Efficient aerodynamic shape optimization by using unsupervised manifold learning to filter geometric features

IF 5.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Engineering Applications of Computational Fluid Mechanics Pub Date : 2024-07-31 DOI:10.1080/19942060.2024.2384465

Long Ma, Xiao-Jing Wu, Wei-Wei Zhang

引用次数: 0

Abstract

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...

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利用无监督流形学习过滤几何特征，高效优化空气动力学形状

许多气动外形优化方法通常侧重于利用设计变量与气动性能之间的端到端关系来找到最佳设计，而忽略了气动性能与设计变量之间的端到端关系。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Engineering Applications of Computational Fluid Mechanics ENGINEERING, MULTIDISCIPLINARY-ENGINEERING, MECHANICAL

CiteScore

10.60

自引率

14.80%

发文量

109

审稿时长

3.4 months

期刊介绍： The aim of Engineering Applications of Computational Fluid Mechanics is a continuous and timely dissemination of innovative, practical and industrial applications of computational techniques to solve the whole range of hitherto intractable fluid mechanics problems. The journal is a truly interdisciplinary forum and publishes original contributions on the latest advances in numerical methods in fluid mechanics and their applications to various engineering fields including aeronautic, civil, environmental, hydraulic and mechanical. The journal has a distinctive and balanced international contribution, with emphasis on papers addressing practical problem-solving by means of robust numerical techniques to generate precise flow prediction and optimum design, and those fostering the thorough understanding of the physics of fluid motion. It is an open access journal.