Aerodynamic Modeling and Parameter Estimation from QAR Data of an Airplane Approaching a High-altitude Airport

Aerodynamic modeling and parameter estimation from quick accesses recorder (QAR) data is an important technical way to analyze the effects of highland weather conditions upon aerodynamic characteristics of airplane. It is also an essential content of flight accident analysis. The related techniques are developed in the present paper, including the geometric method for angle of attack and sideslip angle estimation, the extended Kalman filter associated with modified Bryson-Frazier smoother (EKF-MBF) method for aerodynamic coefficient identification, the radial basis function (RBF) neural network method for aerodynamic modeling, and the Delta method for stability/control derivative estimation. As an application example, the QAR data of a civil airplane approaching a high-altitude airport are processed and the aerodynamic coefficient and derivative estimates are obtained. The estimation results are reasonable, which shows that the developed techniques are feasible. The causes for the distribution of aerodynamic derivative estimates are analyzed. Accordingly, several measures to improve estimation accuracy are put forward.     

Assessment of Two Turbulence Models and Some Compressibility Corrections for Hypersonic Compression Comers by High-order Difference Schemes

The Spalart-Allmaras (S-A) turbulence model,the shear-stress transport (SST) turbulenee model and their compressibility corrections are revaluated for hypersonic compression corner flows by using high-...     

A Scalable Infrastructure for Online Performance Analysis on CFD Application

The fast-growing demand of computational fluid dynamics(CFD) application for computing resources stimulates the development of high performance computing(HPC) and meanwhile raises new requirements for the technology of parallel application performance monitor and analysis.In response to large-scale and long-time running for the application of CFD,online and scalable performance analysis technology is required to optimize the parallel programs as well as to improve their operational efficiency.As a result,this research implements a scalable infrastructure for online performance analysis on CFD application with homogeneous or heterogeneous system.The infrastructure is part of the parallel application performance monitor and analysis system(PAPMAS) and is composed of two modules which are scalable data transmission module and data storage module.The paper analyzes and elaborates this infrastructure in detail with respect to its design and implementation.Furthermore,some experiments are carried out to verify the rationality and high efficiency of this infrastructure that could be adopted to meet the practical needs.     

熵层对高超声速二维钝楔气动参数的影响

采用薄激波层理论和流管质量守恒相结合的方法,分析了高超声速二维钝楔边界层外缘熵的分布规律,研究了熵层对边界层外缘密度、马赫数以及壁面气动加热等气动参数的影响.结果表明:边界层外缘熵在倒圆-肩部区下降最为剧烈,熵层对气动参数的影响在高超声速下不可忽略,特别是使转捩区和湍流区的气动加热增加约53.6%.因此,将表面流态控制在层流模式对高超声速飞行器热防护具有重要意义.      

基于操纵面故障影响估计的安全飞行轨迹优化

操纵面故障将改变飞机受到的气动力和力矩,降低机动性能和控制能力,基于传统质点模型的航迹规划方法难以解决此类飞机安全飞行轨迹优化问题.因此,引入由故障引起的侧滑和侧力,估计故障后气动力系数,建立故障飞机模型;针对故障飞机控制和机动能力下降的问题,在原故障模型的基础上引入控制量变化率,构建轨迹优化对象模型,并将控制量变化率最小作为优化指标;采用高斯伪谱法优化计算安全飞行轨迹.仿真实验以副翼和方向舵故障为例进行设计,结果满足运动方程及各控制量、状态量约束,并能实现平稳飞行.     

Review on bio-inspired flight systems and bionic aerodynamics

Humans' initial desire for flight stems from the imitation of flying creatures in nature. The excellent flight performance of flying animals will inevitably become a source of inspiration for researchers. Bio-inspired flight systems have become one of the most exciting disruptive aviation technologies. This review is focused on the recent progresses in bio-inspired flight systems and bionic aerodynamics. First, the development path of Biomimetic Air Vehicles (BAVs) for bio-inspired flight systems and the latest mimetic progress are summarized. The advances of the flight principles of several natural creatures are then introduced, from the perspective of bionic aerodynamics. Finally, several new challenges of bionic aerodynamics are proposed for the autonomy and intelligent development trend of the bio-inspired smart aircraft. This review will provide an important insight in designing new biomimetic air vehicles.     

超临界层流翼型优化设计策略

针对超临界层流翼型设计问题,提出一种两轮优化策略。采用γ-Reθt转捩模型耦合剪切应力输运(SST)模式的湍流模型对翼型边界层转捩进行预测。翼型几何参数化建模采用形状分类函数转换(CST)方法,设计变量为描述翼型几何特征的参数。第1轮优化的目的是尽量提高层流区域的比例,气动分析模型为基于Kriging模型的代理模型,优化算法为遗传算法,通过优化获得满足约束要求的层流翼型。第2轮优化目的是对第1轮优化获得的翼型进行微调,进一步提高翼型的升阻比,气动分析直接采用CFD程序,优化算法采用基于梯度的优化算法。算例表明,应用本文提出的两轮优化策略,可将超临界翼型NASA SC(2)0412优化设计成超临界层流翼型,翼型的上下表面层流区比例分别达到了55.5%和47.0%,升阻比提高了38.1%。     

进口导流叶片对转子叶片颤振特性的影响

上游静子叶片的尾迹扰动是下游转子叶片发生强迫响应问题的主要原因,但通常认为不会对颤振特性产生影响。运用CFD技术求解非定常流场,用能量法对典型涡轮风扇NASA Rotor 67进行了气动弹性分析。结果表明:不加进口导流叶片时其叶片最有可能在第二阶模态、60°叶间振动相角的情况下发生颤振;加上IGV(进口导流叶片)后,IGV的尾迹会显著改变转子叶片的颤振特性,当转子叶片的最危险颤振模态频率接近IGV尾迹的扰动频率时,即使单独转子叶片十分稳定,但在尾迹的激励下颤振仍然可能发生;当该频率远离IGV尾迹扰动频率时,尾迹扰动同样会使转子叶片气动阻尼降低。该结果意味着尽管IGV的引入不会明显改变压气机性能,但有可能会对其颤振特性带来明显的负面影响,需要在涡轮机设计中予以考虑。     

基于神经网络模型的动态非线性气动力辨识方法

 在标准径向基函数（RBF）神经网络模型的基础上发展了带输出反馈的RBF神经网络。将计算流体力学(CFD)方法计算的时域气动载荷作为输入信号,建立跨声速非定常非线性气动力模型,并进一步运用CFD方法验证模型的精度。算例表明带输出反馈的RBF神经网络较标准RBF神经网络精度更高,能更准确描述跨声速激波大幅振荡时的非线性和非定常特性,并可推广用于多自由度运动的动态非线性气动力建模。用多级信号训练,预测简谐信号输入下的气动力算例表明带输出反馈的RBF神经网络能够预测不同振幅、不同频率的信号激励下的非线性气动力。     

飞行器气动-隐身综合性能评估的灰关联度分析模型

 采用结构化网格和求解Navier-Stokes方程的方法,进行了无人机和巡航导弹气动性能计算,并数值模拟了其气动流场,所得结果与工程实际现象吻合;分别建立了无人机和巡航导弹的曲面及面劈模型,根据GRECO-WM方法,计算了其表面全向雷达散射截面(RCS)值;基于灰色系统的灰关联度分析理论,提出了气动-隐身综合性能的量化评判模型,并对2种无人机和3种巡航导弹的综合性能进行了评价,得到了对工程设计具有参考价值的结论。