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Abstract
The possibility of the impact sensitivity prediction based on the physicochemical properties and element composition of explosives contributes to a faster research of novel high explosives (HE), reduces the research costs and helps to improve the explosive safety. This paper analyzes the existing methods for the prediction of impact sensitivity and introduces a response surface methodology (RSM). The new method comprises a correlation between impact sensitivity and two primary properties of HE: detonation velocity and heat of detonation. Calculated impact sensitivities are compared to the experimental values taken from the literature in order to validate the approach.
Highlights
THE research in the field of high explosives (HE) has a growing tendency to achieve better explosive performance that is often accompanied with the energy content increase
Where h50 is in J, ρ is in g cm-3, B is in g atom kg-1, Qmax is in kcal kg-1 and Tm is in °C
The h50 value of impact sensitivity is considered as the output variable
Summary
THE research in the field of high explosives (HE) has a growing tendency to achieve better explosive performance that is often accompanied with the energy content increase. Because sensitivity is a major characteristic of HE, it is especially desirable to have a valid method of predicting sensitivity based on the available experimental and calculated data. The performance and sensitivity properties of a candidate for a new high explosive as well as for a new HE mixture are very important because its development, manufacture and testing is cost effective, environmentally desirable and because of its time saving capabilities. Detonation velocity and the heat of detonation are used in this paper to predict impact sensitivity of the selected mixtures of aluminized HE. The purpose of this paper is to predict a simple correlation between impact sensitivity of the aluminized HE mixtures and chosen detonation parameters using the response surface methodology [20]. The coefficients of the response function and their statistical significance were evaluated by the least squares method using the DesignExpert v.9.0 software, Stat-Ease, Inc
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