2022 Fiscal Year Final Research Report
Topological data analysis for elucidating the mechanism of unsteady phenomena in aircraft
| Project/Area Number |
19K12095
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 61030:Intelligent informatics-related
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| Research Institution | The University of Electro-Communications |
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Principal Investigator |
Chiba Kazuhisa 電気通信大学, 大学院情報理工学研究科, 教授 (50450705)
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| Project Period (FY) |
2019-04-01 – 2023-03-31
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| Keywords | 位相的データ解析 / パーシステントホモロジー / 非定常空気力学 / 遷音速バフェット |
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| Outline of Final Research Achievements |
This study has investigated the quantification and detection of transonic buffeting intensity using persistent homology. The physical quantity treated by the Navier-Stokes equation is replaced by homology indirectly treated in mathematical space. As a result, the buffet was detected from data at arbitrary observation points on the wing surface in the region of the shock wave passage. Although both the pressure coefficient and the gradient in the uniform flow velocity can detect buffeting, the gradient in the uniform flow velocity indicates a significant difference in the buffet intensity and is a more appropriate indicator. The application of this method suggests that transonic buffets can be detected in real-time from the wing surface sensor data currently acquired by the aircraft.
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| Free Research Field |
高速空気力学
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| Academic Significance and Societal Importance of the Research Achievements |
航空機の安全性の劇的向上に対する自然現象に起因するボトルネックは，非定常な物理現象である．民間航空機の就航以来多様に研究されてきたが，非定常現象を伴う飛行データはカオス的で解析が困難なため，物理メカニズムは未解明で，現在も重大事故を誘引している．
本研究で行ったパーシステントホモロジーを用いた位相的データ解析法は，カオス的飛行データからバフェット強度を定量化した．航空機が運航中取得するセンサデータを利用できるため，本手法の利用のみで，リアルタイムでの遷音速バフェット発生検知が可能となり，安全性を定量的に計測できる．バフェットの時間的発生起点も特定でき，物理メカニズム追究の一助にもなる．
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