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MEMBERS

Muramatsu, M., Yashiro, K., Kawada, T. and Terada, K., “Simulation of Ferroelastic Phase Formation Using Phase-field Model”, International Journal of Mechanical Sciences, Vols. 146-147, pp. 462-474, (2018).https://doi.org/10.1016/j.ijmecsci.2017.12.027

Achievement of Misato Suzuki

Paper

  1. Suzuki, M., Shizawa, K., Muramatsu, M., “Deep learning-aided inverse analysis framework to accelerate the exploration of DP steel microstructures”, Materials Today Communications, Vol. 41, pp. 110557 1-17, (2024). https://doi.org/10.1016/j.mtcomm.2024.110557

International conference

  1. Ikeda, A.*，Higuchi, R., Yokozeki, T., Endo, K., Kojima, Y., Suzuki, M., Muramatsu, M., “Prediction of Microstructures of Dendrite Crystals and Process Parameters for Thermoplastic Resin Based on Mechanical Properties Using The Conditional Diffusion Model”, 16th World Congress on Computation Mechanics & 4th Pan American Congress on Computational Mechanics (WCCM-PANACM2024), Canada (2024), MS??, ??.
  2. Suzuki, M.*，Shizawa, K., Muramatsu, M., “Evaluation of mechanical properties of three-dimensional polycrystalline microstructures of dual-phase steel using machine learning model based on phase-field method and crystal plasticity finite element method”, 16th World Congress on Computation Mechanics & 4th Pan American Congress on Computational Mechanics (WCCM-PANACM2024), Canada (2024), MS??, ??.
  3. Suzuki, M.*，Shizawa, K., Muramatsu, M., “Evaluation of Effect of Microstructures on Mechanical Properties of Dual-phase Steel”, International Conference in an explosively growing informatics world (CIMTEC2024), Italy (2024), P01.
  4. 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.
  5. 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. 池⽥有沙*, 樋⼝諒, 横関智弘, 遠藤克浩, 児嶋佑太, 鈴⽊美智, 村松眞由「Conditional Diffusionモデルを⽤いた⼒学特性に基づく熱可塑性樹脂のデンドライト結晶および加⼯温度の予測｣, 第29回計算工学講演会, ?-??-?? (6 pages), (2024).
  2. 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).
  3. 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).
  4. 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).

Award

  1. 2022年度 慶應義塾大学理工学部機械工学科 優秀発表賞（2023.03.23）
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