To address the need for rapid in situ plugging and repair of hydraulic machinery and chemical pipelines and to resolve the issue that a single curing agent cannot simultaneously achieve rapid curing and excellent mechanical properties in epoxy resin systems, this study explores the use of composite curing agents. In particular, effective formulations are designed for mixing fast and slow curing agents, studying their effects on the curing behavior, curing quality, and mechanical properties of epoxy resins and elucidating their influence mechanisms. The results indicate that three resin systems meet the requirements for rapid curing (curing time within 30 min): 4A6B/EP, 2A8B/EP, and 0A10B/EP. Among them, 4A6B/EP exhibits the best curing quality and mechanical properties. In particular, 4A6B/EP demonstrates the lowest values of curing shrinkage rate, internal curing stress, average pore size, porosity, and cumulative pore volume. Its low internal stress and low defects reduce the stress concentration, while more efficient deflection and branching of internal cracks enhance its deformation resistance. Consequently, 4A6B/EP shows the highest microhardness, fracture toughness, tensile strength, Young’s modulus, and elongation after fracture. Based on the comprehensive evaluation of rapid curing characteristics and mechanical properties, the 4A6B/EP system offers the best overall performance. Therefore, it is recommended as the preferred resin system for rapid plugging and repair of composite materials, providing a theoretical basis and technical support for boosting the application of epoxy resin composite materials in high-tech fields.

Phenyl polyhedral oligomeric silsesquioxane (POSS) is modified onto the GO surface by using the strong π–π coupling between a large number of benzene rings at the end of the phenyl POSS structure and the graphite structure in the GO sheet, realizing the non-covalent functionalization of GO (POSS-GO). The POSS-GO-reinforced EP (POSS-GO/EP) composite material is prepared using the casting molding process. The surface morphology of GO before and after modification and its peel dispersion in EP are examined. Furthermore, the mechanical properties, cross-sectional morphology, and reinforcement mechanism of POSS-GO/EP are thoroughly examined. The results show that the cage-like skeleton structure of POSS is embedded between the GO layers, increasing the spacing between the GO layers and leading to a steric hindrance effect, which effectively prevents their stacking and aggregation and improves the dispersion performance of GO. In particular, the 0.4 phr POSS-GO/EP sample shows the best mechanical properties. This is because, on the one hand, POSS-GO is uniformly dispersed in the EP matrix, which can more efficiently induce crack deflection and bifurcation and can also cause certain plastic deformations in the EP matrix. On the other hand, the POSS-GO/EP fracture cross-section with a stepped morphology of interlaced “canine teeth” shape is rougher and more uneven, leading to more complex crack propagation paths and greater energy consumption. Moreover, the mechanical meshing effect between the rough POSS-GO surface and the EP matrix is stronger, which is conducive to the transfer of interfacial stress and the strengthening and toughening effects of POSS-GO.

Deep learning has been demonstrated to be a universal and successful tool for classification, detection and segmentation. Convolutional neural network (CNN), as a representative model, achieves excellent performance in many image process areas due to its special structural design---shared weights, local receptive field and pooling layer. Large efforts are devoted to studying and improving model performance based on these three parts. In this paper, we proposed a novel pooling layer named restricted stochastic pooling layer. Restricted stochastic pooling randomly select activation from the top n maximum of each pooling region instead of the largest one (max pooling), or stochastic one (stochastic pooling). Our proposed method can not only obtain representative activation but also add randomness to the model. Through large amounts of experiments, we achieve good performance on SVHN and CIFAR-10 which demonstrates the effectiveness of restricted stochastic pooling.

The implementation of perfect electric conductor (PEC) boundary condition for meshless radial point interpolation method (RPIM) with the weighted decaying Laguerre polynomial (WLP) is investigated. A novel uniform nodal placement is proposed and the number of H-nodes reduces to about a half of that for the conventional scheme. There are only E-nodes scattered on the PEC boundary. The E-node and H-node have the same scale of support domain nodes. The image theory is adopted to update the implicit electric equations on the PEC boundary. This scheme is also suitable for nonuniform node distribution. Numerical results have verified the accuracy of the proposed method.

Deterministic electrochemical repairing method is effective technique for the rapid fixing of damaged parts in the military equipment, and its critical content is to achieve a steady deposition function. In order to take into consideration both the repairing efficiency and fixing accuracy, three shapes of deposition functions were developed through the square nozzles, the rectangular nozzles and the round nozzles. Meanwhile, for the three kinds of nozzles, each kind had several sizes, which aimed to further improve the scope of application of the deterministic electrochemical repairing method. Furthermore, the deposition functions were detected through measuring the morphology and efficiency of the deposition spots obtained by the deterministic electrochemical repairing system with the varied deposition times of 0.5h, 1.0h, 1.5h and 2.0h, respectively. The experimental results indicated that morphology of the deposition functions were consistent with those theoretical results, and their corresponding efficiency was steady, which were propitious to obtained better repairing efficiency and higher fixing accuracy. The developed effective deposition functions can promote the practical application of deterministic electrochemical repairing method in the precision assurance of military equipment.