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Inverse design framework for optimizing solid propellant grains toward target performance profiles
DOI:10.1016/j.actaastro.2025.09.039.png)
摘要
En 中文
• 提出了一种固体推进剂药柱优化的逆向设计框架。
• 该方法识别满足性能要求的药柱构型。
• 算例验证了所提出方法的有效性。
• 该框架促进了推进系统设计的系统性开发。
Keyword:
Solid rocket motor
Artificial neural network
Genetic algorithm
Shape optimization
Burnback analysis
期刊
IF:
3.4
论文数:
1.2W
被引数:
2.1W
机构
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Ata Y., Kurtulus D.F., Arkun O.U., Development of a 3d grain burnback simulation tool for solid rocket motors. Advances in Sustainable Aviation 2018;:65–90.Ata Y., Kurtulus D.F., Arkun O.U., 固体火箭发动机3D颗粒燃烧回退模拟工具的开发。可持续航空进展 2018;:65–90.
Alyahya K., Rowe J.E., Simple random sampling estimation of the number of local optima. In: Parallel Problem Solving from Nature–PPSN XIV. Springer; 2016, p. 932–941.Alyahya K., Rowe J.E., 简单随机抽样估计局部最优解的数量。In: Parallel Problem Solving from Nature–PPSN XIV. Springer; 2016, p. 932–941.
Bhattacharya S., Mundhra R., Effect of using fractals as grain configuration on the performance of solid rocket motors. Heat Transfer Engineering 2025;46(9-10):852–864.Bhattacharya S., Mundhra R., 使用分形作为颗粒配置对固体火箭发动机性能的影响。Heat Transfer Engineering 2025;46(9-10):852–864.

