MEMBERS

Hiraide, K., Hirayama, K., Endo, K., Muramatsu, M., “Application of deep learning to inverse design of phase separation structure in polymer alloy”, Computational Materials Science, Vol. 190, pp. 110278, 1-9, (2021).https://doi.org/10.1016/j.commatsci.2021.110278

Achievement of Misato Suzuki

International conference

  1. Muramatsu, M.*, Suzuki, M., Shizawa,K., “Dislocation-crystal Plasticity Simulation for Investigation of Grain Size Dependency in Dual Phase Steel”, XVII International Conference on Computational Plasticity, Fundamentals and Applications (COMPLAS2023), Spain (2023), IS1703b-1.
  2. Suzuki, M.*, Shizawa. K., Muramatsu, M., “Investigation on Optimal Microstructure of Dual Phase Steel with High Strength and Ductility by Machine Learning”, XVII International Conference on Computational Plasticity, Fundamentals and Applications (COMPLAS2023), Spain (2023), IS1703d-4.

Domestic conference

  1. 鈴木美智*, 志澤一之, 村松眞由「Phase-field法および結晶塑性解析による3次元多結晶体Dual Phase鋼の力学特性評価」, 第36回日本機械学会計算力学講演会講演論文集, OS20-04 (4 pages), (2023).
  2. 鈴木美智*, 志澤一之, 村松眞由「機械学習を用いたPhase-field法と結晶塑性解析によるDual Phase鋼材料組織の探索」, ナノ力学若手交流会, P2-54, (2023).
  3. 鈴木美智*, 志澤一之, 村松眞由「機械学習による高強度・高延性を示す最適なDual Phase鋼材料組織の探索」, 第28回計算工学講演会, A-12-05 (6 pages), (2023).
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