Global aerodynamic design optimization based on data dimensionality reduction

In aerodynamic optimization, global optimization methods such as genetic algorithms are preferred in many cases because of their advantage on reaching global optimum. However, for complex problems in which large number of design variables are needed, the computational cost becomes prohibitive, and thus original global optimization strategies are required. To address this need, data dimensionality reduction method is combined with global optimization methods, thus forming a new global optimization system, aiming to improve the efficiency of conventional global optimization. The new optimization system involves applying Proper Orthogonal Decomposition (POD) in dimensionality reduction of design space while maintaining the generality of original design space. Besides, an acceleration approach for samples calculation in surrogate modeling is applied to reduce the computational time while providing sufficient accuracy. The optimizations of a transonic airfoil RAE2822 and the transonic wing ONERA M6 are performed to demonstrate the effectiveness of the proposed new optimization system. In both cases, we manage to reduce the number of design variables from 20 to 10 and from 42 to 20 respectively. The new design optimization system converges faster and it takes 1/3 of the total time of traditional optimization to converge to a better design, thus significantly reducing the overall optimization time and improving the efficiency of conventional global design optimization method.     

Aerodynamic optimization design for high pressure turbines based on the adjoint approach

A first study on the continuous adjoint formulation for aerodynamic optimization design of high pressure turbines based on S2surface governed by the Euler equations with source terms is presented.The objective function is defined as an integral function along the boundaries,and the adjoint equations and the boundary conditions are derived by introducing the adjoint variable vectors.The gradient expression of the objective function then includes only the terms related to physical shape variations.The numerical solution of the adjoint equation is conducted by a finitedifference method with the Jameson spatial scheme employing the first and the third order dissipative fluxes.A gradient-based aerodynamic optimization system is established by integrating the blade stagger angles,the stacking lines and the passage perturbation parameterization with the quasi-Newton method of Broyden–Fletcher–Goldfarb–Shanno(BFGS).The application of the continuous adjoint method is validated through a single stage high pressure turbine optimization case.The adiabatic efficiency increases from 0.8875 to 0.8931,whilst the mass flow rate and the pressure ratio remain almost unchanged.The optimization design is shown to reduce the passage vortex loss as well as the mixing loss due to the cooling air injection.     

风扇进口噪声预测模型的改进

针对Heidmann模型对风扇进口低频噪声(1k Hz)预测结果偏低的情况,通过引入风扇叶尖弦长雷诺数和相关几何参数改进了Heidmann模型中风扇进口宽频噪声的频谱修正函数,确定了其中频谱修正系数为0.085。对比改进模型和Heidmann模型的风扇进口噪声预测结果发现:在亚声速工况下,改进的模型很好地改善了风扇进口低频噪声的预测结果,改进幅值可以达到约45d B;而在超声速工况下,由于风扇进口产生的组合单音噪声成为风扇进口噪声的主要组成部分,除了在小于100Hz的频域内,改进的模型与Heidmann模型的预测结果差别不大。     

变形飞行器建模及控制方法研究综述

针对变形飞行器的发展现状、气动建模、动力学建模以及控制方法研究进行了综述。首先阐述了变形飞行器的定义及变形需求,再从四个方面梳理了变形飞行器的技术优势。针对不同的机翼变形方式,对飞行器各种变形技术的特点及发展现状进行了详细的分析与总结;将变形飞行器与固定外形飞行器的气动机理进行了对比分析,并对变形飞行器的动力学建模方法进行了梳理,总结了各种方法的特点;结合变形飞行器自身特性分析了飞行控制的特点及难点,并详细阐述了各类变形飞行器的控制研究进展。最后总结分析了变形飞行器的发展趋势：深化基础理论与技术研究,从材料、结构及控制等领域全方面朝着智能化方向发展,最终实现变形飞行器的工程化、自主化、智能化应用。     

Noise analysis of continuous GPS coordinate time series for CMONOC

The Crustal Movement Observation Network of China (CMONOC) is one of the major scientific infrastructures, mainly using Global Positioning System (GPS) measurements, to monitor crustal deformation in the Chinese mainland. In this paper, decade-long coordinate time series of 26 continuous GPS sites of CMONOC are analyzed for their noise content using maximum likelihood estimation (MLE). We study the noise properties of continuous GPS time series of CMONOC for the unfiltered, filtered solutions and also the common mode signals in terms of power law plus white noise model. In the spatial filtering, we remove for every time series a common mode error that was estimated from a modified stacking of position residuals from other sites within ∼1000 km of the selected site. We find that the common mode signal in our network has a combination of spatially correlated flicker noise and a common white noise with large spatial extent. We demonstrate that for the unfiltered solutions of CMONOC continuous GPS sites the main colored noise is a flicker process, with a mean spectral index of ∼1. For the filtered solutions, the main colored noise is a general power law process, indicating that a major number of the filtered regional solutions have a combination of noise sources or local effects. The velocity uncertainties from CMONOC continuous GPS coordinate time series may be underestimated by factors of 8–16 if a pure white noise model is assumed. In addition, using a white plus flicker noise model, the median values of velocity errors for the unfiltered solutions are 0.16 (north), 0.17 (east) and 0.58 (vertical) mm/yr, and the median values for the filtered solutions are 0.09 (north), 0.10 (east) and 0.40 (vertical) mm/yr.     

An artificial neural network approach for aerodynamic performance retention in airframe noise reduction design of a 3D swept wing model

With the progress of high-bypass turbofan and the innovation of silencing nacelle in engine noise reduction, airframe noise has now become another important sound source besides the engine noise. Thus, reducing airframe noise makes a great contribution to the overall noise reduction of a civil aircraft. However, reducing airframe noise often leads to aerodynamic perfor-mance loss in the meantime. In this case, an approach based on artificial neural network is intro-duced. An established database serves as a basis and the training sample of a back propagation (BP) artificial neural network, which uses confidence coefficient reasoning method for optimization later on. Then the most satisfactory configuration is selected for validating computations through the trained BP network. On the basis of the artificial neural network approach, an optimization pro-cess of slat cove filler (SCF) for high lift devices (HLD) on the Trap Wing is presented. Aerody-namic performance of both the baseline and optimized configurations is investigated through unsteady detached eddy simulations (DES), and a hybrid method, which combines unsteady DES method with acoustic analogy theory, is employed to validate the noise reduction effect. The numerical results indicate not merely a significant airframe noise reduction effect but also excel-lent aerodynamic performance retention simultaneously.     

红外探测器参数自动计量测试

介绍了我站的红外探测器参数（黑体响应率，噪声、黑体探测率）自动测试系统以及参数测试关键技术的解决分析了这些参数测量不确定度。     

箭体上的凸起物对火箭气动特性的影响

综合大量实验研究结果,本文给出了火箭箭体上的环形凸起物和纵向凸起物对火箭气动特性的影响。其中最主要的是改变滚转力矩的大小和方向。而这正是姿态控制系统设计的重要依据之一。因此,给出凸起物的设计原则,对火箭气动设计有实际意义。     

Assessment on critical technologies for conceptual design of blended-wing-body civil aircraft

Civil aviation faces great challenges because of its robust projected future growth and potential adverse environmental effects. The classical Tube-And-Wing(TAW) configuration following the Cayley's design principles has been optimized to the architecture's limit, which can hardly satisfy the further requirements on green aviation. By past decades' investigations the BlendedWing-Body(BWB) concept has emerged as a potential solution, which can simultaneously fulfill metrics of noise, emission and fuel burn. The purpose of the present work is to analyze the developments of critical technologies for BWB conceptual design from a historical perspective of technology progress. It was found that the high aerodynamic efficiency of BWB aircraft can be well scaled by the mean aerodynamic chord and wetted aspect ratio, and should be realized with the trade-offs among stability and control and low-speed performance. The structure concepts of non-cylinder pressurized cabin are of high risks on weight prediction and weight penalty. A static stability criterion is recommended and further clear and adequate criteria are required by the evaluations of flying and handling qualities. The difficulties of propulsion and airframe integration are analyzed. The energy to revenue work ratios of well-developed BWB configurations are compared,which are 31.5% and 40% better than that of TAW, using state-of-art engine technology and future engine technology, respectively. Finally, further study aspects are advocated.     

Application of a PCA-DBN-based surrogate model to robust aerodynamic design optimization

An efficient method employing a Principal Component Analysis (PCA)-Deep Belief Network (DBN)-based surrogate model is developed for robust aerodynamic design optimization in this study. In order to reduce the number of design variables for aerodynamic optimizations, the PCA technique is implemented to the geometric parameters obtained by parameterization method. For the purpose of predicting aerodynamic parameters, the DBN model is established with the reduced design variables as input and the aerodynamic parameters as output, and it is trained using the k-step contrastive divergence algorithm. The established PCA-DBN-based surrogate model is validated through predicting lift-to-drag ratios of a set of airfoils, and the results indicate that the PCA-DBN-based surrogate model is reliable and obtains more accurate predictions than three other surrogate models. Then the efficient optimization method is established by embedding the PCA-DBN-based surrogate model into an improved Particle Swarm Optimization (PSO) framework, and applied to the robust aerodynamic design optimizations of Natural Laminar Flow (NLF) airfoil and transonic wing. The optimization results indicate that the PCA-DBN-based surrogate model works very well as a prediction model in the robust optimization processes of both NLF airfoil and transonic wing. By employing the PCA-DBN-based surrogate model, the developed efficient method improves the optimization efficiency obviously.