Drag Reducing and Increasing Mechanism on Triangular Riblet Surface

Drag reducing and increasing mechanism on riblet surface has been studied through computational fluid dynamics(CFD).Drag reduction is achieved through the optimization of riblet geometry which would affect flow structure inside riblet grooves.Force and flow structure on riblet surface are analyzed and compared with those of smooth surface based on the k-εturbulence model.Drag reducing and increasing mechanism is proved to be related to microvortexes induced inside riblets which lead to Reynolds shear stress reduction significantly and is considered to be the dominant factor resulting in wall friction reduction.Simulation results also show that the pressure drag generating from the deviation of static pressure on the front and rear ends of riblets occurs and grows exponentially with Mach number,which can cause drag increasing.Furthermore,near-wall vortical structures,Reynolds shear stress and static pressure on riblet surfaces are also analyzed in detail.     

Application of small-size antennas for estimation of angles of arrival of HF signals scattered by ionospheric irregularities

A modification of the Doppler Interferometry Technique is suggested to enable estimating angles of arrival of comparatively broadband HF signals scattered by random irregularities of the ionospheric plasma with the use of small-size weakly directional antennas. The technique is based on the measurements of cross-spectra phases of the probe radiation recorded at least in three spatially separated points. The developed algorithm has been used to investigate the angular and frequency-time characteristics of HF signals propagating at frequencies above the maximum usable one (MUF) for the direct radio path Moscow-Kharkiv. The received signal spectra show presence of three families of spatial components attributed, respectively, to scattering by plasma irregularities near the middle point of the radio path, ground backscatter signals and scattering of the sounding signals by the intense plasma turbulence associated with auroral activations. It has been shown that the regions responsible for the formation of the third family components are located well inside the auroral oval. The drift velocity and direction of the auroral ionosphere plasma have been determined. The obtained estimates are consistent with the classical conception of the ionospheric plasma convection at high latitudes and do not contradict the results of investigations of the auroral ionosphere dynamics using the SuperDARN network.     

冯子明 航空信息化专家

我国航空企业数字化制造已经有哪些成就,为我国航空企业带来怎样的影响?冯子明:目前国内飞机数字化设计制造水平在不断地提高。数字化的软硬件环境已初具规模,飞机设计已由三维几何模型设计向全信息三维模型设计方向发展     

基于自回归与最小均方理论的振动环境下 光纤陀螺仪滤波方法

针对振动应力下光纤陀螺产生测量误差增大的问题,从振动对光纤环的影响机理出发,分析了振动应力下光纤陀螺干涉信号的表现形式,提出了基于自回归最小均方滤波理论的光纤陀螺滤波方法,将AR模型的平稳性和最小均方根滤波的自适应性相结合,提取平稳数据的特性参数,对高频信号进行滤波,降低非互易相移产生陀螺角速度误差值的干扰.试验表明,该方法简单可行,有效地降低了振动应力下光纤陀螺输出信息的噪声,抑制了由振动引起的陀螺漂移.     

基于火箭橇的无人机碰撞民用飞机试验技术研究

无人机碰撞民用飞机关键部位损伤程度的研究是民航领域关注的新型热点问题。本文首次提出采用 火箭橇试验评估无人机碰撞民用飞机的安全性。通过对碰撞速度、碰撞位置、无人机姿态、参数测量等进行研 究,设计碰撞技术方案,论述火箭橇的设计、弹道控制设计、强度校核和测试方案,并进行试验验证和仿真计算。 结果表明:本文设计的火箭橇碰撞试验方案是可行的,实现了单一弹道上的连续多点碰撞及多视角、全覆盖、高 稳定的全过程记录;可为后续开展同类碰撞试验提供必要的技术参考,所开展的多发次碰撞试验也为无人机碰 撞民用飞机的安全性评估提供了有效的试验数据。     

基于硅基MEMS工艺的快速控制反应镜制作

快速控制反应镜(以下简称快反镜)是光电精密跟踪系统中必不可少的组成部分,在消费电子、医疗、天文望远镜、激光通信等领域中有着广泛应用。基于硅基微电子机械系统(micro-electromechanical system, MEMS,)工艺制作微型快反镜,对于实现快反镜和跟踪系统的小型化、轻量化有重要意义。陈述了一款硅基快反镜的结构设计、工艺选择以及制作攻关过程。通过加工便利性、加工精度、加工可靠性与制作成本的综合分析比较,确定了MEMS深硅刻蚀工艺制作小型化快反镜可动结构技术思路。快反镜的制作中,通过“化面为线”的版图优化减少刻蚀面积解决了深硅刻蚀不匀问题,通过清洗方法的对比和择优解决了反射镜面表面清洁度问题,通过改变金属化方法解决了镜面的面形精度控制问题。测试结果表明,此款基于硅基MEMS工艺的小型化快反镜满足了设计和应用需求。     

含多部位损伤搭接结构应力强度因子三维有限元分析

应力强度因子(Stress intensity factor,SIF)分析是含多部位损伤(Multiple site damage,MSD)结构剩余强度和裂纹扩展寿命预测的基础和关键。考虑接触与摩擦,建立了含MSD搭接结构的三维有限元模型,研究了不同裂纹长度、铆钉类型以及损伤模式下裂纹尖端SIF分布情况和变化规律。结果表明,搭接件孔边裂纹Ⅰ型SIF起主导作用,Ⅱ型和Ⅲ型SIF可忽略不计。由于次弯曲、铆钉变形和板厚度等因素,SIF在外表面最小,接触面一侧较大,最大值多位于蒙皮内部。MSD会使裂纹间的干涉作用增强,SIF增大,且裂纹间距离越近干涉作用越强。裂纹长度相同时,埋头铆钉的孔边裂纹SIF积分均值大于平头铆钉,且接触面的SIF埋头铆钉大于平头铆钉,外表面则相反。     

惯性推算误差抑制的神经网络自学习模型设计与验证

惯性推算误差抑制是提升复杂场景下组合导航定位性能的关键,现有采用运动约束或系统误差高阶建模的方法从运动学模型及传感器误差模型出发,通过经验确定参数及模型的最优解。深度学习隐式模型能够挖掘数据之间的隐含关系,进行自主化参数寻优,并在提升惯导误差建模精度方面具有一定优势。总结了现有主流网络模型设计的优缺点,通过对比不同的输入输出方案进行优选,最终利用卷积神经网络构建了一套惯性误差抑制的轻量化神经网络自学习模型,并利用实测车载数据验证了该模型的有效性。实验结果表明,在GNSS信号失锁300 s的路段I和失锁285 s的路段II,网络模型速度约束的算法相较于纯惯性推算和传统NHC算法均有一定提升,融合NHC及网络模型速度约束的算法在水平定位精度上分别改善了41.7%~47.4%和26.7%~36.6%,一定程度上抑制了惯性推算误差。     

探讨培养高职学生语文职业能力的途径

从弱化传统语文重视知识传授的做法、注重语文教学与专业学习的结合及加强语文能力的实践训练等方面,探讨培养高职学生语文职业能力的途径。