日本金属学会2022年秋期(第171回)講演大会
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Session Details

一般講演11.Computational Science : Data Science

[G]Data Science

Wed. Sep 21, 2022 3:05 PM - 5:00 PM JST
Wed. Sep 21, 2022 6:05 AM - 8:00 AM UTC
Rm. E D24,2Flr. Build.D
座長:北嶋　具教(物質・材料研究機構)、小山 敏幸(名古屋大学)
※表示の講演時間には質疑応答時間も含みます。
（質疑応答時間5分、基調講演と招待講演は5～10分）
3:05 PM - 3:20 PM JST(6:05 AM - 6:20 AM UTC)

[109]Parameter estimation for fluid flow based on data assimilation

*Kazuto Moriguchi1, Ryo Yamada1, Munekazu Ohno1 (1. Hokkaido Univ.)
3:20 PM - 3:35 PM JST(6:20 AM - 6:35 AM UTC)

[110]Development of machine learning model for inverse analysis of anisotropy strength of interfacial energy from microsegregation

*Souta FUKUZAWA1, Ryo Yamada2, Munekazu Ohno2 (1. Graduated school, Hokkaido Univ, 2. Hokkaido Univ)
3:35 PM - 3:50 PM JST(6:35 AM - 6:50 AM UTC)

[111]Search for high creep strength welding conditions considering HAZ shape factor

*Hitoshi IZUNO1, Masahiko DEMURA1, Satoshi MINAMOTO1, Junya Sakurai1, Masayoshi YAMAZAKI1, Kenji NAGATA1, Yoh-ichi MOTOTAKE2, Daisuke ABE3, Keisuke TORIGATA3 (1. NIMS, 2. The Inst of Statistical Mathematics, 3. IHI)
3:50 PM - 4:05 PM JST(6:50 AM - 7:05 AM UTC)

[112]Non-Isothermal Heat Treatments designed by Artificial Intelligence for Ni/Ni3Al two-phase alloys

*Vickey NANDAL1, Sae DIEB1, Dmitry　S. BULGAREVICH1, Toshio OSADA1, Toshiyuki KOYAMA2, Masahiko DEMURA1 (1. NIMS, 2. Nagoya University)
4:05 PM - 4:15 PM JST(7:05 AM - 7:15 AM UTC)

break

4:15 PM - 4:30 PM JST(7:15 AM - 7:30 AM UTC)

[113]Deep learning TEM image segmentation for automated microstructural analysis of FePt-C recording media

*Nikita Kulesh1, Anton Bolyachkin1, Ippei Suzuki1, Yukiko Takahashi1, Hossein Sepehri-Amin1 (1. NIMS)
4:30 PM - 4:45 PM JST(7:30 AM - 7:45 AM UTC)

[114]Evaluation of Tensile Strength based on Microscopic Imaging Data of Steel
by Mathematical Approaches

*Kazuto Akagi1, Ippei Obayashi2, Yasuaki Hiraoka1,3,4, Yasumasa Nishiura1,5 (1. Tohoku Univ., 2. Okayama Univ., 3. Kyoto Univ., 4. Riken, 5. Hokkaido Univ.)
4:45 PM - 5:00 PM JST(7:45 AM - 8:00 AM UTC)

[115]Estimation of material microstructure images by combining deep learning framework and phase transformation model

*Satoshi NOGUCHI1, Junya Inoue2 (1. Eng. Univ. Tokyo, 2. IIS Univ. Tokyo)
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