- 著者
-
KITAGAWA Yosuke
KITAGAWA Koki
NAKAMIYA Masaki
KANAZAKI Masahiro
SHIMADA Toru
- 出版者
- THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES
- 雑誌
- Transactions of the Japan Society for Aeronautical and Space Sciences (ISSN:05493811)
- 巻号頁・発行日
- vol.55, no.4, pp.229-236, 2012-07-04
- 被引用文献数
-
1
14
The multi-objective genetic algorithm (MOGA) is applied to the multi-disciplinary conceptual design problem for a three-stage launch vehicle (LV) with a hybrid rocket engine (HRE). MOGA is an optimization tool used for multi-objective problems. The parallel coordinate plot (PCP), which is a data mining method, is employed in the post-process in MOGA for design knowledge discovery. A rocket that can deliver observing micro-satellites to the sun-synchronous orbit (SSO) is designed. It consists of an oxidizer tank containing liquid oxidizer, a combustion chamber containing solid fuel, a pressurizing tank and a nozzle. The objective functions considered in this study are to minimize the total mass of the rocket and to maximize the ratio of the payload mass to the total mass. To calculate the thrust and the engine size, the regression rate is estimated based on an empirical model for a paraffin (FT-0070) propellant. Several non-dominated solutions are obtained using MOGA, and design knowledge is discovered for the present hybrid rocket design problem using a PCP analysis. As a result, substantial knowledge on the design of an LV with an HRE is obtained for use in space transportation.