太原理工大学学报2024，Vol.55Issue(4)：660-669,10.DOI:10.16355/j.tyut.1007-9432.20230070
基于深度学习和MOEA/D的高升力翼型气动优化设计
Research on Aerodynamic Optimization Design of High Lift Airfoil Based on Deep Learning and MOEA/D
摘要
Abstract
[Purposes]Aiming at the performance conflict between optimization parameters in prior optimization method,a hybrid optimization model based on MOEA/D is proposed,which integrates CNN and genetic algorithm into MOEA/D framework to balance the correlation and complexity between various objective functions.[Methods]First,the deep learning method is used as a supplement to the conventional fluid mechanics analysis method to establish a highly re-liable CNN response prediction model for airfoil aerodynamic characteristics,which can be used to quickly evaluate the aerodynamic parameters of airfoil.Then,the response model and genetic operator are interpolated into the MOEA/D framework to construct a multi-objective hybrid opti-mization model based on MOEA/D.And the lift drag ratio and moment coefficient of a NACA high lift airfoil under cruise condition are taken as the optimization objectives for testing.Finally,through the analysis of aerodynamic performance and flow field structure of the airfoil on the Pa-reto front,the distribution law of different airfoil configurations on the front is studied,which further guides the designer to explore the potential basic airfoil in the airfoil selection.关键词
气动优化/混合方法/MOEA/D/CNN/CFDKey words
aerodynamic optimization/mixed method/MOEA/D/CNN/CFD分类
航空航天引用本文复制引用
沈永强,王菡,向纪鑫,李志强..基于深度学习和MOEA/D的高升力翼型气动优化设计[J].太原理工大学学报,2024,55(4):660-669,10.基金项目
国家自然科学基金青年项目资助项目(12102290) （12102290）
山西省关键核心技术和共性技术研发攻关专项(2020XXX017) （2020XXX017）
