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Multi-Phase Trajectory Optimization for Access-to-Space with RBCC-Powered TSTO via Surrogated-Assisted Hybrid Evolutionary Algorithms Incorporating Pseudo-Spectral Methods

机译:结合伪谱方法的代理辅助混合进化算法,利用RBCC驱动的TSTO进行多相轨迹优化

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A multi-objective design optimization study coupling evolutionary algorithms and trajectory optimization via pseudo-spectral methods has been conducted for two-stage to orbit (TSTO) system with a rocket-based combined cycle (RBCC) comprising airbreathing components besides rocket engines, aiming to examine its feasibility to achieve efficient access to space, particularly to the international space station. The optimization has been performed with respect to three important design criteria, that is, the maximization of the final velocity, altitude, and mass at the terminus of the orbiter trajectory under certain constraints of acceleration and dynamic pressure. The results have revealed complex interactions of numerous design parameters and a counteractive trend between the final velocity and mass. Most influential parameters have been identified from trajectory investigation and sensitivity analysis, providing insights into the design requirements needed to fulfill the desired mission with the vehicle and propulsion configurations considered here.
机译:针对带有火箭联合循环(RBCC)的两阶段入轨(TSTO)系统进行了多阶段设计优化研究,该研究通过伪光谱方法将进化算法与轨迹优化结合起来,旨在除火箭发动机外还具有呼吸功能。审查其实现有效进入太空,特别是进入国际空间站的可行性。已针对三个重要的设计标准进行了优化,即在一定的加速度和动压力约束下,轨道速度终点处的最终速度,高度和质量达到了最大值。结果揭示了许多设计参数之间的复杂相互作用以及最终速度和质量之间的反作用趋势。已经从轨迹调查和灵敏度分析中识别出大多数有影响力的参数,从而洞悉了使用此处考虑的车辆和推进构型来实现所需任务所需的设计要求。

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