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Summary & Details

Aerodynamic Shape Optimization by Combination of VAE and PINN Hybrid SDF and Point-Cloud for Shape Representation

VAEとPINNによる空力形状最適化 SDFと点群を併用した方法

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Format: PDF

Price: Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880

Publication code: 20266384

Paper/Info type: Proceedings (Autumn)

No.171-26

Pages: 1-2(Total 2 p)

Date of publication: Oct 2026

Publisher: JSAE

Language: Japanese

Event: 2026 JSAE Annual Congress (Autumn)

Detailed Information

Author(J)	1) 疋田夏帆, 2) 白鳥英
Author(E)	1) Kaho Hikita, 2) Suguru Shiratori
Affiliation(J)	1) 東京都市大学大学院, 2) 東京都市大学
Affiliation(E)	1) Tokyo City University, 2) Tokyo City University
Abstract(J)	効力係数を小さくする車体形状最適化において，メッシュ再生成を伴う従来手法は計算コストが高い．筆者らは生成AIとしてVAEを用いて形状を潜在変数としてパラメータ化し，PINNを用いて空力計算する最適化法を研究している．本報告では形状表現としてSDFと点群を併用した方法を提案し，2次元翼型に対する検証結果を報告する． Translation
Abstract(E)	In aerodynamic shape optimization, conventional methods, which require re-meshing, take huge computational cost. Our research group has proposed mesh-free approach, where the shape is parameterized by latent space based on VAE and aerodynamic drag is evaluated by PINNs. In this study, we propose a new shape representation using hybrid of SDF and point-clouds. Validations are conducted for two-dimensional airfoils.

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