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Inverse airfoil design method for generating varieties of smooth airfoils using conditional WGAN-gp

  • Published:2022-06 Issue:6 Volume:65 Page:
  • ISSN:1615-147X
  • Container-title:Structural and Multidisciplinary Optimization
  • language:en
  • Short-container-title:Struct Multidisc Optim

Author:

Yonekura KazuoORCID,Miyamoto Nozomu,Suzuki Katsuyuki

Funder

Japan Society for the Promotion of Science London

Publisher

Springer Science and Business Media LLC

Subject

Control and Optimization,Computer Graphics and Computer-Aided Design,Computer Science Applications,Control and Systems Engineering,Software

Reference38 articles.

1. Abbot I.. von Doenhoff AE, Stivers Jr L (1945) Summary of airfoil data. United States

2. Achour G, Sung WJ, Pinon-Fischer OJ, Mavris DN (2020) Development of a conditional generative adversarial network for airfoil shape optimization. p 2261

3. Arjovsky M, Bottou L (2017) Towards principled methods for training generative adversarial networks

4. Arjovsky M, Chintala S, Bottou L (2017) Wasserstein generative adversarial networks

5. Barrett TR, Bressloff NW, Keane AJ (2006) Airfoil shape design and optimization using multifidelity analysis and embedded inverse design. AIAA J 44(9):2051–2060

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1. A Short Note on Physics-Guided GAN to Learn Physical Models without Gradients;Algorithms;2024-06-26

2. Airfoil Inverse Design Based on Sequential CST-cGANs;2024 9th International Conference on Computer and Communication Systems (ICCCS);2024-04-19

3. Physics-guided training of GAN to improve accuracy in airfoil design synthesis;Computer Methods in Applied Mechanics and Engineering;2024-03

4. Parametric generative schemes with geometric constraints for encoding and synthesizing airfoils;Engineering Applications of Artificial Intelligence;2024-02

5. Quantification and reduction of uncertainty in aerodynamic performance of GAN-generated airfoil shapes using MC dropouts;Theoretical and Applied Mechanics Letters;2024-02
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