基于神经网络模型的襟翼主动控制旋翼减振分析

基于径向基函数(Radial basis function,RBF)神经网络构建了一种带后缘襟翼主动控制(Active controlled flap,ACF)的旋翼振动载荷计算模型。采用正交试验方法确立RBF网络训练样本的输入,在CAMRAD II中计算前飞状态下与训练样本对应的旋翼桨毂六力素,并将主通过频率下的分量作为样本输出,对RBF网络进行离线训练。在此基础上采用多周控制器对被控模型进行振动载荷主动控制。随后以2桨叶4m直径ACF旋翼为例,构建了其桨毂减振分析方法,并对桨毂动载荷各分量的减振效果进行了分析。研究表明,采用正交样本训练的RBF网络能够精确映射襟翼偏角与桨毂振动载荷的非线性关系,施加多周控制后,桨毂垂向振动载荷降低接近50%,其他方向的振动载荷也有不同程度的降低。     

基于强度退化的齿轮可靠性计算模型研究及应用

为了研究强度退化对齿轮可靠性的影响,针对一般工作环境下具有多种失效模式的齿轮,通过引入条件概率,考虑零件失效相关性和材料性能退化因素,利用动态应力-强度干涉模型建立基于强度退化的齿轮可靠性的计算模型。以某型齿轮可靠度计算为例,其计算结果表明:在考虑材料强度退化时,齿轮的可靠度随工作时间的增加不断降低,验证了该计算模型的准确性。     

细长杆降低超声速客机气动噪声的数值分析

在超声速客机机头加装适当的细长杆可以降低飞行噪声。本文借助基于AUSM+格式的准三维数值模拟手段对7组13种细长杆方案做了分析比较,总结出了近场气体参数与远场气体参数之间的关系的规律。文章还从气体动力学理论和激波理论出发,对数值模拟结果作了解释,并揭示了细长杆降噪效果与细长杆外形的内在联系,以及近场、远场两者关系的经验公式。文章从各种方案中选取了降噪效果较好的细长杆方案做三维流场分析,并通过流固耦合计算对其结构强度做了校核,验证了方案的可行性。     

Beam-Park-Experiment-1/2000 with TIRA

A monostatic 24-h debris observation campaign (BPE-1/2000) has been prepared and conducted using FGAN's TIRA L-Band system. Based on experiences from previous Beam-park experiments a similar largely automated data processing is applied on an extended range window of 300–2000km. More than 1500 detections are encountered, 471 of them are verified as being real objects in Low-Earth-Orbit (LEO). PROOF's observation forecasting of catalogued objects is evaluated against the observed objects, and the difficulties obtaining radar cross-sections (RCSs) and object sizes from Beam-park experiments are discussed. Sidelobe detections are identified by using background information like two-line element (TLE) sets and/or catalogued RCSs.In comparison with previous experiments, the statistics show similarities confirming the concept of Beam-park experiments for space debris observations, despite the snapshot character of 24-h experiments. The comparison with MASTER/PROOF'99 and ORDEM2000 leads to a reasonable agreement between models and observations.     

Improved predictions of equatorial TEC for real time applications

It is important to use models developed specifically for the equatorial ionospheric estimation for real-time applications, particularly in Satellite Navigation. This work demonstrates a methodology for improved predictions of VTEC in real time using the model developed for the equatorial ionosphere by the authors. This work has been done using TEC data of the low solar activity period of 2005 obtained using dual frequency GPS receivers installed under the GAGAN project of ISRO. For the purpose, the model is first used in conjunction with Kriging technique. Improvement in accuracy is observed when compared with the estimations from the model alone using the measurements as true reference. Further improvement is obtained by Bayesian combination of these estimates with independent Neural Network based predictions. Statistical performance of improvement is provided. An improvement of ∼1 m in confidence level of estimation of VTEC is obtained.     

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.     

现代飞机俯仰跟踪时诱发振荡预测分析

根据飞机纵向ＰＩＯ的特点，提出了预测分析ＰＩＯ所用的人－机闭环系统数学模型，其中飞机采用等效系统数学模型，驾驶员操纵采用ＭｃＲｕｅｒ模型，参数按地面人－机模拟飞行跟踪试验确定，集中介绍了四种飞机纵向ＰＩＯ预测准则，Ｓｍｉｔｈ－Ｇｅｄｄｅｓ准则，修正带宽准则，增益，相位裕度准则，Ｎｅａｌ－Ｓｍｉｔｈ原则，并提供了相应的计算方法。     

AHP方法在系(部)工作评价中的应用

本文给出了系(部)工作评价的AHP模型，并对模型进行求解，说明了该模型的有效性。     

A salient edges detection algorithm of multi-sensor images and its rapid calculation based on PFCM kernel clustering

Multi-sensor image matching based on salient edges has broad prospect in applications, but it is difficult to extract salient edges of real multi-sensor images with noises fast and accurately by using common algorithms. According to the analysis of the features of salient edges, a novel salient edges detection algorithm and its rapid calculation are proposed based on possibility fuzzy C-means （PFCM） kernel clustering using two-dimensional vectors composed of the values of gray and texture. PFCM clustering can overcome the shortcomings that fuzzy C-means （FCM） cluster- ing is sensitive to noises and possibility C-means （PCM） clustering tends to find identical clusters. On this basis, a method is proposed to improve real-time performance by compressing data sets based on the idea of data reduction in the field of mathematical analysis. In addition, the idea that kernel-space is linearly separable is used to enhance robustness further. Experimental results show that this method extracts salient edges for real multi-sensor images with noises more accurately than the algorithm based on force fields and the FCM algorithm; and the proposed method is on average about 56 times faster than the PFCM algorithm in real time and has better robustness.     

民机与民航产业投入产出分析

运用价值型投入产出模型,基于投入产出表,分析我国民机产业在国民经济中的地位、与各部门之间的相关联系、对其他部门的依赖性以及对国民经济的带动,并进一步与民航产业进行对比分析。研究结果进一步印证民机产业在国民经济发展中的重要性,为进一步争取国家政策支持提供理论基础和依据。