考虑吸气影响的层流翼型梯度优化设计

王一雯; 兰夏毓; 史亚云; 华俊; 白俊强; 周铸

doi:10.7527/S1000-6893.2022.27323

航空学报 >

2022 , Vol. 43 >Issue 11: 527323 - 527323

DOI: https://doi.org/10.7527/S1000-6893.2022.27323

论文

考虑吸气影响的层流翼型梯度优化设计

王一雯 ,
兰夏毓 ,
史亚云 ,
华俊 ,
白俊强 ,
周铸

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1. 西北工业大学无人系统技术研究院, 西安 710072;
2. 西北工业大学航空学院, 西安 710072;
3. 西安交通大学航天航空学院, 西安 710049;
4. 中国航空研究院, 北京 100012;
5. 中国空气动力研究与发展中心计算空气动力研究所, 绵阳 621000

收稿日期: 2022-04-26

修回日期: 2022-07-05

网络出版日期: 2022-07-14

基金资助

中国博士后科学基金（2021M692569）

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Gradient optimization design for laminar airfoil considering inspiration effect

WANG Yiwen ,
LAN Xiayu ,
SHI Yayun ,
HUA Jun ,
BAI Junqiang ,
ZHOU Zhu

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1. Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China;
2. School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China;
3. School of Aerospace, Xi'an Jiaotong University, Xi'an 710049, China;
4. Chinese Aeronautical Establishment, Beijing 100012, China;
5. Computational Aerodynamic Research Institute, China Aerodynamics Research and Development, Mianyang 621000, China

Received date: 2022-04-26

Revised date: 2022-07-05

Online published: 2022-07-14

Supported by

China Postdoctoral Science Foundation (2021M692569)

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摘要

针对层流翼优化设计问题，推导考虑吸气影响的层流-湍流转捩耦合伴随方程，并结合链式求导法则、自动微分技术及CK （Coupled Krylov）算法实现耦合伴随方程的高效求解，构建基于离散伴随理论的混合层流（HLF）翼梯度优化设计系统。转捩预测采用基于扰动放大因子模型（AFM）的e^N方法。层流飞行试验结果表明，基于AFM的转捩预测方法能够有效捕捉吸气控制影响下T-S （Tollmien-Schlichting）扰动波失稳诱导的转捩现象。利用构建的梯度优化系统开展层流翼型多点设计，并与非梯度优化方法的优化结果进行对比。自然层流设计结果对比显示，不同优化方法得到的设计结果呈现出较强的一致性。混合层流翼型多点设计结果显示，混合层流优化具有比自然层流优化更强的减阻能力。相比于自然层流优化翼型，混合层流优化翼型分别减阻6.1%、5.9%、33.3%、9.5%。本文构建的基于离散伴随的层流翼梯度优化方法能使混合层流机翼的气动性能得到大幅提升，可为未来混合层流机翼减阻设计提供方法支撑。

关键词： 自然层流; 混合层流; 离散伴随; 梯度优化; 气动设计

本文引用格式

王一雯 , 兰夏毓 , 史亚云 , 华俊 , 白俊强 , 周铸 . 考虑吸气影响的层流翼型梯度优化设计[J]. 航空学报, 2022 , 43(11) : 527323 -527323 . DOI: 10.7527/S1000-6893.2022.27323

Abstract

The coupled adjoint equation of laminar-turbulent transition considering the suction control effect is derived for the aerodynamic design of Hybrid Laminar Flow Control (HLFC) airfoils. The chain rule, automatic differentiation algorithm, and CK (Coupled Krylov) algorithms are used to accurately and efficiently solve the coupled adjoint equations. Finally, the gradient-based optimization framework, based on the discrete adjoint equations, for HLFC airfoil is constructed. The transition prediction model adopts the e^N method based on the Amplification Factor Model (AFM). The laminar flight test results show that the transition prediction method based on the AFM can effectively capture the transition phenomenon induced by T-S (Tollmien-Schlichting) waves instability under the influence of suction control. The multi-point design of the laminar airfoil is carried out using the gradient-based optimization framework, and comparison of the results with those of the gradient-free optimization. The comparison of natural laminar flow design results show that the gradient-free optimization has a deformation trend similar to the gradient-free optimization. The results of multi-point design of the hybrid laminar flow airfoil show that the hybrid laminar flow optimization has stronger drag reduction ability than the natural laminar flow optimization. Compared with that of the natural laminar airfoil, the total drag of the hybrid laminar airfoil is reduced by 6.1%, 5.9%, 33.3%, 9.5%, respectively. In conclusion, the gradient-based optimization method based on the discrete adjoint equations can effectively improve the aerodynamic performance of the HLFC airfoil, thereby providing methodological support for the future drag reduction design of HLFC.

Key words： natural laminar flow; hybrid laminar flow control; discrete adjoint equations; gradient-based optimization; aerodynamic design

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