Affiliations: [a] Wuhan University of Science and Technology, Wuhan, Hubei, China | [b] Hubei Intelligent Blasting Engineering Research Center, Wuhan, Hubei, China
Correspondence:
[*]
Corresponding author: Dongwang Zhong, Wuhan University of Science and Technology, Wuhan, Hubei 430065, China. E-mail: [email protected].
Abstract: The water medium explosion container is an experimental device that simulates explosion in different water depth environments by loading different hydrostatic pressures and different doses of explosive. To ensure its safety during service, it is necessary to study the dynamic response of water medium explosion container. Because the dynamic response is complicated and the correlation between the response and the load of the container is nonlinear, it is difficult to calculate the dynamic response by analytical and numerical methods. In this paper, a model is built based on convolutional neural network (CNN) to predict the dynamic response of water medium explosion container. The accuracy and usability of the CNN prediction model are verified by comparison with the prediction results of the BP neural network model. The results show that CNN can be effectively used to predict the strain response of the dynamic response of water medium explosion container. and this method will play an important role in the later study of the overall feature analysis of the dynamic response of the water medium explosion vessel.
Keywords: Water medium explosion container, dynamic response, convolutional neural network, bp neural network
