Development of an innovative model to predict solidification structures using data science approach
Project/Area Number |
17K06874
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Metal making/Resorce production engineering
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Research Institution | Akita University |
Principal Investigator |
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Project Period (FY) |
2017-04-01 – 2020-03-31
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Project Status |
Completed (Fiscal Year 2019)
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Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
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Keywords | 凝固 / データ同化 / データサイエンス / 凝固組織 / 鋳造 / セルオートマトン法 / 熱伝達係数 / 金属生産工学 / シミュレーション / 材料組織 |
Outline of Final Research Achievements |
A method to estimate the heat transfer coefficient based on data assimilation has been developed for the casting processes. To understand its usefulness for estimating the time-dependent heat transfer coefficient, herein we performed the experiments of unidirectional and sand castings. The experimental data were then used to validate the estimated time-dependent heat transfer coefficient. Consequently, the measured cooling curves could be accurately simulated. Next, the nucleation parameters including in a numerical model to predict solidification structures were estimated using the data assimilation technique. We confirmed that the parameter estimations for simulating quantitatively the grain size of solidification structures could be easily and quickly performed without trial and error. Therefore, it was found that the data science approaches were very useful and effective tools to advance the models to simulate the solidification processes.
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Academic Significance and Societal Importance of the Research Achievements |
本研究課題で得られた研究成果の学術的意義は,従来の凝固組織予測法には用いられていなかったデータサイエンス的アプローチを,モデル内の各種パラメータ評価に用い,評価者の主観によるパラメータの不確実性や高度な専門知識に基づく評価基準を排除できる方法を構築したことであり,これは,凝固組織予測法の幅広い産業応用への課題でもあるため,今後,応用研究としてさらに発展させることで社会的にも意義ある成果であると考えている。
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Report
(4 results)
Research Products
(5 results)