| 摘要: |
| 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。 |
| 关键词: 遗传算法 支持向量机 推进剂 配方优化 |
| DOI： |
| 分类号: |
| 基金项目:国家部委科研项目(40406030201)。 |
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| Application of Genetic Algorithm-Support Vector Machine in Formula Optimization of Mg/PTFE Fuel Rich Propellant |
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FAN Lei, PAN Gong-pei, OUYANG De-hua, CHEN Xin, PANG Gao-feng
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School of Chemical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
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| Abstract: |
| 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. |
| Key words: Genetic algorithm Support vector machine Propellant Formula optimization |
