神经网络状态方程在强爆炸冲击波数值模拟中的应用

强爆炸数值模拟的主要挑战在于如何准确地描述爆炸产物状态方程。利用BP神经网络和强爆炸产物状态数据对神经网络产物状态方程进行训练，并将得到的状态方程植入自编的一维球对称数值模拟程序，对强爆炸冲击波参数进行了计算。结果显示，计算得到的冲击波峰值超压、冲击波到时、正压时间与标准值吻合较好，证明将神经网络状态方程应用于强爆炸冲击波数值模拟是可行的。研究结果对确定强爆炸数值模拟方法具有很好的借鉴意义。

Application of the neural network equation of state in numerical simulation of intense blast wave

The main challenge of numerical simulation of intense explosion is how to accurately determine the equations of state for the explosive products. The traditional equations of state are mostly empirical or semi-empirical formulas, which can just deal with ordinary explosions, but the treatment of intense explosions is of great limitation. The parameters of intense explosive products span an extremely wide range, which often exceeds the scope of empirical formula. Neural network has an excellent nonlinear fitting function and can realize the function of the equations of state. At the same time, there are a lot of state parameters of material in the sesame library, and the material parameters suitable for intense explosive products were selected as training data of neural network. The tabulated data of intensive explosive product samples were pretreated to make them better used in neural networks, then the data was adopted as training set to train the BP neural network and a one-dimensional spherical numerical code embedded with neural network equation of state was used to calculate the blast wave parameters of the explosion of fission device. In the process of neural network construction, the structure of neural network was optimized by enumeration experiment, and the structure of multi-layer neural network with a simple structure and good precision was obtained. In the process of numerical calculation, the code called the embedded neural network equations of state module, calculated the pressure of the explosive product through the density and the specific internal energy, and the flow field parameters of the whole explosive blast wave were finally obtained. The numerical results show that the calculated peak overpressure, arrival time and positive pressure duration coincide with the standard values, which proves the feasibility of the application of the neural network equation of states in the intense blast wave calculations. The results are of great significance to the numerical simulation of intense explosion.