著者

杉浦 正彦 田辺 安忠 菅原 瑛明 木村 桂大 竹川 国之 大山 聖 佐藤 允 金崎 雅博 岸 祐希 SUGIURA Masahiko TANABE Yasutada SUGAWARA Hideaki KIMURA Keita TAKEKAWA Kuniyuki OYAMA Akira SATO Makoto KANAZAKI Masahiro KISHI Yuki

出版者

宇宙航空研究開発機構(JAXA)

雑誌

宇宙航空研究開発機構特別資料: 流体力学講演会/航空宇宙数値シミュレーション技術シンポジウム2020オンライン論文集 = JAXA Special Publication: Proceedings of Fluid Dynamics Conference / Aerospace Numerical Simulation Symposium 2020 Online (ISSN:24332232)

巻号頁・発行日

vol.JAXA-SP-20-008, pp.157-164, 2021-02-08

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流体力学講演会/航空宇宙数値シミュレーション技術シンポジウム2020オンライン (2020年9月28日-30日. 日本航空宇宙学会 : 宇宙航空研究開発機構(JAXA)オンライン会議)

著者

大山 聖 永井 大樹 藤田 昂志 安養寺 正之 岡本 正人 江 光希 金崎 雅博 高野 敦 水上 諒 竹内 伸介 安部 明雄 佐々 修一 布田 翼 満武 勝嗣 得竹 浩 火星探査航空機リサーチグループ Oyama Akira Nagai Hiroki Fujita Koji Anyoji Masayuki Okamoto Masato Koh Mitsuki Kanazaki Masahiro Takano Atsushi Mizukami Ryo Takeuchi Shinsuke Abe Akio Sasa Shuichi Futa Tsubasa Mitsutake Katsushi Tokutake Hiroshi

出版者

宇宙航空研究開発機構宇宙科学研究所(JAXA)(ISAS)

雑誌

大気球シンポジウム: 平成30年度 = Balloon Symposium: 2018

巻号頁・発行日

2018-11

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大気球シンポジウム 平成30年度(2018年11月1-2日. 宇宙航空研究開発機構宇宙科学研究所 (JAXA)(ISAS)), 相模原市, 神奈川県

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 13

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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.

著者

後藤 駿 金崎 雅博 村山 光宏 伊藤 靖 山本 一臣 Goto Shun Kanazaki Masahiro Murayama Mitsuhiro Ito Yasushi Yamamoto Kazuomi

出版者

宇宙航空研究開発機構(JAXA)

雑誌

宇宙航空研究開発機構特別資料: 第48回流体力学講演会/第34回航空宇宙数値シミュレーション技術シンポジウム論文集 = JAXA Special Publication: Proceedings of the 48th Fluid Dynamics Conference / the 34th Aerospace Numerical Simulation Symposium (ISSN:1349113X)

巻号頁・発行日

vol.JAXA-SP-16-007, pp.189-194, 2016-12-27

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第48回流体力学講演会/第34回航空宇宙数値シミュレーション技術シンポジウム (2016年7月6日-8日. 金沢歌劇座), 金沢市, 石川

著者

KANAZAKI Masahiro SETO Naoto

出版者

日本機械学会

雑誌

Journal of Computational Science and Technology (ISSN:18816894)

巻号頁・発行日

vol.6, no.1, pp.1-15, 2012

被引用文献数

3

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Efficient global optimization (EGO) was applied to the multi-objective design and knowledge discovery of a supersonic transport (SST) wing. The objective functions considered here are employed to maximize the lift–to-drag ratio at supersonic cruise, to minimize the sonic boom intensity and to minimize wing structural weight, simultaneously. The EGO process is based on Kriging surrogate models, which were constructed using several sample designs. Subsequently, the solution space could be explored through the maximization of expected improvement (EI) values that corresponded to the objective function of each Kriging model because the surrogate models provide an estimate of the uncertainty at the predicted point. Once a number of solutions have been obtained for the EI maximization problem by means of a multi-objective genetic algorithm (MOGA), the sample designs could be used to improve the models' accuracy and identify the optimum solutions at the same time. In this paper, 108 sample points are evaluated for the constructions of the Kriging models. In order to obtain further information about the design space, two knowledge discovery techniques are applied once the sampling process is completed. First, through functional analysis of variance (ANOVA), quantitative information is gathered and then, self-organizing maps (SOMs) are created to qualitatively evaluate the aircraft design. The proposed design process provides valuable information for the efficient design of an SST wing.