In order to achieve a normal performance of the armature, which is a moving part carrying currents in a railgun, it is of great importance to maintain good electrical contacts between the armature and rails. In this paper, based on mutiphysics effects, a dynamic interior ballistic process considering the friction loss, nonlinear electrical contacts, and aerodynamic drag is established to simulate the movement of the armature in bore. Some dynamic parameters versus time, such as the forces on the armature, the wear rate of armature, and the interference, were obtained and analyzed. Incorporating with the morphology of rail surfaces after a shot, the dynamic contact status between the armature and rails is discussed. The simulations coincide well with experimental results.

As an important part of head protection equipment, research on the material and structural application of helmet liners has always been one of the hotspots in the field of helmets. This paper first discusses common helmet liner materials, including traditional polystyrene, polyethylene, polypropylene, etc., as well as newly emerging anisotropic materials, polymer nanocomposites, etc. Secondly, the design concept of the helmet liner structure is discussed, including the use of a multi-layer structure, the addition of geometric irregular bubbles to enhance the energy absorption effect, and the introduction of new manufacturing processes, such as additive manufacturing technology, to realize the preparation of complex structures. Then, the application of biomimetic structures to helmet liner design is analyzed, such as the design of helmet liner structures with more energy absorption properties based on biological tissue structures. On this basis, we propose extending the concept of bionic structural design to the fusion of plant stalks and animal skeletal structures, and combining additive manufacturing technology to significantly reduce energy loss during elastic yield energy absorption, thus developing a reusable helmet that provides a research direction for future helmet liner materials and structural applications.

In order to analyze the dynamic responses of rails subjected to distributed moving electromagnetic pressure, the vibration governing equations of rails on viscoelastic support were established based on Winkler foundation beam model. The analytical expression of the vibration response of the rail was deduced by modal superposition method. Taking a typical current excitation as an example, the dynamic responses (such as vibration deflection, velocity, bending stress, and so on) were calculated, and the characteristics along with the critical velocity effects were emphatically analyzed. The influence of support stiffness and damping on the dynamic response of rails were also investigated. The research results can provide a theoretical basis for the design of launcher packaging structure.

Helmets play a crucial role in protecting motorcycle riders during two-wheeler accidents by reducing the risk of head injuries. This study investigated the complex interplay between the density, Poisson’s ratio, and Young’s modulus of a helmet liner and their impact on biomechanical factors contributing to traumatic brain injury during collisions. A validated finite element model of a 50th percentile detailed human head was initially used, followed by the development of a coupled helmet head model for collision simulations. The accuracy of the model was assessed by comparing the center-of-mass acceleration data of the head with the experimental results. This study analyzed the von Mises stress, skull stress, and intracranial pressure (ICP),and the results revealed patterns in stress distribution and the potential for cranial and brain injuries. Stress concentrations were observed in the cervical region before the impact, characterized by compressive stress on the impacted side and tensile stress on the opposite side, with peak stress levels found in the temporal bone base and frontal bone. After the impact, brain inertia–driven movements can further increase the risk of traumatic brain injury. The study found a positive correlation between liner density and center-of-mass acceleration of the head in the absence of bottoming out of the liner. By optimizing the liner properties, the study achieved a 4.5% reduction in head acceleration, a 10.1% decrease in skull stress, and a 19.8% reduction in ICP. These findings offer valuable insights for biomechanical research on head injuries caused by traffic accidents and for improving helmet designs to enhance protective measures.

The air conditioning compressor is a critical component in automobile heating, ventilation and air conditioning systems. However, compressor noise has long been a problem for automobile manufacturers. In recent years, the development and application of automobile air conditioning scroll compressors has increased significantly due to their low mechanical vibration and noise. However, their limitations in terms of airflow pulse and noise cannot be ignored, especially in low speed and high load conditions where the noise generated has a negative impact on driving and passenger experience. Noise and airflow pulses are important considerations that cannot be ignored. This study innovatively modifies the end cap structure of the scroll compressor, using the principles of expansion muffler and insertion tube structure, with the aim of improving the acoustic quality of the scroll compressor. The results show that the novel valve construction can significantly reduce the sound pressure level of the scroll compressor noise to a maximum of 75.20 dBA. The results of this study provide a theoretical basis and practical technical applications for future research and development in the automobile industry.

The variation in armature structural parameters has a profound impact on electromagnetic railgun performance. In order to enhance the electrical contact performance of armature and rail interfaces and achieve armature lightweighting, a novel approach is proposed that combines backpropagation (BP) neural networks with genetic algorithms for optimizing armature structures. Employing Latin hypercube experiments, structural dimension samples were extracted for both flat armatures and convex-arc armatures, and a training dataset was generated through finite element simulations. Mapping models were constructed based on BP neural networks to relate the contact pressure distribution coefficient, maximum stress, mass, and total contact force individually to the armature structural parameters. Incorporating a comprehensive evaluation index denoted as “W” as the fitness function for the genetic algorithm, global optimization of armature size was carried out. The optimized results were subsequently validated through finite element comparative analysis. The outcomes revealed that, following optimization of flat armatures, a 10.4% reduction in mass and a 55.7% decrease in the contact pressure distribution coefficient were achieved. For convex-arc armatures, a 25% reduction in mass and a 46.5% decrease in the contact pressure distribution coefficient were observed. Simultaneously achieving armature lightweighting and improving the uniformity of contact pressure distribution on armature and rail interfaces, this methodology offers a novel perspective and serves as a valuable reference for addressing the optimization of armature structures under complex operating conditions.