Prediction of Detonation Velocity of Aluminized Explosive by Artificial Neural Network

Yue Qiang Jiang; Yong Gang Liu; Xin Tian; Gong Bing Li

doi:10.4028/www.scientific.net/AMR.790.673

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 790Prediction of Detonation Velocity of Aluminized...

Prediction of Detonation Velocity of Aluminized Explosive by Artificial Neural Network

Abstract:

In this study, a three-layer artificial neural network (ANN) model was constructed to predict the detonation velocity of aluminized explosive. Elemental composition and loading density were employed as input descriptors and detonation velocity was used as output. The dataset of 61 aluminized explosives was randomly divided into a training set (49) and a prediction set (12). After optimized by adjusting various parameters, the optimal condition of the neural network was obtained. Simulated with the final optimum neural network [812, calculated detonation velocity show good agreement with experimental results. It is shown that ANN is able to produce accurate predictions of the detonation velocity of aluminized explosive.

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Periodical:

Advanced Materials Research (Volume 790)

Pages:

673-676

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.790.673

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Online since:

September 2013

Authors:

Yue Qiang Jiang, Yong Gang Liu, Xin Tian, Gong Bing Li

Keywords:

Aluminized Explosive, Artificial Neural Network (ANN), Detonation Velocity

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