This work investigated the fatigue crack propagation behavior of the 2195-T8 Al-Li alloy with precorroded holes. The microstructure, crack growth path, and the fracture surfaces of the samples with the precorroded holes have been examined with scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and computed tomography (CT). The characteristics of the crack growth have been analyzed via fracture mechanics by employing the finite element method (FEM). The results showed that the bulk of the fatigue cracks had been initiated from the corrosion pits and corroded discontinuously and precipitated further to become intergranular. Owing to the superposed stress concentration caused by the corrosion pits, the porous region at the bottom of the precorroded hole had affected the crack propagation performance. Crack growth rates were different in multiple positions owing to the difference of at crack fronts.

Recent studies have shown that graph‐based clustering methods are good at processing hyperspectral images (HSIs), while falling short for large‐scale HSIs due to high time complexity. Meanwhile, the performance of these methods relies on the quality of the constructed graph with selected anchor points. More anchor points bring better clustering results for graph‐based methods. Time complexity, however, sees a considerable increase as the number of anchor points grows. Therefore, a method that can obtain efficient clustering accuracy and consumes less time is to be developed. Against this backdrop, a novel algorithm named fast spectral clustering via efficient multilayer anchor graph (FEMAG) is proposed to resolve the accuracy and time‐consuming trade‐off problem. First, FEMAG adopts superpixel principal component analysis (SuperPCA) to extract the low‐dimensional features of HSIs. Then, a multilayer anchor graph is constructed to improve the clustering performance. When constructing the similarity graph, FEMAG takes balanced K‐means‐based hierarchical K‐means (BKHK) to obtain outperforming anchor points efficiently. Extensive experiments validate that FEMAG achieves better clustering accuracy while taking less time compared to previous clustering methods.

This study investigates the effects of heat transfer and molten pool flow behavior on the final structure of laser filler wire welds, aiming to improve weld quality. Laser filler wire welding experiments and numerical simulations were performed on 2195 Al-Li alloy workpieces with varying welding parameters. Numerical simulation of the heat transfer and flow in the molten pool was carried out using the CFD method, and the moving filler wire was introduced from the computational boundary by secondary development. Simulation results indicated that reducing welding speed and increasing wire feeding rate enhanced the cooling rate of the weld. Additionally, energy absorbed by the filler wire contributed between 6% and 16% of the total energy input during the liquid bridge transition. Comparing experimental and simulation data revealed that the cooling rate significantly affected the weld’s micro-structure and hardness. Notably, the formation of the equiaxed grain zone (EQZ) was crucial for weld performance. Excessive cooling rates hindered EQZ formation, reducing flow in this critical region. These findings offer valuable insights for optimizing welding parameters to enhance weld quality and performance.