Fracture mechanics design principles incorporate the damage tolerance approach for a safe and extended operational life of engineering structures subjected to variable amplitude or spectrum loading. Numerical models used to predict the fatigue crack growth rate (FCGR) under spectrum loading require large experimental data, idealization of conditions, and formulation of various crack-driving force parameters. This has rendered all the models useful but not universally applicable. The current study uses FCGR-Net-a machine learning (ML) model to predict fatigue crack growth under spectrum loading conditions. The performance of the FCGR-Net model is investigated on nickel-based super-alloys, GTM 718 and 720, subjected to TURBISTAN (turbine standard) spectrum load sequence. It was observed that the predictions of the model, trained over constant amplitude FCGR data, were highly conservative, while the same model trained over the variable amplitude FCGR data resulted in a quite accurate prediction. The difference (domain shift) in the constant amplitude trained FCGR-Net predictions and experimental data was effectively addressed by introducing a "delay factor (Df)" in the FCGR-Net ML model. The results of the predictions were validated with the popular Kujawski's K* model and experimental data. The current work is a proof-of-concept that demonstrates a promising alternative for predicting FCGR behavior under variable amplitude loading or spectrum loading using ML techniques. The accuracy of these ML models will continuously improve with increased application and the availability of experimental data.
AA6061-based hybrid aluminum matrix composites were successfully produced via stir casting. Al6061/7 wt% SiC/0.05 wt% WSe2 and Al6061/14 wt% SiC/0.1 wt% WSe2 were developed and then evaluated for mechanical, tribological, and corrosion properties. X-ray diffraction analysis confirmed the presence and uniform distribution of the reinforcement phases within the aluminum matrix. Mechanical test results showed a significant improvement in properties with an increase in reinforcement content. The hardness increased from about 105 HV to 121 HV. The yield strength and ultimate tensile strength were enhanced from 275 MPa and 310 MPa to 340 MPa and 395 MPa, respectively. Although ductility decreased, it represents a small trade-off compared to the considerable enhancement in strength and hardness. Under the study of dry sliding conditions, the wear-rate and coefficient of friction showed a significant reduction. In the case of the Al6061/14 wt% SiC/0.1 wt% WSe2 composite, the lowest wear-rate of about 1.90 & times; 10(-4) mm(3)/N & centerdot; m was observed. A transition in wear mechanism was also noted, from moderate adhesive wear in the less reinforced composites to mild abrasive wear in the more reinforced composites, leading to the formation of a stable tribolayer. Taguchi optimization and analysis of variance (ANOVA) results report that material composition is the primary factor influencing wear behavior, with a very high degree of accuracy (R-2 = 99.73%), and contributing a dominant share of 64.51%. From the potentiodynamic polarization studies, a reduction in corrosion current density from 3.85 to 2.45 mu A/cm(2) was observed, indicating improved corrosion resistance with increasing reinforcement content. Overall, the hybrid composites exhibit excellent performance, making them a suitable choice for demanding engineering and automotive applications.
ABSTRACT The effect of hydrogen on the strain hardening or softening behavior of 316L stainless steel during the plastic deformation stage remains controversial. The influence of hydrogen on the plastic deformation and fracture behavior of 316L austenitic stainless steel was investigated using digital image correlation (DIC) and finite element method (FEM) in this study. The results show that hydrogen reduces the fracture strain of the material. After 48 h of hydrogen charging, the hydrogen embrittlement sensitivity index reaches 13.85%, whereas its effect on the hardening or softening behavior of the material can be considered negligible. DIC and FEM analyses indicate that hydrogen promotes strain localization and accelerates the onset of necking, leading to premature fracture before full macroscopic plastic deformation can develop. This further confirms that hydrogen primarily reduces the fracture strain of 316L stainless steel, without significantly influencing its hardening or softening behavior. Scanning electron microscope (SEM) fractography reveals that hydrogen‐induced damage transforms the fracture morphology from large and deep dimples to small and shallow dimples, indicating that the microvoid coalescence process is significantly accelerated, which is consistent with the premature fracture behavior observed by DIC/FEM.
ABSTRACT Both wear and fatigue are damage mechanisms of fretting phenomenon. Plasticity affects contact pressure of the fretting specimen. Hence, it is necessary to account for the contribution of plasticity in the study of fretting. First, the numerical model based on the finite element method is established and validated by the experiment. Then, the effect of fretting wear on fretting fatigue considering plasticity is investigated. It is shown that wear changes the crack initiation position. The crack initiation site gradually shifts toward the trailing edge with the increase of maximum bulk stress. Under the gross slip condition with significant plastic deformation, although wear can improve the fatigue crack initiation life, this beneficial effect is limited. Consequently, fretting fatigue rather than fretting wear is the primary fretting damage mechanism.
Abstract Ni-based superalloys produced via powder metallurgy (PM) undergo hot isostatic pressing (HIP) and subsequent forming operations, during which prior particle boundaries (PPBs) are formed and only partially eliminated. The residual PPB clusters strongly influence the mechanical and thermomechanical performance of these alloys. In this study, a polycrystalline discrete dislocation dynamics (DDD) framework is employed to investigate the role of PPBs in governing dislocation behavior, residual stress evolution, and macroscopic hardening in Ni-based superalloys. Realistic grain morphologies are incorporated, and PPBs are modeled as nontransmissive interfaces, representing a limiting case of strong dislocation blocking, which restricts dislocation motion across boundaries. The simulations reveal that PPBs induce localized dislocation pile-ups and back stresses, thereby enhancing strain hardening and yield strength. Larger and more densely distributed PPB clusters intensify these effects due to increased dislocation pinning. Residual stress analysis further shows that regions adjacent to PPBs retain higher compressive stresses after unloading, with relaxation strongly dependent on PPB density. These results highlight the critical role of PPB size, number, and spatial configuration in shaping the deformation and stress evolution behavior of PM-processed Ni-based superalloys. The study underscores the need to control PPB characteristics during HIP and post-HIP processing to achieve an optimal balance between strengthening and stress recovery.
