37th CFD Symposium

Presentation information

流体データの処理と活用

4.情報科学とCFD:情報科学の活用,情報科学とCFDの融合を目指す提案 » OS.4-2:流体データの処理と活用(可視化,プリ・ポスト処理,データ同化,機械学習(人工知能),データ分析法,設計探査,最適化など)

OS.4-2:流体データの処理と活用(可視化,プリ・ポスト処理,データ同化,機械学習(人工知能),データ分析法,設計探査,最適化など)

Sun. Dec 17, 2023 3:00 PM - 4:20 PM E室 (IB015)

Chair:Tomoaki Tatsukawa

3:00 PM - 3:20 PM

[3515-18-01] Weight-Sharing CNN Mode Decomposition Model for Unsteady Flows

*Yosuke Shimoda1, Naoya Fukushima2 (1. Graduate School of Science and Technology, Tokai Univ., 2. Department of Mechanical Engineering, School of Engineering, Tokai Univ.)

Keywords:Machine Learning, Convolutional Neural Network, Mode Decomposition, Unsteady Flow, Weight Sharing