不同直径圆球诱导燃烧的振荡机制与频率特性

为了分析不同直径圆球诱导振荡燃烧的规律，并揭示圆球大小在振荡燃烧现象中所发挥的深层次作用，本文采用二维轴对称Euler方程和基元反应模型，对不同直径的圆球在H2/air预混气体中诱导振荡燃烧的现象开展数值模拟研究。研究发现，振荡频率并不是简单地随直径增大而逐渐从高频向低频连续过渡，而是存在两次突变，形成了超高频、高频以及低频三种振荡燃烧模态。在两种模态间过渡时，振荡达到稳定状态前，会存在一段双频耦合的振荡阶段。三种不同振荡燃烧模态的产生是受到了不同振荡机制的作用，而两种模态间过渡时的双频耦合现象则是两种机制相互竞争的结果。     

Early analysis of precise orbit and clock offset determination for the satellites of the global BeiDou-3 system

Eight new-generation BeiDou satellites (BeiDou-3) have been launched into Medium Earth Orbit (MEO), allowing for global coverage since March 2018, and they are equipped with new hydrogen atomic clocks and updated rubidium clocks. Firstly, we analyzed the signals for the carrier-to-noise-density ratio (C/N0) and pseudorange multipath (MP) by using international GNSS (Global Navigation Satellite System) Monitoring and Assessment System (iGMAS) station data, and found that B1C has a lower C/N0, and B2a has the same level of C/N0 as the B1I and B3I signals. For pseudorange multipath, compared with the BeiDou-2 satellites, the obvious systematic variation of MP scatters related to the elevation angle is greatly improved for the BeiDou-3 and BeiDou-3e satellites signals. For the signals of the BeiDou-3 satellites, the order of the Root Mean Square (RMS) values of multipath and noise is B3I?<?B1I?<?B2a?<?B1C. Then, the comparison of the precise orbit determination and clock offset determination for the BeiDou-2, BeiDou-3, and BeiDou-3 experimental (BeiDou-3e) satellites was done by using 10 stations from iGMAS. The 3D precision of the 24?h orbit overlap is 24.55, 25.61, and 23.35?cm for the BeiDou-3, BeiDou-3e, and BeiDou-2 satellites, respectively. BeiDou-3 satellite has a comparable precision to that of the BeiDou-2 satellite. For the precision of clock offset estimation, the Standard Deviation (STD) of the BeiDou-3 MEO satellite is 0.350?ns, which is an improvement of 0.042?ns over that of the BeiDou-2 MEO satellite. The stabilities of the BeiDou-3 and BeiDou-3e onboard clocks are better than those of BeiDou-2 by factors of 2.84 and 1.61 at an averaging time of 1000 and 10,000?s, respectively.     

Using TensorFlow-based Neural Network to estimate GNSS single frequency ionospheric delay (IONONet)

In the last 20?years, and in particular in the last decade, the availability of propagation data for GNSS has increased substantially. In this sense, the ionosphere has been sounded with a large number of receivers that provide an enormous amount of ionospheric data. Moreover, the maturity of the models has also been increased in the same period of time. As an example, IGS has ionospheric maps from GNSS data back to 1998, which would allow for the correlation of these data with other quantities relevant for the user and space weather (such as Solar Flux and Kp). These large datasets would account for almost half a billion points to be analyzed. With the advent and explosion of Big Data algorithms to analyze large databases and find correlations with different kinds of data, and the availability of open source code libraries (for example, the TensorFlow libraries from Google that are used in this paper), the possibility of merging these two worlds has been widely opened. In this paper, a proof of concept for a single frequency correction algorithm based in GNSS GIM vTEC and Fully Connected Neural Networks is provided. Different Neural Network architectures have been tested, including shallow (one hidden layer) and deep (up to five hidden layers) Neural Network models. The error in training data of such models ranges from 50% to 1% depending on the architecture used. Moreover, it is shown that by adjusting a Neural Network with data from 2005 to 2009 but tested with data from 2016 to 2017, Neural Network models could be suitable for the forecast of vTEC for single frequency users. The results indicate that this kind of model can be used in combination with the Galileo Signal-in-Space (SiS) NeQuick G parameters. This combination provides a broadcast model with equivalent performances to NeQuick G and better than GPS ICA for the years 2016 and 2017, showing a 3D position Root Mean Squared (RMS) error of approximately 2?m.     

基于ANSYS Workbench的行星滚柱丝杠动态特性分析

通过Pro/Engineer建立行星滚柱丝杠三维模型，基于ANSYS Workbench有限元分析技术进行模态与谐响应分析，得到前六阶固有频率与各阶模态振型，确定共振频率，掌握对应频率下的位移峰值响应，并研究螺母处于不同工作位置时对固有频率的影响，为基于行星滚柱丝杠传动的舵系统抗振设计提供数据支撑。     

一种基于观测站数目最小化的TDOA/FDOA无源定位算法

在三维（3D）运动目标无源定位系统中，无模糊定位最少需要4个观测站。而传统的两步加权最小二乘（TSWLS）及其改进的闭式算法至少需要5个观测站进行求解，当减少一个观测站时，这些闭式算法往往无法提供可靠解。针对这一问题，提出一种最小化观测站数目的到达时间差（TDOA）与到达频率差（FDOA）定位算法。该算法是一种闭式解法并且能够在三维场景下仅使用4个观测站进行定位。该算法分为两步：第1步分离传统的TSWLS算法中未知参数空间，建立了一组新的等式，并且利用加权最小二乘（WLS）算法得到目标位置与速度的初始值；第2步利用泰勒级数展开算法将中间变量线性化，对目标位置和速度初始值进一步校正。理论分析证明了在适当的噪声水平下该算法能够达到克拉美罗界（CRLB）。此外，计算机仿真表明仅使用4个观测站时，该算法对于近场以及远场目标参数的估计精度在测量噪声较小时可以实现CRLB；并且还表明使用5个观测站估计时，该算法比TSWLS及其改进算法能更好地适应大的测量噪声。     

单向电永磁作动器结构优化与动态特性分析

针对电磁作动器的使用要求，设计出一种具有能耗低、吸力大及响应快等特点的新型单向电永磁作动器。结合有限元仿真软件，利用有限元法研究作动器的结构参数如铁芯齿形结构、平面结构、无永磁结构、铁芯的倾斜角度及衔铁位移（气隙厚度）等因素对作动器电磁吸力和响应速度的影响。结果表明，电磁吸力随着作动衔铁位移的增加而大幅度减小；倾角结构的铁芯设计能使作动器性能达到最佳，且铁芯的倾斜角度为50°时，电磁吸力有最大值3071N。     

超宽带变频系统中的本振产生技术研究

本振源是超宽带变频系统中的核心部件，本文以超宽带上变频系统为例，介绍变频系统中本振信号的产生技术。本文所设计的超宽带变频系统，经过三次上变频，可将(0.8~2.8)GHz 的低频信号变换至（0.5~40）GHz。变频过程中需要一系列点频本振和一组宽带本振，基于PLL+DFS 的方法产生点频本振，基于DDS+DFS 的方式产生宽带本振。     

拓扑数据分析在复杂脑网络分析中的应用

针对复杂脑网络分析中网络结构变化阈值选择中没有公认的标准确定合适阈值这一问题，基于拓扑分析中的持续同调性理论，本文提出一种多尺度大脑网络建模分析方法，该方法在大脑全尺度距离范围之内，通过不断增加阈值，运用Rips过滤算法捕获网络的动态持续拓扑特征，并用条形码和持续图对拓扑特征可视化，最后通过计算持续图之间的Bottleneck距离和Wasserstein距离分析持续特征的稳定性。实验结果表明，该方法能更准确地提取大脑网络的拓扑结构特征并提高诊断分类的准确性。     

流向强迫作用下的液体初始雾化机制及动力学特征

使用Volume of fluid (VOF)方法和基于树形数据结构的自适应算法来研究射流雾化的破碎过程以及扰动对射流破碎机理产生的影响。在无扰动情况下,液体射流的头部、液丝和液滴随着射流时间的发展不断发生演变。射流头部先呈现蘑菇状外形,随后液丝生成,并慢慢转变成网兜状,直至断裂形成小液滴。在周期性流向强迫的作用下,射流液柱的表面会形成周期波,其液丝破裂形成液滴的时机与稳定射流情形相比会有所提前,射流形成的头部更趋于扁平,最终生成的液滴数量更多。低中频阶段,随着扰动频率的增大,射流未扰动液柱长度(L)逐渐缩短,液滴直径的概率密度分布(PDF)趋于尖锐,液滴平均直径(SMD)增大。在高频阶段,随着扰动频率的增大,L会随之增大,液滴直径的PDF分布变得平缓,SMD会减小。     

介质材料对频率选择表面传输特性的影响

通过理论计算和实验验证分析了介质材料对频率选择表面传输特性的影响规律,讨论了蒙皮的厚度、介电常数,芯层厚度、介电常数四个因素对FSS的通带位置、宽度、损耗的影响。结果表明,蒙皮和芯层厚度增厚会使通带位置向低频移动,厚度减小通带位置向高频移动;蒙皮和芯层介电增大会使通带位置向低频移动,介电减小通带位置向高频移动。并测试了同样结构的FSS平板传输特性,理论分析和实验结果一致性较好。