ABSTRACT This study proposes a modelling framework for ice adhesive and bulk fracture. In this framework, adhesive and bulk fracture mechanisms are treated as distinct phenomena. Adhesive fracture is modelled using the well‐established cohesive zone model, which is widely used in the analysis of composite material delamination. Conversely, bulk fracture is treated using bond‐based peridynamics, a relatively new theory that is becoming increasingly popular for modelling brittle material failure under impact conditions. The contribution of this study is the assessment of the combination of these models for impact‐driven ice failure. A test rig was designed and manufactured to validate the modelling framework against experimental results. An analysis of the two modelling methods was performed to identify the necessary model parameters, and numerical values specific to ice failure were proposed. Although they overestimate the delaminated area, the simulations reproduce the main features of the observed fracture patterns. Ultimately, a sensitivity analysis of the framework to variations in model parameters demonstrates areas for enhancement.
ABSTRACT A physics‐informed multisource domain transfer learning (PITL) prediction model was proposed to predict fatigue life of IN718 superalloy under complex conditions, which faced sparse data and complex mechanism challenges. The model effectively integrates physical prior knowledge and transfer learning algorithms widely used in current fatigue research and engineering fields, such as equivalent effect variable model, Manson–Coffin model, and other physical information, as well as low‐cycle fatigue hysteresis‐loop characteristic information, based on its architecture. It effectively solves the problem of learning and utilizing multisource data in fatigue testing and achieves accurate prediction of fatigue life under different strain‐ratio loading conditions based on known fatigue loading conditions. And then, the effects of different model combinations, multisource transfer patterns, and multisource data size on the accuracy of target domain life prediction are systematically explored under four strain ratios loading condition. The results show that the PITL model incorporating physical information exhibits higher prediction accuracy and robustness than the basic transfer learning model. Its predictive performance depends on the model combinations, the transfer patterns, and the amount of data in the source domain.
ABSTRACT Deep brittle rocks are subjected to true triaxial compressive stresses () coupled with pore fluid pressure. Existing models rarely distinguish the localized actions of pore pressure on different microcrack planes under true triaxial conditions. This study establishes a true triaxial micro–macro fracture constitutive model incorporating pore fluid pressure. At the microscale, the dual mechanisms of pore pressure, weakening effective normal stress on initial crack surfaces and inducing tensile driving forces on wing crack surfaces, are formulated, with cross‐scale damage evolution mapping microscopic crack propagation to macroscopic strain. At the macroscale, the lateral confinement effect of the intermediate principal stress () is incorporated into the hydromechanical constitutive equation. The model is validated against true triaxial seepage experimental data of yellow sandstone. Results demonstrate that pore fluid pressure degrades peak strength and accelerates unstable crack propagation, whereas effectively suppresses crack growth via lateral confinement.
ABSTRACT The fatigue limit and fatigue life vary depending on the loading mode and are also greatly affected by stress concentration. The effect of mean stress has been mathematically expressed using several models, but based on experimental data, the Walker model is the most appropriate. Although the model constants differ depending on the material, stress concentration state, and loading mode, it was shown that high prediction accuracy can be achieved by selecting appropriate constants for both smooth and notched specimens. The same was true for the effect of assembling stress due to welding distortion on the fatigue limit and the threshold stress intensity range of welded details. Furthermore, it was shown that this model can also be applied to predicting multiaxial fatigue and to estimating statistical failure probability. By using the concept of equivalent alternating stress, it became possible to apply the Walker model to predict both the fatigue limit and the fatigue life under arbitrary stresses in the high‐cycle regime.
ABSTRACT Ferritic and ferritic/martensitic steels exhibit a ductile‐to‐brittle transition (DBT) whose large scatter in cleavage toughness makes structural integrity assessment statistical. This review focuses on the experimental, data‐driven and event‐based evidence bearing on the probabilistic description of transition toughness, and on the shape of the toughness–temperature curve; the extensive numerical constraint‐modelling literature is deferred to a companion review. Treating the transition micromechanism critically, we show that the weakest‐link Master Curve survives recent fractographic findings, and that the Weibull exponent is derived from small‐scale‐yielding crack‐tip scaling and confirmed experimentally, not assumed. Using model‐free machine‐learning analyses of raw toughness data, we argue that the exponential Master Curve and the saturating Unified Curve differ decisively only beyond the transition window, that saturation is real rather than imposed, and that prior ductile crack growth is the deciding variable. Constraint, active volume, loading rate, and warm pre‐stressing are reviewed accordingly.
