| 研究課題/領域番号 |
20J10276
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| 研究機関 | 東北大学 |
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研究代表者 |
ティワリ ニトゥ 東北大学, 工学研究科, 特別研究員(PD)
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| 研究期間 (年度) |
2020-04-24 – 2022-03-31
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| キーワード | Pressure measurement / Non- Newtonian fluid / Data driven / stochastic estimation / sensor selection |
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| 研究実績の概要 |
My research aims to enhance the capability of existing flow measurement experimental devices. First objective of my work is to provide the pressure field measurement tool for opaque and non-Newtonian fluids because direct pressure field measurement is still not possible in fluids (except air) by available experimental devices. In my research I have developed three novel algorithms for pressure estimation for opaque and non-Newtonian fluids. I have published my results in international Journal Flow measurement and instrumentation. Second objective of my work is to increase the resolution of measurement tool. I am developing new technique based on data driven models to increase the temporal resolution of measurement.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
I have developed three novel pressure estimation algorithms for opaque and non-Newtonian fluids. Based on these results one of my research paper is published in international Journal "Flow measurement and instrumentation". Second paper is under review in "Experiments in Fluids". I have been working on application of data driven techniques for temporal resolution improvement. I have completed most of the experiments and now conducting postprocessing. I will be able to write some new papers in coming months.
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| 今後の研究の推進方策 |
Required experiments for implementation of data driven techniques to enhance the experimental capability had been done. The experiments consist of time resolved measurements of supersonic jet with schlieren technique. The idea is to implement linear stochastic estimation for high speed flows to increase temporal resolution. Simultaneous pressure and temperature distributions measurement using sensitive paints has been done. The plan is to reconstruct the temperature distribution by just measuring temperature at few points using a sensor selection model.
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