• Polymer(Korea)
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• v.36 no.5
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• pp.549-554
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• 2012

It was known that triphenyl phosphate wasn't homogeneously dispersed in HDPE/EPDM/boron carbide blends, which caused the decrease in mechanical properties. HDPE, EPDM, boron carbide, and triphenyl phosphate were blended with PE-g-MAH(polyethylene-graft-maleic anhydride) as a compatiblizer for improving the miscibility of triphenyl phosphate. Tensile strength of HDPE/EPDM/boron carbide blends decreased with increasing the contents of triphenyl phosphate for flammability. However, the mechanical properties of HDPE/EPDM/boron carbide/triphenyl phosphate blends increased by the addition of compatiblizer because triphenyl phosphate was homogeneously mixed in the blend system. The homogeneous dispersibility of triphenyl phosphate was confirmed by using scanning electron microscopy (SEM). Increased thermal stability and flammability derived from high miscibility of triphenyl phosphate were confirmed by the results of thermogravimetric analysis (TGA) and limiting oxygen index (LOI). A self-extinguishing HDPE/EPDM/boron carbide/triphenyl phosphate blend was successfully fabricated with more than 21% LOI.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.4
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• pp.117-122
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• 2021

In recent years, human damage and loss of money due to various disasters such as typhoons, earthquakes, forest fires, landslides, and wars are steadily occurring, and a lot of manpower and funds are required to prevent and recover them. In this paper, we designed and developed a disaster drone system based on artificial intelligence in order to monitor these various disaster situations in advance and to quickly recognize and respond to disaster occurrence. In this study, multiple disaster drones are used in areas where it is difficult for humans to monitor, and each drone performs an efficient search with an optimal path by applying a deep learning-based optimal path algorithm. In addition, in order to solve the problem of insufficient battery capacity, which is a fundamental problem of drones, the optimal route of each drone is determined using Ant Colony Optimization (ACO) technology. In order to implement the proposed system, it was applied to a forest fire situation among various disaster situations, and a forest fire map was created based on the transmitted data, and a forest fire map was visually shown to the fire fighters dispatched by a drone equipped with a beam projector. In the proposed system, multiple drones can detect a disaster situation in a short time by simultaneously performing optimal path search and object recognition. Based on this research, it can be used to build disaster drone infrastructure, search for victims (sea, mountain, jungle), self-extinguishing fire using drones, and security drones.