燃料空气炸药爆轰产物JWL状态方程参数计算

The JWL EOS parameters of detonation products for high explosives are generally determined by the cylinder test. However, the cylinder test is not suitable for fuel air explosives (FAE), which is cloud-like in a macro state. A method for calculating the EOS parameters based on the experimental data of FAE detonation in external field is established to determine the JWL EOS parameters of FAE detonation products. A back propagation neural-based genetic algorithm (BPNN-GA) is introduced into the method. The calculated values are compared with the data from the single- and multi-source external field experiments. The research shows that the introduction of BPNN-GA can simplify the EOS parameter optimization process and also improve the speed and accuracy. Based on the obtained JWL EOS parameters of FAE, the single- and multi-source FAE cloud detonation models are established. The profile of shockwave front from the simulation is consistent with the morphology of actual detonation shockwave. The maximum deviations between simulated and experimental values of the ground peak overpressure at the 50 m measuring points from single- and multi-source are 9.0% and 11.1%, respectively.