Genetic Algorithm Applied to Design Knowledge Discovery of Launch Vehicle Using Clustered Hybrid Rocket

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Abstract

The conceptual design of a multi-stage launch vehicle (LV) using a clustered hybrid rocket engine (HRE) is carried out through multi-disciplinary design optimization. This LV designed in this study can deliver micro-satellites to sunsynchronous orbits (SSO). The optimum size of each component, such as an oxidizer tank containing liquid oxidizer, a combustion chamber containing solid fuel, a pressurizing tank, and a nozzle, should be strictly optimized because of the combustion mechanism is different from existent liquid/solid rocket engines. In this study, the semi-empirical based evaluation is applied to the design optimization of the multi-stage LV. For clustered HRE, paraffin (FT-0070) is used as a propellant for the HRE, and three cases are compared to examine the commonization effect of the engine for each stage: In the first case, HREs are optimized for each stage. In the second case, HREs are optimized together for the first and second stages but separately for the third stage. In the third case, HREs are optimized together for each stage. The optimization results show that the performance of the design case that uses the same HREs in all stages is 40% reduced compared with the design case that uses optimized HREs for each stage.

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Kanazaki, M., Chiba, K., Ito, S., Nakamiya, M., Kitagawa, K., & Shimada, T. (2019). Genetic Algorithm Applied to Design Knowledge Discovery of Launch Vehicle Using Clustered Hybrid Rocket. In Computational Methods in Applied Sciences (Vol. 48, pp. 519–535). Springer Netherland. https://doi.org/10.1007/978-3-319-89988-6_31

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