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Structures designed against earthquake loads based on using control systems may experience explosions during their lifetime. In this paper, the performance of a hybrid control system composed of a low-damping base isolation and a supplemental magneto-rheological (MR) damper under external explosion has been studied. Base isolation system has the ability of decreasing the maximum structural response under blast loadings by shifting the period of the structure. In addition, MR damper improves the base isolation system performance by controlling the base drift of the structure. Hence, in this paper, the capability of a hybrid base isolation system equipped with an MR damper at the base has been evaluated in reducing the maximum structural response and base drift under external blast loadings. To determine the voltage of the semi-active MR damper, the H₂/Linear Quadratic Gaussian (LQG) and clipped-optimal control algorithms have been applied. For numerical simulations, a 10-storey shear frame subjected to blast loadings applied on different floors has been considered and the performance of the hybrid isolation system and MR damper has been studied. The results have proven the effectiveness of the hybrid control system in controlling the maximum response and base drift of the isolated structure against spherical external explosion. Furthermore, comparing the performance of the hybrid passive and semi-active base isolation systems indicates that the semi-active hybrid base isolation system is more effective in reducing the root-mean-square (RMS) value of the base drift. Similarly, it has been found that the semi-active hybrid base isolation system also performs better than the high-damping base isolation system.

Rebound effects can be caused for a blast door under explosion loadings of conventional weapons. Such effects reaching a certain extent can lead to severe reversed stresses and even destroy the hinge and lock system before the door leaf. In this study, an analytical model for the elastic rebound of a blast door under explosion loadings was proposed and analyzed. Based on the calculations, the effects of aspect ratio and load duration on the rebound behavior were analyzed. Furthermore, for extension of the analysis from the elastic to plastic range, comparison of the solutions with the analytical ones was made. The results showed that the positive and negative dynamic shear force peaks of the blast door deceased gradually with the aspect ratio, whereas the rebound strength was inversely proportional to the load duration. For blast doors entering into the plastic stage, the rebound behavior was similar to the elastic stage, implying that the design of a blast door can be based on its characteristics in elastic stage.

The attenuation of impact inducer vibration is critical to the safety of underground protection structure, equipment and personnel. Metamaterials and metastructures show great potential in terms of sound and impact attenuation. To effectively attenuate ground shock-induced vibration of underground protective structures, scaled shallow-buried annular metastructures with concrete–rubber layered structures were proposed and constructed. Underground explosion experiments were performed to investigate the vibration attenuation effect of annular metastructures with different layered structures. It is clear in this research only annular metastructures with concrete–rubber–concrete structures like annular metastructure model B6 have the most excellent wave attenuation performances, whose rubber layer thickness must be over 6mm and hardness is 20HA. Other layered structures with rubber layer thickness of 0.3cm or with more layers cannot effectively attenuate the shock wave in this research.

Unmanned aerial vehicles (UAVs) equipped with high definition (HD) cameras can obtain a large number of detailed inspection images. The insulator is an indispensable component in the transmission lines. Detecting insulator in image video quickly and accurately can provide a reliable basis for the ranging and the obstacle avoidance flight of UAV close to the tower and transmission line. At the same time, the insulator is a serious threat to the safety of the power grid due to the multiple faults of the insulator, and the computer technology should be fully utilized to diagnose the fault. Detection of the insulator images with the complex aerial background is implemented by constructing a convolutional neural network (CNN), which has the classic architecture of five modules of convolution and pooling, two modules of fully connected layers. In this paper, we propose a recognition algorithm for explosion fault based on saliency detection, which uses the trained network model to extract the features. Then, we put the saliency maps into a self-organizing feature map (SOM) network and build the mathematical module via super pixel segmentation, contour detection and other image processing methods. The test shows that the algorithm can reduce the error that may be caused by manual analysis. It also demonstrates that the detection of the insulator and the recognition of explosion fault can effectively improve the efficiency and intelligence level.

We study the dynamic fracture of thin-walled structure mainly due to impact and explosive loading. Therefore, we make use of a meshless smoothed particle hydrodynamics (SPH) shell formulation based on Mindlin–Reissner's theory. The formulation is an extension of the continuum-corrected and stabilized SPH method, so that thin structure can be modeled using only one particle characterizing mean position of shell surface. Fracture is based on separation of particles. We study tearing of pre-notched plates, fracture due to impact loading and dynamic fracture of cylindrical shells.