空气动力学学报2025，Vol.43Issue(12)：121-134,14.DOI:10.7638/kqdlxxb-2024.0139
基于柔性智能蒙皮的翼型流场预测和重建方法
Flow field prediction and reconstruction of aircraft based on flexible smart skin
摘要
Abstract
Real-time analysis and prediction of flow field characteristics are essential for flight safety and necessitating in-flight data acquisition,an almost impossible task for traditional techniques such as temperature/pressure-sensitive paints.Flexible smart skins demonstrate great promise for acquiring in-flight data.Nevertheless,the multi-physical data collected are usually sparsely in distribution and limited in quantity,making it difficult to accurately identify transition and stall locations.To overcome this limitation,we introduce a novel method for rapidly reconstructing high-resolution flow fields around aircraft wings from sparse data.Leveraging the flow fields computed by CFL3D,a dual-branch attention fusion model is developed based on an encoder-decoder network.This model facilitates rapid prediction of 2D flow fields for 52 types of NACA airfoils under 156 different freestream conditions,achieving an average relative error of 3.68%and providing a substantial amount of high-fidelity training data for the reconstruction process.Furthermore,using flow fields around the M6 airfoil generated by the rapid prediction model,a flow field reconstruction model is developed based on a shallow neural network.This model fulfills rapid reconstruction of high-resolution flow fields with a relative error of 2.73%.This work establishes a valuable data foundation for the in-flight application of smart skins,enhancing real-time monitoring capabilities and improving flight safety through accurate flow field reconstructions and insights.关键词
智能蒙皮/流场重建/流场预测/双分支编码器/特征融合/神经网络Key words
aircraft smart skin/flow field reconstruction/flow field prediction/double branch encoder/feature fusion/neural network分类
航空航天引用本文复制引用
来五星,赵浩哲,黄林,冀晶晶,黄永安..基于柔性智能蒙皮的翼型流场预测和重建方法[J].空气动力学学报,2025,43(12):121-134,14.基金项目
国家重点研发计划(2021YFB3200700) （2021YFB3200700）
国家自然科学基金(52175536,U23A20111) （52175536,U23A20111）
