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Effect of Variable Selection on Multidisciplinary Design Optimization: a Flight Vehicle Example

机译：变量选择对​​多学科设计优化的影响：飞行器示例

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摘要

Different multidisciplinary design optimization (MDO) problems are formulated and compared. Two MDO formulations are applied to a sounding rocket in order to optimize the performance of the rocket. In the MDO of the referred vehicle, three disciplines have been considered, which are trajectory, propulsion and aerodynamics. A special design structure matrix is developed to assist data exchange between disciplines. This design process uses response surface method (RSM) for multidisciplinary optimization of the rocket. The RSM is applied to the design in two categories: the propulsion model and the system level. In the propulsion model, RSM determines an approximate mathematical model of the engine output parameters as a function of design variables. In the system level, RSM fits a surface of objective function versus design variables. In the first MDO problem formulation, two design variables are selected to form propulsion discipline. In the second one, three new design variables from geometry are added and finally, an optimization method is applied to the response surface in the system level in order to find the best result. Application of the first developed multidisciplinary design optimization procedure increased accessible altitude (performance index) of the referred sounding rocket by twenty five percents and the second one twenty nine.
机译：制定并比较了不同的多学科设计优化（MDO）问题。为了优化火箭的性能，将两种MDO公式应用于探空火箭。在所提及车辆的MDO中，考虑了三个方面，即轨迹，推进和空气动力学。开发了一个特殊的设计结构矩阵，以帮助各学科之间进行数据交换。该设计过程使用响应面方法（RSM）对火箭进行多学科优化。 RSM在设计中分为两类：推进模型和系统级。在推进模型中，RSM根据设计变量确定发动机输出参数的近似数学模型。在系统级别，RSM适合目标函数与设计变量之间的关系。在第一个MDO问题公式中，选择了两个设计变量来形成推进规则。在第二篇文章中，从几何中添加了三个新的设计变量，最后，在系统级对响应曲面应用了一种优化方法，以便找到最佳结果。第一个开发的多学科设计优化程序的应用使所提及的探空火箭的可到达高度（性能指数）提高了25％，第二个提高了29％。

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