Impact Analysis of Different Trajectory Shapes on Optimization Based on Original Natural Algorithm

• Published in: International journal of aerospace engineering 2024-03, Vol.2024, p.1-11
• Main Authors: Chen, Yijing, Nan, Ying, Li, Zhihan
• Format: Article
• Language: English
• Subjects: Aerodynamic heating; Aerospace environments; Aircraft; Algorithms; Atmosphere; Aviation; Collaboration; Flight; Heating rate; Impact analysis; Methods; Natural algorithms; Optimization; Parameters; Reentry trajectories; Shape optimization; Spacecraft guidance; Spaceplanes; Thermal protection; Trajectory analysis; Trajectory optimization; Variables
• ISSN: 1687-5966; 1687-5974
• DOI: 10.1155/2024/5569229

In this paper, the reentry phase of the Aerospaceplane is taken as the research object, and the performance parameters of the reusable rocket of a private company are analyzed. Aiming at the guidance and control scheme of the spacecraft returning to the reentry trajectory in the real environment, the original natural algorithm is optimized by considering various reentry flight constraints, and the improved original natural algorithm is used to optimize the reentry trajectory of the Aerospaceplane. We obtained two types of reentry trajectories in the presence of large flight-restricted areas, the “S-type” trajectory and the “spiral-type” trajectory, and obtained data on various influencing factors. The results showed that the basic state parameters of the spiral trajectory optimized using the improved original natural algorithm after adding constraints met the constraint conditions. The aerodynamic heating rate and overload of the spiral reentry trajectory were to some extent greater than those of the S-type trajectory. Under the increasingly stringent requirements of the aerospace environment, new requirements were put forward for the thermal protection system to meet the wider environmental situation. This paper uses the improved original natural algorithm for the first time and applies it to the field of aerospace reentry and entry and adds more constraints to this algorithm for computation. Besides, for the first time, the macroscopic nature of trajectory types is used as a comparative element for parameter comparison, providing a reference basis for selecting trajectory optimization directions from the macroscopic perspective of trajectory types.