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Yonekura Kazuo  米倉 一男

Researcher Number 40890025
Other IDs
  • ORCIDhttps://orcid.org/0000-0002-1955-069X
Affiliation (based on the past Project Information) *help 2021 – 2024: 東京大学, 大学院工学系研究科(工学部), 講師
Review Section/Research Field
Principal Investigator
Basic Section 18030:Design engineering-related
Keywords
Principal Investigator
強化学習 / 生成モデル / 設計工学 / 機械学習 / データ駆動型設計 / 最適設計 / 深層強化学習 / 深層生成モデル / 機械設計
  • Research Projects

    (2 results)
  • Research Products

    (35 results)
  •  Improving data-driven design using physical model-based machine learningPrincipal Investigator

    • Principal Investigator
      米倉 一男
    • Project Period (FY)
      2023 – 2025
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 18030:Design engineering-related
    • Research Institution
      The University of Tokyo
  •  Data driven design utilizing machine learning techniquesPrincipal Investigator

    • Principal Investigator
      Yonekura Kazuo
    • Project Period (FY)
      2021 – 2022
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 18030:Design engineering-related
    • Research Institution
      The University of Tokyo

All 2025 2024 2023 2022 2021

All Journal Article Presentation Patent

  • [Journal Article] Quantification and reduction of uncertainty in aerodynamic performance of GAN-generated airfoil shapes using MC dropouts2025

    • Author(s)
      Yonekura Kazuo、Aoki Ryuto、Suzuki Katsuyuki
    • Journal Title

      Theoretical and Applied Mechanics Letters

      Volume: 15 Issue: 4 Pages: 100504-100504

    • DOI

      10.1016/j.taml.2024.100504

    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Journal Article] Multimaterial Topology Optimization of Unsteady Heat Conduction Problems Based on Discrete Material Optimization2025

    • Author(s)
      Ogawa Shun、Yonekura Kazuo、Suzuki Katsuyuki
    • Journal Title

      International Journal of Heat and Mass Transfer

      Volume: 225 Pages: 125353-125353

    • DOI

      10.2139/ssrn.4635977

    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Journal Article] Physics-guided training of GAN to improve accuracy in airfoil design synthesis2024

    • Author(s)
      Wada Kazunari、Suzuki Katsuyuki、Yonekura Kazuo
    • Journal Title

      Computer Methods in Applied Mechanics and Engineering

      Volume: 421 Pages: 116746-116746

    • DOI

      10.1016/j.cma.2024.116746

    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Journal Article] Applications of machine learning in surge prediction for vehicle turbochargers2024

    • Author(s)
      Saito Hiroki、Kanzaki Dai、Yonekura Kazuo
    • Journal Title

      Machine Learning with Applications

      Volume: 16 Pages: 100560-100560

    • DOI

      10.1016/j.mlwa.2024.100560

    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Journal Article] A Short Note on Physics-Guided GAN to Learn Physical Models without Gradients2024

    • Author(s)
      Yonekura Kazuo
    • Journal Title

      Algorithms

      Volume: 17 Issue: 7 Pages: 279-279

    • DOI

      10.3390/a17070279

    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Journal Article] Hypervolume-Based Multi-Objective Optimization Method Applying Deep Reinforcement Learning to the Optimization of Turbine Blade Shape2024

    • Author(s)
      Yonekura Kazuo、Yamada Ryusei、Ogawa Shun、Suzuki Katsuyuki
    • Journal Title

      AI

      Volume: 5 Issue: 4 Pages: 1731-1742

    • DOI

      10.3390/ai5040085

    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Journal Article] Preliminary Study of Airfoil Design Synthesis Using a Conditional Diffusion Model and Smoothing Method2024

    • Author(s)
      Yonekura Kazuo、Oshima Yuta、Aichi Masaatsu
    • Journal Title

      Computation

      Volume: 12 Issue: 11 Pages: 227-227

    • DOI

      10.3390/computation12110227

    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Journal Article] Airfoil Shape Generation and Feature Extraction Using the Conditional VAE-WGAN-gp2024

    • Author(s)
      Yonekura Kazuo、Tomori Yuki、Suzuki Katsuyuki
    • Journal Title

      AI

      Volume: 5 Issue: 4 Pages: 2092-2103

    • DOI

      10.3390/ai5040102

    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Journal Article] Improved Monte Carlo tree search formulation with multiple root nodes for discrete sizing optimization of truss structures2024

    • Author(s)
      Ko Fu-Yao、Suzuki Katsuyuki、Yonekura Kazuo
    • Journal Title

      Engineering Optimization

      Volume: online Issue: 10 Pages: 1-29

    • DOI

      10.1080/0305215x.2024.2413962

    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Journal Article] Turbine blade optimization considering smoothness of the Mach number using deep reinforcement learning2023

    • Author(s)
      Yonekura Kazuo、Hattori Hitoshi、Shikada Shohei、Maruyama Kohei
    • Journal Title

      Information Sciences

      Volume: 642 Pages: 119066-119066

    • DOI

      10.1016/j.ins.2023.119066

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Journal Article] Multi-material topology optimization considering material cost and displacement constraints2023

    • Author(s)
      OGAWA Shun、YONEKURA Kazuo、SUZUKI Katsuyuki
    • Journal Title

      Transactions of the JSME (in Japanese)

      Volume: 89 Issue: 926 Pages: 23-00180-23-00180

    • DOI

      10.1299/transjsme.23-00180

    • ISSN
      2187-9761
    • Language
      Japanese
    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Journal Article] Super-resolving 2D stress tensor field conserving equilibrium constraints using physics-informed U-Net2023

    • Author(s)
      Yonekura Kazuo、Maruoka Kento、Tyou Kyoku、Suzuki Katsuyuki
    • Journal Title

      Finite Elements in Analysis and Design

      Volume: 213 Pages: 103852-103852

    • DOI

      10.1016/j.finel.2022.103852

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-21K14064
  • [Journal Article] Inverse airfoil design method for generating varieties of smooth airfoils using conditional WGAN-gp2022

    • Author(s)
      Yonekura Kazuo、Miyamoto Nozomu、Suzuki Katsuyuki
    • Journal Title

      Structural and Multidisciplinary Optimization

      Volume: 65 Issue: 6 Pages: 173-173

    • DOI

      10.1007/s00158-022-03253-6

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-21K14064
  • [Journal Article] Generating various airfoils with required lift coefficients by combining NACA and Joukowski airfoils using conditional variational autoencoders2022

    • Author(s)
      Yonekura Kazuo、Wada Kazunari、Suzuki Katsuyuki
    • Journal Title

      Engineering Applications of Artificial Intelligence

      Volume: 108 Pages: 104560-104560

    • DOI

      10.1016/j.engappai.2021.104560

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-21K14064
  • [Journal Article] Quantitative analysis of latent space in airfoil shape generation using variational autoencoders2021

    • Author(s)
      YONEKURA Kazuo
    • Journal Title

      Transactions of the JSME (in Japanese)

      Volume: 87 Issue: 903 Pages: 21-00212-21-00212

    • DOI

      10.1299/transjsme.21-00212

    • NAID

      130008120025

    • ISSN
      2187-9761
    • Language
      Japanese
    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-21K14064
  • [Patent] 学習方法、情報処理システム、プログラム及び学習モデル2022

    • Inventor(s)
      米倉一男、和田一成
    • Industrial Property Rights Holder
      東京大学
    • Industrial Property Rights Type
      特許
    • Filing Date
      2022
    • Data Source
      KAKENHI-PROJECT-21K14064
  • [Presentation] Understanding agent actions utilizing actor-critic algorithm in deep reinforcement learning2024

    • Author(s)
      R. Kai, K. Yonekura
    • Organizer
      The16th World Congress on Computational Mechanics and 4th Pan American Congress on Computational Mechanics
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Presentation] Automotive motor rotor design synthesis using conditional Wasserstein Generative Adversarial Networks with gradient penalty and distortion penalty2024

    • Author(s)
      N. Kato, K. Suzuki, Y. Kondo, K. Suzuki, K. Yonekura
    • Organizer
      9th European Congress on Computational Methods in Applied Sciences and Engineering
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Presentation] mproving Accuracy in Shape Generation of Motors Using Generative Models2024

    • Author(s)
      M. Tamura, K. Suzuki, Y. Kondo, K. Suzuki, K. Yonekura
    • Organizer
      9th European Congress on Computational Methods in Applied Sciences and Engineering
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Presentation] 最適化手法を用いた海洋生態系モデルパラメータの同定2024

    • Author(s)
      鈴木 彩, 小林 高士, 久田 正樹, 米倉一男
    • Organizer
      日本応用数理学会年会
    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Presentation] Physics guided training of GAN model to improve accuracy in a design synthesis2024

    • Author(s)
      K. Yonekura
    • Organizer
      The16th World Congress on Computational Mechanics and 4th Pan American Congress on Computational Mechanics
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Presentation] Inverse airfoil design considering uncertainties of GAN models2024

    • Author(s)
      K. Yonekura, R. Aoki, K. Suzuki
    • Organizer
      9th European Congress on Computational Methods in Applied Sciences and Engineering
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Presentation] 多目的強化学習を用いた設計最適化2024

    • Author(s)
      米倉一男, 山田 龍征, 小川 竣, 鈴木 克幸
    • Organizer
      設計工学システム部門講演会
    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Presentation] Ship hull form design synthesis using generative adversarial network2024

    • Author(s)
      K. Yonekura, X., Qi, K. Suzuki
    • Organizer
      Asian Congress of Structural and Multidisciplinary Optimization 2024
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Presentation] Generating Solutions for Laplace Equations by using Physics-Guided Generative Adversarial Networks2024

    • Author(s)
      Z. Gi, K. Suzuki, K. Yonekura
    • Organizer
      Asian Congress of Structural and Multidisciplinary Optimization 2024
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Presentation] Data driven design method for inverse problems and optimization problems2024

    • Author(s)
      K. Yonekura
    • Organizer
      International Workshops on Advances in Computational Mechanics
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Presentation] Physics informed GAN for generating 2D airfoil shapes with required lift coefficients2023

    • Author(s)
      K. Yonekura, Kazunari Wada, Katsuyuki Suzuki
    • Organizer
      The 15th World Congress of Structural and Multidisciplinary Optimization (WCSMO15)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-23K13239
  • [Presentation] Physics Guided cWGAN-gp による翼型生成の高精度化2022

    • Author(s)
      和田 一成, 鈴木 克幸, 米倉 一男
    • Organizer
      日本機械学会 最適化シンポジウム2022
    • Data Source
      KAKENHI-PROJECT-21K14064
  • [Presentation] Physics Guided Deep Learning Method to Surrogat Flow Simulation2022

    • Author(s)
      H. Saito, K. Yonekura
    • Organizer
      The 15th World Congress on Computational Mechanics (WCCM-XV) & the 8th Asian Pacific Congress on Computational Mechanics (APCOM-VIII)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-21K14064
  • [Presentation] Airfoil generation using conditional Wasserstein VAEGAN with gradient penalty2022

    • Author(s)
      Y. Tomori, K. Yonekura, K. Suzuki
    • Organizer
      Asian Congress of Structural and Multidisciplinary Optimization 2022
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-21K14064
  • [Presentation] Airfoil generation using conditional Wasserstein VAEGAN with gradient penalty2022

    • Author(s)
      YONEKURA Kazuo
    • Organizer
      Asian Congress of Structural and Multidisciplinary Optimization 2022
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-21K14064
  • [Presentation] 形状設計タスクにおける深層生成モデルと Physics Guided GAN2022

    • Author(s)
      米倉一男
    • Organizer
      日本機械学会 最適化シンポジウム2022
    • Data Source
      KAKENHI-PROJECT-21K14064
  • [Presentation] 要求仕様を満たす船型プロトタイプ生成のための深層学習モデル2022

    • Author(s)
      大森晃太朗, 米倉一男, 鈴木克幸
    • Organizer
      第27回計算工学会
    • Data Source
      KAKENHI-PROJECT-21K14064
  • [Presentation] Generating airfoil with specific lift coefficients using conditional GAN and conditional VAE2021

    • Author(s)
      YONEKURA Kazuo
    • Organizer
      The 14th World Congress of Structural and Multidisciplinary Optimization
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-21K14064
  • [Presentation] 変分オートエンコーダを用いた形状のデータマイニングと形状創出2021

    • Author(s)
      米倉一男
    • Organizer
      日本機械学会 設計工学システム部門講演会
    • Data Source
      KAKENHI-PROJECT-21K14064

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