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Efficient aerodynamic shape optimization by using unsupervised manifold learning to filter geometric features
Engineering Applications of Computational Fluid Mechanics ( IF 5.9 ) Pub Date : 2024-07-31 , DOI: 10.1080/19942060.2024.2384465 Long Ma 1 , Xiao-Jing Wu 1, 2 , Wei-Wei Zhang 3, 4, 5
Engineering Applications of Computational Fluid Mechanics ( IF 5.9 ) Pub Date : 2024-07-31 , DOI: 10.1080/19942060.2024.2384465 Long Ma 1 , Xiao-Jing Wu 1, 2 , Wei-Wei Zhang 3, 4, 5
Affiliation
Many aerodynamic shape optimization methods often focus on utilizing the end-to-end relationship between design variables and aerodynamic performance to find the optimal design, while overlooking t...
中文翻译：
通过使用无监督流形学习来过滤几何特征，实现高效的空气动力学形状优化
许多气动形状优化方法通常侧重于利用设计变量和气动性能之间的端到端关系来寻找最佳设计，而忽略了...
更新日期：2024-08-03
中文翻译：
通过使用无监督流形学习来过滤几何特征，实现高效的空气动力学形状优化
许多气动形状优化方法通常侧重于利用设计变量和气动性能之间的端到端关系来寻找最佳设计，而忽略了...
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