Entire aerial-aquatic trajectory modeling and optimization for trans-medium vehicles
Trans-medium flight vehicles can combine high aerial maneuverability and underwater concealment ability, which have attracted much attention recently. As the most crucial procedure, the trajectory design generally determines the trans-medium flight vehicle performance. To quantitatively analyze the...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2025-07-01
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| Series: | Defence Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214914725000534 |
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| Summary: | Trans-medium flight vehicles can combine high aerial maneuverability and underwater concealment ability, which have attracted much attention recently. As the most crucial procedure, the trajectory design generally determines the trans-medium flight vehicle performance. To quantitatively analyze the flight vehicle performance, an entire aerial-aquatic trajectory model is developed in this paper. Different from modeling a trajectory purely for the water entry process, the constructed entire trajectory model has integrated aerial, water entry, and underwater trajectories together, which can consider the influence of the connected trajectories. As for the aerial and underwater trajectories, explicit dynamic models are established to obtain the trajectory parameters. Due to the complicated fluid force during high-velocity water entry, a computational fluid dynamics model is investigated to analyze this phase. The computational domain size is adaptively refined according to the final aerial trajectory state, where the redundant computational domain is removed. An entire trajectory optimization problem is then formulated to maximize the total flight range via tuning the joint states of different trajectories. Simultaneously, several constraints, i.e., the max impact load, trajectory height, etc., are involved in the optimization problem. Rather than directly optimizing by a heuristic algorithm, a multi-surrogate cooperative sampling-based optimization method is proposed to alleviate the computational complexity of the entire trajectory optimization problem. In this method, various surrogates cooperatively generate infill sample points, thereby preventing the poor approximation. After optimization, the total flight range can be improved by 20%, while all the constraints are satisfied. The result demonstrates the effectiveness and practicability of the developed model and optimization framework. |
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| ISSN: | 2214-9147 |