2022 Fiscal Year Final Research Report
Estimation of Scalar Source in Turbulent Environment by Using Moving Sensors
| Project/Area Number |
20H02063
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Review Section |
Basic Section 19010:Fluid engineering-related
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| Research Institution | The University of Tokyo |
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Principal Investigator |
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| Project Period (FY) |
2020-04-01 – 2023-03-31
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| Keywords | 乱流 / スカラー源推定 / 移動ロボット群 |
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| Outline of Final Research Achievements |
Estimating scalar sources in turbulent environments is a challenging task. So far, a large mount of studies discuss how to estimate scalar sources and flow fields based on given sensor signals. Meanwhile, the estimation performance mostly depends on which physical quantity is measured and at which location. In the present study, we applied Gaussian process and/or machine learning techniques in order to achieve better estimation performances and also optimize sensor arrangements for this purpose. The proposed algorithms were verified through numerical simulation of scalar transfer in complex flow fields, and also validated through wind tunnel experiments and mobile robots equipped with a concentration sensor.
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| Free Research Field |
熱流体工学
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| Academic Significance and Societal Importance of the Research Achievements |
大気や海洋中を拡散する汚染物質や有害物質の時空間分布を正確に推定し，その発生源を同定することは，災害やテロ発生時における人々の安全・安心を保証する上で，極めて重要である．学術的には乱流中に放出されたスカラーは，流れによって移流し，引き延ばされることにより複雑なスカラー場を形成し，下流のセンサ信号は極めて複雑なものとなる．このような限られた計測情報からスカラー源を推定することは依然として極めて困難であるため，効果的なスカラー源推定アルゴリズムを開発することは意義が大きい．さらに，開発したアルゴリズムを実験を通じて実証する試みも限られており，本研究で開発する実験システムは学術的な意義が大きい．
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