超声速射流对挡流板的冲击流场的数值模拟

采用数值分析方法分析了跨声速喷管无粘流动和超声速射流对挡流板的冲击流场。该方法是对激波流动添加了显式人工粘性项，控制方程仍为Ｎａｖｉｅｒ－Ｓｔｏｋｅｓ方程，采用ＭａｃＣｏｒｍａｃｋ二阶显式预后－校正差分格式求解。     

A proposal on the test of general relativity by clock transportation experiments

We propose a test of the gravitational time dilation in general relativity by long term clock comparison between two stations separated in height. The geopotential difference between the two National time keeping centers in China, Lintong (A)$(A)$ and Beijing (B)$(B)$ is around 4000 geopotential unit, which corresponds to the height difference of 400 m. Two clocks _CA$C_A$ and _CB$C_B$ are fixed at stations A and B, respectively, which are synchronized at beginning by a portable clock C in a short time period with go-back synchronization approach. After one month, the clock C is again transported between A and B  , comparing the records of the keeping time by clocks _CA$C_A$ and _CB$C_B$, respectively. Calculations show that, after one month, the difference of the time durations between the clocks _CA$C_A$ and _CB$C_B$ is around 121 ns, if general relativity is correct.     

高动态GPS/SINS 组合导航系统的时间同步方法

高动态环境下GPS/SINS 组合导航系统的同步误差源均被不同程度地放大, 严重影响了系统的组合性能. 给出了同步时间基准及记录GPS 通信延时的硬件设计思想. 在此基础上, 将GPS 与SINS 的时标差、SINS 的频标漂移及GPS 的通信延迟作为同步误差源, 采用软件处理方式完成对SINS 频标漂移的建模、量测信息的外推计算及GPS 通信延时的滤波补偿, 使系统的量测信息在每一个同步点上实现同步. 仿真结果验证了方法的有效性.      

非线性时间序列在卫星通信网络数据预测中的研究

卫星通信网络数据预测在卫星通信系统中起着重要的作用,是系统建模的主要研究内容之一。由于卫星通信网络数据的非平稳性和不可预知因素的影响,决定了应采用非线性时间序列建模方法来分析、预测。在分析通信网络数据的基础上,建立卫星通信网络数据的ARIMA模型,在确定预测模型的阶和进行参数估计后,给出不同预测步数条件下的通信网络数据流量的预测,并进行了仿真对比实验。仿真结果表明,该模型在预测步数较小的情况下,预测误差在4％左右,具有良好的预测精度,为卫星通信网络数据流量的预测、异常检测和网络负载预测的应用奠定了坚实的基础。     

基于模型预测控制的非线性飞行控制系统研究

应用泰勒级数展开方法设计了飞行器六自由度非线性模型预测控制器.通过对控制向量和输出向量的有限泰勒级数展开,确定闭环形式的控制输入.仿真结果表明:该方法能够适应控制项不完全或缺少控制项的病态情况,适当选择控制器的泰勒展开阶数可得到最优的控制结果,所设计的模型预测控制器具有很好的跟踪效果.     

任意K元Huffman树的新构造

给出了一种简单而有效地构造任意k元最优Huffman树的新方法。给出了Huffman村存贮的父母一子女环结构,该结构空间利用率高,在不增加parent域的情况下,使查找父母的T（m）达到O（1）,并能高效实现建立最优Huffman树和求Huffman编码的算法,无论是空间复杂度还是时间复杂度均优于传统算法,具有很强的实用性。     

Combining frequency and time domain models to forecast space weather

Space weather series incorporate several distinct components, cycles at multiple frequencies, irregular trends, and nonlinear variability. The cycles are stochastic, i.e., the amplitude varies over time. Similarly, the trend is stochastic: the slope and direction of trending change repeatedly. This study sets out a combined model using both frequency and time domain methods, in two stages. In the first stage, a frequency domain algorithm is estimated and forecasted. In the second stage, the forecast is used as an input in a neural network. The combined model also includes a term enabling the model to react inversely to large deviations between the actual values and forecast. The models are evaluated using two data sets, the hemispheric power data obtained from the Polar Orbiting Environment satellites, and the Aa geomagnetic index. All the series are at a daily resolution. Forecasting experiments are run over horizons of 1–7 days. The models are estimated using a moving window or adaptive approach. The combined model consistently achieves the most accurate results. Among single equation methods, the frequency domain model is more accurate for the geomagnetic index because it is able to capture the underlying cycles more effectively. In the hemispheric power series, the cycles are less pronounced, so that time domain methods are more accurate, except at very short horizons. Nevertheless, in both data sets, the combined model works well because the frequency domain algorithm captures cyclical behavior, while the neural net is better able to capture short-term dependence and trending.     

Time constants in the ionosphere from neural network models

Neural network (NN) models for the low latitude and the polar ionosphere from the D- to the F-region were developed which are based on incoherent scatter radar data from Arecibo and EISCAT Svalbard, respectively. The various geophysical input parameters defining the NN are not only the ones that represent the time one wants to predict, but also the geophysical conditions prior to the time of the prediction. The optimum length of these preceding periods are derived for the two models are different, but a period of 60 days is a compromise acceptable for both latitudes. Furthermore from the Arecibo data time constants of electron density decay after sundown are derived which – arguably – are also relevant elsewhere, including the polar latitudes. Whereas at all altitudes the electron densities decay exponentially after sundown, below 300 km there is an additional variation with solar zenith angle.     

定位环系列产品的工艺及模具设计

按定位环系列产品外径大小,设计了三种定位环系列产品压制模具结构,不仅结构合理,制造成本低,而且做到了一模多用。     

航材消耗的时间序列分析

本文采用时间序列分析法对某种航材故障率进行预测,用移动平均法消除时间序列的长期趋势和周期变动,然后按月平均法求出季节指数,并对季节指数进行调整,然后根据拟合的趋势方程对此种航材的故障率进行预测.其结果能为航材的可靠性保障提供理论依据.