遗传算法在炸药爆轰参数计算中的应用

为解决爆轰参数计算中自变量取值范围要求严格以及收敛性差等问题，在最小自由能法的基础上，引入遗传算法建立了炸药爆轰参数的计算方法，并利用典型单质炸药和混合炸药的实验结果对计算结果进行了验证。结果表明:采用该方法计算得到的单质和混合炸药的爆速、爆压与实验测试结果基本一致，误差在5%以内，满足炸药性能预估的要求；该方法人工干预弱，只需一次性确定少数主要组分物质的量的变化范围，可适应于多配方优化计算。

Application of genetic algorithm to calculation of detonation parameters

To solve the problems of bad convergence and to satisfy the strict requirement to initial conditions in the calculation of detonation parameters, a new calculation method was proposed based on the principles of chemical equilibrium and the method of minimum free energy by introducing the genetic algorithm, and the calculated results of typical explosives were compared with the experimental data to verify the validity and the accuracy of the new method. It is demonstrated that, by the new method, the calculated results of detonation pressure and velocity of the explosives correspond well with the experimental data with the errors under 5%, which can be applied to predict explosive properties. Also, the computational process is convenient with little manual intervention and entails only the verification of the moles variation form of the few major ingredients, which may be used for multi-formula optimization design.