Magnesium alloy AZ31B and titanium TA2 were welded by resistance spot welding technology employing an interlayer of aluminum foil and asymmetric electrodes. The microstructure of the joint was observed, with an analysis conducted on the impact of welding current and welding time on the tensile shear load of the joint. During the welding process, the aluminum interlayer melted and blended with the molten magnesium alloy, leading to the formation of a eutectic layer consisting of Mg17Al12 and (Mg) in close proximity to the welding interface. As the increasing of welding current or the extending of welding time, there was an initial increase followed by a slight decrease in the tensile shear load of the AZ31B/TA2 joint. At a welding current of 16 kA, the tensile shear load of the joint achieved the maximum, which was approximately 6.48 kN. The findings suggest that it is effective to use an aluminum foil as an intermediary to regulate the metallurgical reaction at the interface and utilize nonsymmetrical electrodes for thermal compensation in the resistance spot welding between titanium and a magnesium alloy.

Aiming at the problems of lack of intelligent fire extinguishing means, insufficient timeliness of manual fire extinguishing, and difficult security guarantee in the existing valve hall, an intelligent fire extinguishing robot system for the converter station valve hall was developed this paper. The overall structure, robot body, water supply system, navigation system and software architecture of the system were introduced. Water spray test was conducted, and the robot could switch between columnar spray and fog spray. Finally, the robot has been applied in the valve hall for one year. The results showed that the robot has a high degree of intelligence, and can extinguish the fire automatically, accurately and quickly. The robot is suitable for firefighting of equipment in valve hall of converter station and provides a new technical means and method.

A 1060 commercial-purity aluminum and T2 pure copper plates with a thickness of 2 mm were welded by using resistance element welding with an aluminum rivet and auxiliary gasket. The interfacial microstructure was analyzed, and the tensile shear load of the joint was tested. In the joint welded, a layer of Al2Cu adjacent to the copper and the eutectic structure of Al2Cu + (Al) near the nugget region were formed at the interface of Al/Cu. The tensile shear load of the joint increased first and then decreased with the increase of welding current, and it reached the maximum of 2.24 kN when the welding current was 26 kA. The results reveal that the application of the auxiliary gasket not only promote the thickening of the nugget, but also achieve the joining between the rivet leg and the upper plate when resistance element welding of Al/Cu is performed.

Thermal processing is a useful method for improving the strengthening effects of fibers used to reinforce metal matrix composites (MMCs), but the corresponding models have not been constructed. In this work, a Ti matrix composite (TMC) reinforced by in situ TiB fibers was prepared, then thermal processing was applied to it at different levels of deformation to align the TiB fibers along the loading direction. Changes in the microstructure of the matrix, the orientation and the aspect ratio of the TiB fibers during this process were investigated. It was found that the aspect ratio of TiB fibers decreased sharply after a large amount of deformation. The strengthening effect of TiB fibers in the composite was simulated by strengthening models of the fibers, and the simulated results were verified by the results of tensile tests. The modeled results show that the strengthening factor (C₀) of the in situ TiB fibers improved from 0.125 in the as-cast composite to 0.520, 0.688 and 0.858 by the processes with deformation ratios of 0.39, 0.26 and 0.14, respectively. The results of the tensile tests showed that the measured values of C₀ gradually deviated from the modeled ones with an increase in the ratio of deformation applied during processing, and the deviation could be interpreted with the strengthening models.