| Budget Amount *help |
¥17,940,000 (Direct Cost: ¥13,800,000、Indirect Cost: ¥4,140,000)
Fiscal Year 2022: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2021: ¥6,630,000 (Direct Cost: ¥5,100,000、Indirect Cost: ¥1,530,000)
Fiscal Year 2020: ¥8,580,000 (Direct Cost: ¥6,600,000、Indirect Cost: ¥1,980,000)
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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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