Oral Session

A. New Materials Methodology for Next-Generation » [A-2] Materials Integration: Prediction and Design for Structural Materials through Data Science

[A2-O7] Slot 07

2021年12月15日(水) 14:30 〜 18:00 Room P (G317)

Chair: Masahiko Demura (National Institute for Materials Science (NIMS)), Toshihiro Ashino (Toyo University)

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14:30 〜 14:55

[A2-O7-01 (Symposium Invited)] Computer vision for analysis of microstructure evolution

*Irina Roslyakova¹, Uchechukwu Nwachukwu¹, Abdulmonem Obaied¹, Oliver Martin Horst², Muhammad Adil Ali¹, Ingo Steinbach¹ (1. ICAMS, Ruhr-University Bochum (Germany), 2. Institut für Werkstoffe, Ruhr-University Bochum (Germany))

14:55 〜 15:10

[A2-O7-02] Implementation of Ontology-Based Data Integration for Materials Data

*Toshihiro Ashino¹, Nobutaka Nishikawa², Takuya Kadohira³, Masahiko Demura³ (1. Toyo Univ. (Japan), 2. Mizuho Res. & Tech. Ltd. (Japan), 3. National Inst. for Materials Sci. (Japan))

15:10 〜 15:25

[A2-O7-03] Machine Learning Prediction Model of Continuous Cooling Transformation Diagram for steel HAZ

*Satoshi Minamoto¹, Susumu Tsukamoto¹, Tadashi Kasuya², Makoto Watanabe³, Masahiko Demura¹ (1. Research and Services Division of Materials Data and Integrated System (MaDIS), National Institute for Materials Science (NIMS) (Japan), 2. Department of Materials Engineering, The University of Tokyo (Japan), 3. Research Center for Structural Materials (RCSM), National Institute for Materials Science (NIMS) (Japan))

15:25 〜 15:40

[A2-O7-04] Unsupervised Steel Microstructure Segmentation Using Data Mining Methods

*Hoheok Kim¹, Junya Inoue^1,2, Yuuki Arisato² (1. Institute of industrial science, The University of Tokyo (Japan), 2. Department of materials engineering, The University of Tokyo (Japan))

15:40 〜 15:55

[A2-O7-05] Characterization and generation of stochastic heterogenous microstructures for inverse material design by VQVAE and PixelCNN

*Satoshi Noguchi¹, Junya Inoue¹ (1. The Univ. of Tokyo (Japan))

15:55 〜 16:10

[A2-O7-06] A simple framework for texture analysis of steel microstructure images and its application to correlation analysis with steel properties

*Nanami Takagi^1,2, Takashi Michikawa¹, Norio Yamashita¹, Shin Yoshizawa¹, Hiroshi Takemura^1,2, Takayuki Shiraiwa³, Manabu Enoki³, Kazuhiko Yamazaki⁴, Hideo Yokota¹ (1. RIKEN Center for Advanced Photonics (Japan), 2. Tokyo Univ. of Sci. (Japan), 3. The Univ. of Tokyo (Japan), 4. JFE Steel Corp. (Japan))

16:10 〜 16:25

[A2-O7-07] 3D Shape Evaluation of Martensite-Austenite Constituents in High Tensile Steel using a 3D Internal Structure Microscope

*Ryoma Suzumura^1,2, Norio Yamashita¹, Takashi Michikawa¹, Shinya Morita^1,2, Masahiro Inomoto³, Yoshitomi Okazaki³, Hideo Yokota¹ (1. RIKEN Center for Advanced Photonics, RIKEN (Japan), 2. Tokyo Denki University (Japan), 3. Materials Research Laboratory, Technical Development Group, KOBE STEEL, Ltd. (Japan))

Break (16:25 〜 16:35)

16:35 〜 17:00

[A2-O7-08 (Symposium Invited)] Intelligent-data-guided process design for fatigue-resistant bainitic steel: iBain

*Steinbach Ingo¹, Ulrich Krupp², Chris Eberl³ (1. Ruhr-University Bochum (Germany), 2. RWTH-Aachen (Germany), 3. IEW Freiburg (Germany))

17:00 〜 17:15

[A2-O7-09] AI for material formulations

Victor Viterbo¹, Oliver Schilter¹, Theophile Gaudin¹, Leonid Kahle¹, *Federico Zipoli¹, Teodoro Laino¹ (1. IBM Research Europe (Switzerland))

17:15 〜 17:30

[A2-O7-10] Using Uncertainty Quantification Of First-Principles-Only CALPHAD Phase Diagrams To Guide Sequential Learning Of Unknown Phases And Energy Contributions

*Theresa Davey¹, Ying Chen¹ (1. Tohoku Univ. (Japan))

17:30 〜 17:45

[A2-O7-11] Uncertainty and accuracy of neural-network interatomic potentials

Leonid Kahle¹, *Federico Zipoli¹, Teodoro Laino¹ (1. IBM Research Zurich (Switzerland))

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