methods (new kinds of fatigue tests, critical evaluation of existing methods, in situ measurement of fatigue degradation, non-contact field measurements)
Multiaxial fatigue and complex loading effects of materials and structures, exploring state-of-the-art concepts in degradation under cyclic loading
Fatigue in the very high cycle regime, including failure mode transitions from surface to subsurface, effects of surface treatment, processing, and loading conditions
Modeling (including degradation processes and related driving forces, multiscale/multi-resolution methods, computational hierarchical and concurrent methods for coupled component and material responses, novel methods for notch root analysis, fracture mechanics, damage mechanics, crack growth kinetics, life prediction and durability, and prediction of stochastic fatigue behavior reflecting microstructure and service conditions)
Models for early stages of fatigue crack formation and growth that explicitly consider microstructure and relevant materials science aspects
Understanding the influence or manufacturing and processing route on fatigue degradation, and embedding this understanding in more predictive schemes for mitigation and design against fatigue
Prognosis and damage state awareness (including sensors, monitoring, methodology, interactive control, accelerated methods, data interpretation)
Applications of technologies associated with fatigue and their implications for structural integrity and reliability. This includes issues related to design, operation and maintenance, i.e., life cycle engineering
Smart materials and structures that can sense and mitigate fatigue degradation
Fatigue of devices and structures at small scales, including effects of process route and surfaces/interfaces.