Developing methods to evaluate the effectiveness of camouflage against thermal reconnaissance devices reliably and close to reality is an urgent requirement today. Therefore, applying camouflage solutions against thermal reconnaissance equipment has been developing rapidly in many countries. However, to reach the target, it is essential to develop a process and method to evaluate the properties of camouflage materials and means in the laboratory, simulate targets in the virtual environment, and asset the effectiveness of camouflage directly at the scene. In Vietnam, research in the field still needs more information and has only recently been implemented. To deal with the target above, the research team conducted studies to develop and evaluate the effectiveness of thermal camouflage. This article focuses on developing a complete procedure for the field method to evaluate the effectiveness of thermal camouflage. The result can be applied to evaluate and select the thermal camouflage material and facilities in jungle - mountainous terrain.Thermal imaging
Enhance blast resistance of defensive structure systems on the island is one of the most important research trending today. The paper is aimed to use Monte-Carlo simulation method to evaluate effectiveness of the defensive structures before and after upgrading the blast resistances. The result is the basis for assessing and comparing the actual protective effect of the defensive structure system among possible combat scenarios.
The difficulty in solving finite element programs is to estimate the appropriate element size to obtain a reliable solution. Therefore, the element(s) size and meshing density is required to be determined reasonably. However, almost models ignored that problem or have to solve it by hand. In addition, the processes recreate meshing, and updating the total model is a really big deal because of time-consuming. To establish a proper mesh convergence method, it is required to plot the curve for a critical result (typically stress or displacement) in a specific part or point in the considered model versus mesh density. To deal with it, the article is aimed to introduce how to use the Python script to estimate mesh convergence. The method uses the Python script automatically to refine the mesh and update the system. In addition, at least three convergence results are displayed to plot a curve which can be used to indicate the achieved convergence. Finally, the article also suggests some critical conditions for implicit and explicit problems to archive the optimum convergence.
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