高速自然层流翼型高效气动稳健优化设计方法

赵欢; 高正红; 夏露

doi:10.7527/S1000-6893.2020.24894

航空学报 >

2022 , Vol. 43 >Issue 1: 124894 - 124894

DOI: https://doi.org/10.7527/S1000-6893.2020.24894

流体力学与飞行力学

高速自然层流翼型高效气动稳健优化设计方法

赵欢 ,
高正红 ,
夏露

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1. 中山大学航空航天学院, 广州 510275;
2. 西北工业大学航空学院, 西安 710072

收稿日期: 2020-10-19

修回日期: 2021-12-27

网络出版日期: 2020-12-25

基金资助

国家自然科学基金（12102489）

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Efficient robust aerodynamic design optimization method for high-speed NLF airfoil

ZHAO Huan ,
GAO Zhenghong ,
XIA Lu

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1. School of Aeronautics and Astronautics, Sun Yat-sen University, Guangzhou 510275, China;
2. School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China

Received date: 2020-10-19

Revised date: 2021-12-27

Online published: 2020-12-25

Supported by

National Natural Science Foundation of China（12102489）

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摘要

先进高速高升力自然层流（NLF）翼型的设计已经成为提高新一代高空长航时（HALE）无人机（UAV）性能的重要手段。然而这类翼型表面极易出现分离泡和激波等，尤其对于马赫数、飞行攻角等状态波动气动特性非常敏感，这导致传统的层流翼型设计方法设计的外形在面向工程应用中出现稳健性差，难以被工程使用。气动稳健设计（RADO）方法虽然是一种有希望的解决途径，但它遭遇了巨大计算花费的难题。为了解决这些问题，通过对影响气动稳健优化设计效率的关键技术进行研究，发展了基于自适应前向-后向选择（AFBS）的稀疏多项式混沌重构方法，极大改善了不确定分析（UQ）和稳健优化效率。同时，也发展了考虑多参数不确定的高效气动稳健优化设计方法，有效解决了传统翼型设计方法难以满足高速高升力自然层流翼型设计要求兼顾高升力设计、自然层流设计以及超临界设计的难题。最后使用发展的方法成功设计了一类具有典型特点的跨空域稳健自然层流翼型。结果表明设计的翼型相对于经典的全球鹰无人机翼型气动性能全面提升，同时低阻范围更大，气动性能更加稳健，从而验证了稳健优化方法的有效性和相对于确定性设计的优势。

关键词： 高速自然层流翼型; 自然层流设计; 高空长航时无人机; 稳健设计; 不确定分析; 多项式混沌展开

本文引用格式

赵欢 , 高正红 , 夏露 . 高速自然层流翼型高效气动稳健优化设计方法[J]. 航空学报, 2022 , 43(1) : 124894 -124894 . DOI: 10.7527/S1000-6893.2020.24894

Abstract

The advanced high-speed and high-lift Natural-Laminar-Flow (NLF) airfoil has played an important role in improving the aerodynamic performance of the new generation of High-Altitude Long Endurance (HALE) Unmanned Air Vehicles (UAV). However, shock waves and separation bubbles are likely to occur on the surface of this kind of airfoil, which are very sensitive to the aerodynamic characteristics such as fluctuation of Mach number and angle of attack. The aerodynamic shape designed with the traditional method has low robustness, and is thus difficult to be used in engineering practice. Although the Robust Aerodynamic Design Optimization (RADO) method is a very promising solution, it encounters the difficulty of large computational cost. In this paper, we study the key technologies affecting the efficiency of RADO and develop a sparse PC reconstruction algorithm based on the Adaptive Forward-Backward Selection (AFBS) method, greatly improving the efficiency of Uncertainty Quantification (UQ) and RADO. We also develop an efficient RADO method considering multi-parameter uncertainty, which solves the difficulty of the traditional airfoil design method that requirements for high-lift design, NLF design, and supercritical design cannot be met simultaneously. Finally, we successfully apply the proposed methods to design a class of robust high-speed NLF airfoils with significant characteristics. Results demonstrate that compared with the classical Global Hawk UAV airfoil, the airfoils designed with the proposed methods can provide better aerodynamic performance, larger low-drag range and more robust performance, which validate the effectiveness of the proposed RADO method and advantages of the proposed method over the deterministic optimization method.

Key words： high-speed natural-laminar-flow airfoil; natural-laminar-flow design; high-altitude long-endurance unmanned air vehicle; robust design; uncertainty quantification; polynomial chaos expansion

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