酚醛树脂炭的合成及力学性能研究

为了表征多孔炭泡沫材料基体的结构与力学性能,采用碱催化法制备热固性酚醛树脂,经固化、高温炭化处理合成多孔炭泡沫材料的基体——酚醛树脂炭。研究酚醛树脂炭的微观结构、压缩强度及压缩断裂韧性。结果表明:酚醛树脂炭结构以树脂炭基体、微孔和微裂纹为主,其碳元素以sp3杂化的非晶炭形式存在;压缩强度为8.58 MPa,压缩断裂特征为脆性断裂模式;酚醛树脂炭的压缩断裂韧性较差,断裂过程中吸收的总能量为0.135 MJ/m3。     

NiAl合金的热爆合成及其反应机制

本文研究了NiAl合金的热爆合成,其反应过程为液相控制,产物为β-NiAl,密度较高。本文给出了不同条件下合成的起爆时间及主要影响因素。     

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.     

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。     

三芳基均三氮杂苯环（TSTR）耐高温树脂的研究

从制备最主要的原材料入手,研究了ＴＳＴＲ树脂的合成,并对树脂进行了红外光谱分析（ＩＲ）以及差示扫描量热法（ＤＳＣ）和热重量分析法（ＴＧＡ）等热分析,其中４－氰基苯酐的一步合成法已申请了国家专利。试验结果表明：该树脂的最高工作温度可达４００℃,接近美国先进的ＰＭＲ－Ⅱ－５０ 高温树脂的工作温度。     

DDS中相位截断效应分析及其改善方法

分析了在直接数字频率合成（ＤＤＳ）中引起杂散的相位截断效应,针对其引起的杂散特点讨论了一种通过加入伪随机数改善杂散谱分布的方法,并通过计算机仿真进行了验证。     

数据中继卫星的频率和轨道

描述了典型数据中继卫星系统的通信链路;给出了这些系统在用的和计划使用的无线电频谱;讨论了影响数据中继卫星频段选择的因素。为了防止其他中继卫星系统对一个中继卫星系统的有害干扰,可以使用如频率错开、极化分辨、经度分离,甚至采用伪码分辨的方法。     

对旋轴流风机降噪措施的实验研究

针对一台自行设计的高效对旋轴流风机噪声高的缺点, 分析了主要噪声源及噪声的频率特征;并用消声声衬及适当增加管道长度的方法进行了大量的实验研究, 取得了良好的效果。总声压级由101dB(A)降至88dB(A)。      

数据收集系统下行频偏校准与点频值计算

风云二号（ＦＹ－２）卫星在轨运行期间本振源必定产生一定的频率偏移,这就影响了数据收集平台接收系统（ＤＣＰＲ）相应于各种平台的报文锁相环路的频率捕获范围,严重时将无法解调出各种平台收集的气象数据,整个系统也将无法正常工作。为解决上述问题,介绍了ＤＣＰＲ下行频偏校准及点频值计算的方法。通过ＦＹ－２卫星在轨测试表明,在随机干扰比较严重的情况下,ＤＣＰＲ对各种平台报文接收解调的成功率优于９８％,取得了令人满意的结果。     

一种低复杂度的Multi-h CPM相干解调算法及FPGA实现

多调制指数连续相位调制（Multi-h Continuous Phase Modulation,Multi-h CPM）是一种恒包络调制,具有多个周期出现的调制指数,因此其频谱效率和功率效率比单调制指数CPM更高,但其接收机的复杂度也随之增加。本文在倾斜相位（Tilted Phase,TP）的基础上采用频率脉冲截断（Frequency Pulse Truncation,FPT）和状态空间分割（State Space Partition,SSP）相结合的方法来降低多调制指数连续相位调制的复杂度,使相位状态由512降低到16,理论损耗约为0.8 dB。同时,对降低复杂度的解调算法在现场可编程门阵列（Field Programmable Gate Arrays, FPGA）上进行了验证。仿真和在线测试的误码率曲线接近理论分析曲线,和常用的128状态解调算法相比,资源消耗降低了约59%。