Prediction of detonation velocity of aluminized explosive by Artificial Neural Network

摘要：

　　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 8-12-1,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.

关键词： aluminized explosive detonation velocity Artificial Neural Network

作者: Jiang Yueqiang Liu Yonggang Tian Xin Li Gongbing

作者单位: Institute of Chemical Materials,CAEP,China School of Chemical,Sichuan University,China

会议类型: 国际会议

会议名称: 2013 International Conference on Advanced Engineering Materials and Architecture Sciences(2013先进工程材料与建筑科学国际会议)(ICAEMAS 2013)

会议地点: 西安

会议语种:英文

页码: 688-691

在线出版日期: 2013-07-27（万方平台首次上网日期，不代表论文的发表时间）