• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to previous page

Development of an innovative model to predict solidification structures using data science approach

Research Project

Project/Area Number 17K06874
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Metal making/Resorce production engineering
Research InstitutionAkita University

Principal Investigator

Natsume Yukinobu  秋田大学, 理工学研究科, 准教授 (80632752)

Project Period (FY) 2017-04-01 – 2020-03-31
Project Status Completed (Fiscal Year 2019)
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)
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.

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。

Report

(4 results)
  • 2019 Annual Research Report   Final Research Report ( PDF )
  • 2018 Research-status Report
  • 2017 Research-status Report
  • Research Products

    (5 results)

All 2020 2019 2018 2017

All Journal Article (1 results) (of which Peer Reviewed: 1 results,  Open Access: 1 results) Presentation (4 results) (of which Invited: 1 results)

  • [Journal Article] Estimation of Time-dependent Heat Transfer Coefficient in Unidirectional Casting Using a Numerical Model Coupled with Solidification Analysis and Data Assimilation2020

    • Author(s)
      Yukinobu NATSUME, Yukimi OKA, Jota OGAWA, Munekazu OHNO
    • Journal Title

      International Journal of Heat and Mass Transfer

      Volume: 150 Pages: 119222-119222

    • DOI

      10.1016/j.ijheatmasstransfer.2019.119222

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed / Open Access
  • [Presentation] 鋳造組織シミュレーションへのデータサイエンスの適用2019

    • Author(s)
      棗 千修
    • Organizer
      秋田大学革新材料研究センター(セミナー)
    • Related Report
      2019 Annual Research Report
    • Invited
  • [Presentation] データ同化を利用した一方向凝固解析における時間依存熱伝達係数の自動推定2018

    • Author(s)
      棗千修,内山涼介,岡ゆきみ,大野宗一
    • Organizer
      日本鋳造工学会 第97回東北支部鋳造技術部会
    • Related Report
      2018 Research-status Report
  • [Presentation] 粒子フィルタに基づく熱伝達係数の推定を導入した凝固解析による一方向鋳造実験の冷却曲線再現2018

    • Author(s)
      棗千修,内山涼介,岡ゆきみ,大野宗一
    • Organizer
      日本鉄鋼協会 第176回秋季講演大会
    • Related Report
      2018 Research-status Report
  • [Presentation] セルオートマトンモデルを用いた凝固組織形成シミュレーションにおける組織再現性2017

    • Author(s)
      内山涼介,棗千修
    • Organizer
      日本金属学会
    • Related Report
      2017 Research-status Report

URL: 

Published: 2017-04-28   Modified: 2021-02-19  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi