基于遗传算法结合支持向量机的Mg/PTFE贫氧推进剂配方优化

针对Mg/PTFE贫氧推进剂配方设计的复杂性,采用支持向量机理论建立了相关预测模型,结合遗传算法对模型结果进行多目标寻优,以此获得最佳的配方,最后对所得的最佳配方进行了实验验证。结果表明Mg/PTFE贫氧推进剂的最佳配方为PTFE/Mg=0.49,酚醛树脂含量为12.50%,镁粉粒度为26.90μm,PTFE粒度为111.33μm。遗传算法结合支持向量机的优化方法,适合于推进剂配方的优化,具有一定的实际应用价值。

Application of Genetic Algorithm-Support Vector Machine in Formula Optimization of Mg/PTFE Fuel Rich Propellant

According to the complexity of formulation design for Mg/PTFE fuel rich propellant,a prediction model of formulation design for Mg/PTFE fuel rich propellant with the support vector machine(SVM) was introduced,and the genetic algorithm(GA) was used for multi-objective optimization to obtain optimal formula composition,which was verified with experiment at last.Results show that the optimum formula composition for Mg/PTFE fuel rich propellant is PTFE/Mg= 0.49,the mass content of phenolic resin is 12.50%,the diameter of Mg is 26.90μm,the diameter of PTFE is 111.33μm.GA-SVM is suitable for formula optimization of Mg/PTFE fuel rich propellant,which has certain practical application value.