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Two dimensional star grain optimization method using genetic algorithm

机译:基于遗传算法的二维星纹优化方法

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This study describes the internal ballistic and the design optimization of two-dimensional star grain of rocket motors. The burnback analysis and geometric modeling of grain geometry are calculated using star grain geometry. In this study, the grain geometry was modeled parametrically using CAD software. The internal ballistic analysis by using MATLAB program, we used zero dimensional method for calculating the performance prediction. Genetic Algorithm optimization method has been used. Average thrust maximization, total impulse maximization and minimizing the neutrality of thrust time curve under design constraints is the objective functions. The uses of Genetic Algorithm optimization method clear the problem of suitable initial guess. This idea proves increase in capability of optimal solutions. According to different objective function it is capable to choose which is suitable according to the results.
机译:这项研究描述了火箭发动机的内部弹道和二维星形结构的设计优化。使用星形晶粒几何形状计算晶粒几何形状的回烧分析和几何模型。在这项研究中,使用CAD软件对晶粒几何形状进行了参数化建模。通过使用MATLAB程序进行内部弹道分析,我们使用零维方法来计算性能预测。已经使用遗传算法优化方法。在设计约束下,平均推力最大化,总脉冲最大化和推力时间曲线的中性最小化是目标函数。遗传算法优化方法的使用消除了合适的初始猜测的问题。这个想法证明了最佳解决方案能力的提高。根据不同的目标函数,可以根据结果选择合适的目标函数。

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