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MEMBERS

Muramatsu, M., Yashiro, K., Kawada, T. and Terada, K., “Numerical simulations of non-stationary distributions of electrochemical potentials in SOFC”, Engineering Computations, Vol. 34, No. 6, pp. 1956-1988, (2017).https://doi.org/10.1108/EC-08-2016-0311

Achievement of Yuta Kojima

Paper

  1. Kojima, Y., Hirayama, K., Endo, K., Hiraide, K., Muramatsu, M., “Inverse Estimation Method for Internal Defects Based on Surface Stress of Carbon-Fiber-Reinforced Plastics Using Machine Learning”, Advanced Composite Materials, Vol. 31, pp. 617-629, (2022).https://doi.org/10.1080/09243046.2022.2052786

International conference

  1. Fujiwara, S.*，Okada，K., Endo，K., Kojima, Y., Ode, M., Muramatsu, M., “Evaluation method for the dendritic crystal by phase-field model using U-net and the effect of random terms”, 2nd IACM 2nd IACM Mechanistic Machine Learning and Digital Engineering for Computational Science Engineering and Technology (2nd IACM MMLDE-CSET), United States (2023), OS14, ID**. (Submitted)
  2. Kojima, Y.*，Hirayama，K., Endo，K., Harada, Y., Muramatsu, M., “Prediction of Three-dimensional Defectʼs Shape in Simple Shaped CFRP Specimens Using Transfer Learning Based on Two-dimensional Stress Distribution from Finite Element Analysis and Infrared Measurements”, 2nd IACM 2nd IACM Mechanistic Machine Learning and Digital Engineering for Computational Science Engineering and Technology (2nd IACM MMLDE-CSET), United States (2023), OS14, ID**. (Submitted)
  3. Kojima, Y.*，Hirayama，K., Endo，K., Hiraide, K., Muramatsu, M., Harada, Y., “Defects Analysis in Carbon Fiber Reinforced Plastic by Combining Machine Learning and Infrared Stress Analysis”, 15th World Congress on Computation Mecchanics & 8th Asian Pacific Congress on Computation Mechanics (WCCM-APCOM2022), Online (2022), MS1713, 2817.
  4. Kojima, Y.*, Hiraide, K., Hirayama, K., Endo, K., Muramatsu, M., Harada, Y. “Development of the Defects Detection System for Carbon Fiber Reinforced Plastic by Using Infrared Stress Analysis and Machine Learning”, 8th European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS2022), Norway (2022), MS117D-1.
  5. Kojima, Y.*, Hiraide, K., Hirayama, K., Endo, K., Muramatsu, M. “Estimation of Defects in Carbon Fiber Reinforced Plastic Based on Surface Pressure by Machine Learning”, XVI International Conference on Computational Plasticity (COMPLAS2021), Online, (2021), WM12-4.

Domestic conference

  1. 藤原紳也*, 児嶋佑太, 大出真知子, 村松眞由「フェーズフィールド法による2次元デンドライトの機械学習を用いた評価手法の提案｣, 第36回日本機械学会計算力学講演会講演論文集, OS08-* (* pages), (2023). (発表予定)
  2. 児嶋佑太*，平山健太，原田祥久，村松眞由「単純形状CFRP試験片の応力解析および熱伝導解析｣, M&M・CMD若手シンポジウム2023, ID* (* pages), (2023). (発表予定)
  3. 児嶋佑太*，平山健太，遠藤克浩, 原田祥久，村松眞由「有限要素解析による応力分布に基づく機械学習を用いた複雑形状CFRP試験片の欠陥3次元情報の予測｣, 第36回日本機械学会計算力学講演会講演論文集, OS24-* (* pages), (2023). (発表予定)
  4. 児嶋佑太*，遠藤克浩，平山健太, 原田祥久，村松眞由「有限要素解析および赤外線測定による応力分布に基づく転移学習を用いたCFRP 単純形状内の欠陥3次元情報の予測｣, 第28回計算工学講演会, A-11-01 (6 pages), (2023).
  5. 児嶋佑太*，遠藤克浩，平山健太，平出和也，村松眞由, 原田祥久「機械学習と赤外線応力測定を組み合わせた炭素繊維強化プラスチックの欠陥探索｣, 第27回計算工学講演会, C-07-02 (6 pages), (2022).
  6. 児嶋佑太*，遠藤克浩，平山健太，平出和也，村松眞由, 「機械学習を用いた炭素繊維強化プラスチック表面応力に基づく内部欠陥逆推定｣, 第26回計算工学講演会, B-07-03 (6 pages), (2021).
  7. 児嶋佑太*，村松眞由，遠藤克浩，平山健太，平出和也， ｢機械学習を用いた層間剝離を有する炭素繊維強化プラスチックの表面応力・欠陥解析｣, 日本機械学会関東学生会第60回学生員卒業研究発表講演会, OS4-418 (5 pages), (2021).

Award

  1. 自動車技術会 2022年度大学院研究奨励賞（2023.03.28）
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