The 2524-T3 aluminum alloy was subjected to fatigue tests under the conditions of R = 0, 3.5% NaCl corrosion solution, and the loading cycles of 10⁶, and the S-N curve was obtained. The horizontal fatigue limit was 169 MPa, which is slightly higher than the longitudinal fatigue limit of 163 MPa. In addition, detailed microstructural analysis of the micro-morphological fatigue failure features was carried out. The influence mechanism of corrosion on the fatigue crack propagation of 2524-T3 aluminum alloy was discussed. The fatigue source characterized by cleavage and fracture mainly comes from corrosion pits, whose expansion direction is perpendicular to the principal stress direction. The stable propagation zone is characterized by strip fractures. The main feature of the fracture in the fracture zone is equiaxed dimples. The larger dimples are mixed with second-phase particles ranging in size from 1 to 5 μm. There is almost a one-to-one correspondence between the dimples and the second-phase particles. The fracture mechanism of 2524 alloy at this stage is transformed into a micro-holes connection mechanism, and the nucleation of micropores is mainly derived from the second-phase particles.

The different creep-aging forming processes of 2524 aluminum alloy were taken as the research object, and the effects of creep-aging temperature and creep stress on the fatigue-crack propagation properties of the alloy were studied. The research results showed the following under the same sintering time of 9 h, at creep-aging temperatures of 100 °C, 130 °C, 160 °C, and 180 °C, respectively, with an increase in creep-aging temperature: the fatigue-crack propagation rate was promoted, the spacing of fatigue striations increased, and the sizes of dimples decreased while the number was enlarged; this proves that the fatigue property of the alloy was weakened. Compared with the specimens with creep deformation radii of 1000 mm and 1500 mm, the creep deformation stress was the smallest when the forming radius was 1800 mm, with a higher threshold value of fatigue-crack growth in the near-threshold region of fatigue-crack propagation (ΔK ≤ 8 MPa·m^1/2). Under the same fatigue cycle, the specimens under the action of larger creep stress endured a longer fatigue stable-propagation time and a faster fracture speed. Comparing the effect of creep-aging temperature and creep stress, the creep-aging temperature plays a dominant role in the fatigue-crack propagation of creep-aged 2524 aluminum alloy.

By aiming at the common distributed random dynamic loads in engineering practice, an equivalent identification method that is based on K–L decomposition and sparse representation is proposed. Considering that the establishment of a probability model of the distributed random dynamic load is usually unfeasible because of the requirement of a large number of samples, this method describes it by using an interval process model. Through K–L series expansion, the interval process model of the distributed random dynamic load is recast as the sum of the load median function and the load uncertainty. Then, the original load identification problem is transformed into two deterministic ones: the identification of the load median function and the reconstruction of the load covariance matrix, which reveals the load uncertainty characteristics. By integrating the structural modal parameters, and by adopting the Green’s kernel function method and sparse representation, the continuously distributed load median function is equivalently identified as several concentrated dynamic loads that act on the appropriate positions. On the basis of the realization of the first inverse problem, the forward model of the load covariance matrix reconstruction is derived by using K–L series expansion and spectral decomposition. The resolutions to both inverse problems are assisted by the regularization operation so as to overcome the inherent ill-posedness. At the end, a numerical example is presented to show the effectiveness of the proposed method.

The carburized holes processed by ordinary internal grinding are prone to burn, crack, and low efficiency. Honing has a superior machining efficiency and cooling effect compared to traditional internal grinding. In this paper, we innovatively apply honing to carburizing hole grinding and propose an effective optimization scheme to enhance the surface finish of carburized holes. We set up an experimental system to explore the influence law of honing head rotation speed, axial reciprocating speed, grain size, and single grinding depth on surface roughness. Based on the grey correlation and response surface method, we propose a method to optimize the honing parameters of carburized holes and establish a prediction model, which has an R² value of 0.9887, indicating that the model fits well. We verify the validity of the model by the root mean square error of 0.012 between the measured and calculated values. Based on the model, the optimal parameters of roughness (Ra) is obtained and verified by experiments. Compared with the original honing parameters, the surface roughness quality is improved by 25.8%. It shows that the optimized honing process based on the GRA-RSM method improves the surface quality of carburized holes significantly.

As-cast TiZrMoSn_0.8Hf_0.2 high-entropy alloy (HEA) was prepared by vacuum non-consumable arc melting furnace, followed by annealing treatment at 600–900 °C. The effect of annealing treatment on the phase composition, microstructure, hardness, friction and wear properties, and corrosion resistance have been investigated. The results showed that the as-cast alloy was composed of BCC-β+HCP-α solid solution phases and Hf₅Sn₃. After annealing treatment, the microstructure of the samples were refined, and the Mo₃Sn phase formed at 600 °C, but it was unstable and decomposed above 700 °C. The hardness and wear resistance of the alloy are improved after annealing. The highest hardness, lowest friction coefficient, and the smallest wear scar width and depth were obtained after annealing at 600 °C due to its fine microstructure and the formation of Mo₃Sn phase. The wear mechanism of this alloy is mainly adhesive wear and abrasive wear. Compared with the as-cast alloy, the annealed samples possessed more positive corrosion potential, lower corrosion current density, and better corrosion resistance in Ringer’s corrosion solution.

Wearable inertial sensors offer a portable means of assessing gait abnormalities associated with neurological and orthopedic disorders. However, intersubject variability, overlapping gait patterns, and class imbalance complicate multiclass recognition. This study presents the Temporal Structural Dual Graph Network (TSDGNet) for pathological gait classification using inertial measurement unit (IMU) signals. Four IMUs positioned on the head, lower back, and both feet provide acceleration and angular velocity signals during walking and turning. The framework combines multiscale temporal feature extraction with graph-based modeling of sequence-level relationships among sensor representations. Two fixed prior graphs encode anatomical and symbiotic relationships, while trainable graph attention and context-guided gated residual refinement adapt sensor-node representations. Class-balanced optimization is incorporated to reduce training bias toward majority classes. Subject-independent evaluation was performed on a public clinical dataset comprising healthy controls and seven neurological or orthopedic disease groups. Comparisons with representative baseline and advanced models showed competitive classification performance. Ablation analyses examined the contributions of temporal modeling, structural relationship learning, and class-balanced optimization. These findings support the potential of combining wearable inertial sensing with temporal and graph-based learning for objective classification of pathological gait.