Thermospheric neutral density response to solar forcing

Recent measurements by the Solar EUV (Extreme Ultra Violet) Experiment (SEE) aboard the Thermosphere–Ionosphere–Mesosphere Energetics and Dynamics satellite (TIMED) provide solar EUV spectral irradiance with adequate spectral and temporal resolution, and thus the opportunity to use solar measurements directly in upper atmospheric general circulation models. Thermospheric neutral density is simulated with the NCAR Thermosphere–Ionosphere–Electrodynamic General Circulation Model (TIEGCM) using TIMED/SEE measurements and using the EUVAC solar proxy model. Neutral density is also calculated using the NRLMSISE-00 empirical model. These modeled densities are then compared to density measurements derived from satellite drag data. It is found that using measured solar irradiance in the general circulation model can improve density calculations compared to using the solar proxy model. It is also found that the general circulation model can improve upon the empirical model in simulating geomagnetic storm effects and the solar cycle variation of neutral density.     

Deuterium Fractionation in Interstellar Clouds

This paper reviews the chemical processes responsible for fractionating deuterium in interstellar molecules. I show that this process is intrinsically a low temperature phenomenon and discuss how the degree of enhancement of the deuterium content of molecules is related to the physical conditions, particularly abundances, in molecular clouds. If significant amounts of abundant species, such as CO, are frozen out on to interstellar dust grains, the resulting enhancement in H₂D⁺ can result in its abundance being greater than that of H ₃ ⁺ at 10K. Transfer of the deuteron from H₂D⁺ can then lead to the efficient formation of multiply deuterated species, such as NHD₂ and ND₃. Fractionation can also occur in grain surface reactions and some simple models are discussed. This revised version was published online in August 2006 with corrections to the Cover Date.     

有限β等离子体中密度和磁场不均匀驱动的动理学Alfven波

在分析有限β等离子体中的密度、磁场不均匀引起的漂移波不稳定性的基础上，剖析了漂移波不稳定性对动理学Alfven波激发的作用．动理学理论能正确地处理有限拉莫半径效应和波粒共振相互作用，本文根据带电粒子在电磁场中的运动特性，采用Vlasov方程描述离子运动，运用漂移动理学方程对电子运动进行描述．密度不均匀和磁场不均匀对产生漂移不稳定性的对比分析表明：在有限β等离子体中，密度不均匀比磁场不均匀更易激发漂移不稳定性，且密度不均匀激发漂移不稳定性中的能量转换和转移更为强烈．这种能量的转换为动理学Alfven波的激发提供了物理基础．所得数值解表明：动理学Alfven波在磁层中能广泛地被激发产生，特别是在磁层空间的极尖区、磁层顶和等离子体片边界层等具有明显的不均匀性区域中更容易被激发产生．本文的研究结果进一步表明动理学Alfven波对磁层空间中能量传输具有重要作用．     

基于经验模态分解的点云数据平滑与增强

在计算机辅助设计与逆向工程应用中,针对缺乏拓扑连接关系的点云数据,提出了基于经验模态分解(EMD)的点云数据平滑与增强算法。首先,以点云模型的拉普拉斯矩阵坐标与法向的内积作为EMD输入信号,提取点云模型输入信号的极值点作为插值节点计算信号的上下包络;然后,为实现特征保持的EMD信号分解,通过检测点云数据上特征点,并在计算信号上下包络的过程中作为约束,克服传统EMD算法无法保持特征的局限;最后,迭代地从输入信号中减去上下包络的均值得到内蕴模态函数(IMF)和余量,并通过设计滤波器实现了点云数据平滑和增强。实验结果表明,本文算法有效地将EMD推广到三维散乱点云数据中,扩大EMD在三维几何中的应用范围,并在点云数据平滑和增强方面取得了很好的效果。     

A point cloud deep neural network metamodel method for aerodynamic prediction

Aiming to reduce the high expense of 3-Dimensional (3D) aerodynamics numerical simulations and overcome the limitations of the traditional parametric learning methods, a point cloud deep learning non-parametric metamodel method is proposed in this paper. The 3D geometric data, corresponding to the object boundaries, are chosen as point clouds and a deep learning neural network metamodel fed by the point clouds is further established based on the PointNet architecture. This network can learn an end-to-end mapping between spatial positions of the object surface and CFD numerical quantities. With the proposed aerodynamic metamodel approach, the point clouds are constructed by collecting the coordinates of grid vertices on the object surface in a CFD domain, which can maintain the boundary smoothness and allow the network to detect small changes between geometries. Moreover, the point clouds are easily accessible from 3D sensors. The point cloud deep learning neural network, which employs re-sampling technique, the spatial transformer network and the fully connected layer, is developed to predict the aerodynamic characteristics of 3D geometry. The effectiveness of the proposed metamodel method is further verified by aerodynamic prediction and robust shape optimization of the ONERA M6 wing. The results show that the proposed method can achieve more satisfactory agreement with the experimental measurements compared to the parametric-learning-based deep neural network.     

磁控溅射用W-Ti合金靶材的研究进展

W-Ti合金靶材可作为原材料，通过磁控溅射技术，制备W-Ti、W-Ti-N、W-Ti-O等功能薄膜，应用于集成电路、薄膜太阳能电池等领域。本文介绍了W-Ti合金靶材的性能指标、各种制备技术和应用领域，提出高纯度、全致密、少富Ti相、小粒径、大尺寸、低成本是W-Ti合金靶材的重要方向。     

一种互相关法测量相位噪声理论及仿真分析

相位噪声测量是无线电计测领域的重要研究内容，随着信号源等各种信号仪器设备的不断发展，相位噪声测量技术方面也产生了更高的要求。介绍了互相关法测量相位噪声的理论与仿真分析方法，通过理论推导阐释了互相关法抑制干扰噪声的原理，在推论的基础上建立了基于MATLAB的仿真分析模型，仿真验证了不同互相关次数下，系统噪声底部的改善程度，并进一步分析了双通道相关性对互相关运算结果的影响，得到了对应的仿真验证结果，为相关的工程设计提供参考。     

沥青浸渍炭化C/ C 复合材料密度及孔隙分布

以径棒法编织成型预制体,采用沥青浸渍炭化工艺制备了C/ C 复合材料(1. 50 g/ cm3 ),采用CT

检测了试件的密度分布特征,并采用光学显微镜和压汞法分析了试件的孔隙分布特征。结果表明,在沥青浸渍

炭化的工艺条件下,试件外端密度最高,由外端到中心沿径向密度递减;以坯体中心为参照点,同一圆周方向密

度均匀分布;坯体开孔率沿径向由外端到中心递增;坯体大孔和中孔孔容积比率沿径向从外端到中心递增,而

微孔孔容积比率则从外端到中心递减。

     

基于多维特征的战场实体目标分群方法

目标分群问题也称为群形成过程，是态势估计中的一个重点和难点问题，属于信息融合中的高层融合范畴。现有的目标分群方法大多是将空间位置相近的目标聚为一类，极少有分群方法考虑到进行战场态势分析所需的位置、速度、航向、属性和类型等多维特征。为此，首先根据海战场态势分析需求，基于目标的特征属性定义了多维度欧式距离；然后综合利用分类与密度聚类两种分析方法，提出了一种战场实体目标分群方法,以综合实现战场实体目标的实时分群处理；最后，将该算法应用于一个军用场景的数据集上进行仿真实验。仿真结果表明了该方法在海战场环境中实现目标分群处理的可行性和有效性。