POD降阶算法中对基模态表达的改进

由一系列已知的相近流场解重新组合成一组正交分解(POD)的基模态。利用这些模态的线性组合构造绕一任意翼型的流场,使计算的未知量数目仅为所取相近解流场个数,而传统方法的未知量数目为网格单元数的4倍,因此极大地减少了未知量的数目,将其用于翼型优化,计算量会显著减少。给定的一系列相近流场解,是通过计算快照得到的,这些快照是形成正交模态的根本,直接影响近似计算的准确程度。本文提出了一种新的扰动方法,即通过扰动翼型的关键控制点反求翼型函数得到快照。通过几个已知的翼型解对子空间的投影比较可以看出,该方法的空间表达能力优于常用的加局部凸起的H icks-H enne函数的方法,而且近似计算的准确程度也更好。最后,探讨了正交分解的必要性,阐明利用POD降阶模型方法计算流场可以迅速收敛的内在原因。     

Effects of surface roughness on the aerodynamic performance of a high subsonic compressor airfoil at low Reynolds number

The aerodynamic performance of compressor airfoil is significantly affected by the surface roughness at low Reynolds number (Re). In the present study, numerical simulations have been conducted to investigate the impact of surface roughness on the profile loss of a high subsonic compressor airfoil at Re = 1.5 × 10⁵. Four roughness locations, covering 10%, 30%, 50% and 100% of the suction surface from the leading edge and seven roughness magnitudes (R_a) ranging from 52 to 525 μm were selected. Results showed that the surface roughness mainly determined the loss generation process by influencing the structure of the Laminar Separation Bubble (LSB) and the turbulence level near the wall. For all the roughness locations, the variation trend for the profile loss with the roughness magnitude was similar. In the transitionally rough region, the negative displacement effect of the LSB was suppressed with the increase of roughness magnitude, leading to a maximum decrease of 14.6%, 16.04%, 16.45% and 10.20% in the profile loss at R_a = 157 μm for the four roughness locations, respectively. However, with a further increase of the roughness magnitude in the fully rough region, the stronger turbulent dissipation enhanced the growth rate of the turbulent boundary layer and increased the profile loss instead. By comparison, the leading edge roughness played a dominant role in the boundary layer development and performance variation. To take fully advantage of the surface roughness reducing profile loss at low Re, the effects of roughness on suppressing LSB and inducing strong turbulent dissipation should be balanced effectively.     

A generative deep learning framework for airfoil flow field prediction with sparse data

Deep learning has been probed for the airfoil performance prediction in recent years.Compared with the expensive CFD simulations and wind tunnel experiments, deep learning models can be leveraged to somewhat mitigate such expenses with proper means. Nevertheless, effective training of the data-driven models in deep learning severely hinges on the data in diversity and quantity. In this paper, we present a novel data augmented Generative Adversarial Network(GAN), da GAN, for rapid and accurate fl...     

合成射流控制翼型分离的流动显示与PIV测量

合成射流是一种新型的流动控制技术,近年来引起广泛关注.本文首先利用热线风速仪测量了基于声激励的合成射流流动特性,确定了最佳输入信号频率;采用流动显示和PIV测试技术,研究了合成射流对二维翼型分离流动的控制效果.研究结果表明,合成射流可以有效地抑制二维翼型在大迎角下的分离流动;PIV测试结果进一步表明,合成射流开启后使翼型上表面分离区域减小,分离点后移.应用合成射流控制翼型流动分离,可以大大改善翼型在大迎角下的气动特性.     

涡桨飞机短舱/增升装置一体化气动设计研究

对涡桨飞机增升装置设计的特殊性进行了分析,指出了传统增升装置设计方法在涡桨飞机增升装置设计上存在的问题。详细描述了涡桨飞机短舱/增升装置一体化气动设计方法的流程,并对某涡桨飞机的多段翼型参数优化设计、短舱/三维增升装置一体化设计及风洞试验结果进行了简要介绍。相对于传统的增升装置设计方法,采用涡桨飞机短舱/增升装置一体化气动设计方法显著提高了涡桨飞机起飞、着陆构型的气动性能。     

基于XML语言和代理模型的翼型通用气动数据库技术

建立翼型气动数据库对翼型的选择和设计具有重要的意义。本文基于一种建立翼型通用气动数据库的思想,介绍该数据库的基本框架和基本功能;该数据库采用一种基于可扩展标记语言的通用数据格式进行存储,包含翼型几何特性数据、不同流动状态下力系数、物面压力分布等各种气动数据,并且还可提供灵活多样的数据处理功能;采用代理模型和变可信度模型技术,实现气动数据快速检索和插值功能。通过DU93-W-210翼型算例初步表明如何实现气动数据生成和快速插值,从而初步展示了所提出翼型气动数据库技术的可行性。     

A model of flow separation controlled by dielectric barrier discharge

Flow separation,as an aerodynamic phenomenon,occurs in specific conditions.The conditions are studied in a wind tunnel on different airfoils.The phenomenon can be delayed or suppressed by exerting an external momentum to the flow.Dielectric barrier discharge actuators arranged in a row of 8 and perpendicular to the flow direction can delay flow separation by exerting the momentum.In this study,a mathematical model is developed to predict a parameter,which is utilized to represent flow separation on an NACA0012 airfoil.The model is based on the neurofuzzy method applied to experimental datasets.The neuro model is trained in different flow conditions and the parameter is measured by pressure sensors.     

旋翼翼型动态失速模型参数识别及应用

为了拓展Leishman-Beddoes(L-B)动态失速模型的应用范围,以适应特定翼型的动态失速分析,在详细分析L-B动态失速模型特点的基础上,提出一种模型参数的识别方法。以SC-1095翼型为例,采用其静态升阻特性数据,对L-B动态失速模型中的参数进行了识别,并据此对该翼型的动态失速升阻特性进行了数值计算,计算结果与试验值吻合良好。     

间隙约束二元翼段系统分岔与多解共存现象分析

研究了分段刚度描述的间隙约束二元翼段气动弹性系统,取俯仰角最大幅值处为类Poincaré截面,数值计算得到了系统随飞行速度变化的分岔图,发现飞行速度在Ma=0.71~0.75属于跨临界颤振区,而在Ma=0.75~0.95发生极限环震荡.同时通过构造极限环震荡的四维Poincaré映射分析了极限环震荡的稳定性,结合稳定性和运动流形理论,得到极限环震荡的吸引域一般位于极限环内部并用数值方法进行了验证.且跨临界颤振速度区域中存在多种分岔形式以及多解共存现象,例如由双周期运动直接通向混沌、多周期运动与双周期运动共存现象,振动幅值也存在跳跃现象.     

超临界翼型设计中的多响应代理模型

为考虑超临界翼型设计中代理模型多响应之间的相关性,研究了基于多输出高斯过程回归的代理模型。通过实验数据验证了升力系数、阻力系数及力矩系数之间显著的相关性,建立了超临界翼型设计中的基于多输出高斯过程的多响应代理模型,并与kriging模型、BP和RBF两种人工神经网络模型进行了对比。结果表明,当超临界翼型设计中多输出端口之间存在显著的相关性时,多输出高斯过程相比kriging、BP和RBF能有效显著提高预测精度,并获得更加稳定的预测性能。