Automatic Optimization of JWL‐Miller parameters of HMX‐based aluminized explosive based on genetic algorithm

Abstract

The calibration of JWL‐Miller equation of state (EOS) parameters for aluminized explosive is a cumbersome but important work in explosive evaluation. Manual calibration is usually adopted while the work may be tedious and the optimal results may be unachievable. An automatic calibrating method was established to optimize this procedure based on genetic algorithm program and finite element software. Optimal JWL‐Miller EOS parameters were achieved by iterative calculation calibrating with cylinder test results and underwater‐explosion experiment results. Cylinder test results were adopted to illustrate the initial phase of explosion, and underwater explosion experiments were conducted to calibrating the Miller term of the equation of state. The results showed that the error between cylinder test and simulation result was less than 1 %, the error of underwater explosion impulse between test and simulation results was less than 3.73 %. The optimized parameters of JWL‐Miller EOS will be useful in the numerical simulation research of aluminized explosives.