Higher order ionospheric propagation effects on GPS radio occultation signals

With the increasing number of remote sensing satellites using the GPS radio occultation technique for atmospheric sounding, the estimation of higher order ionospheric effects and their mitigation have become relevant and important. Due to long ionospheric limb paths, GPS signals are strongly affected by ionospheric refraction during radio occultation. Standard dual-frequency GPS measurements may be used to estimate the first order term of the refractive index. However, non-linear terms such as the second and third order ionospheric terms and ray path bending effects are not considered in occultation measurements so far. Analysing selected CHAMP–GPS occultation events different higher order ionospheric terms are estimated and their effects on dual-frequency range estimation and total electron content (TEC) estimation are discussed. We have found that the separation between the GPS L1 and L2 ray paths exceeds the kilometer level during occultation for a vertical TEC level of more than 160 TEC units. Corresponding errors in the GPS dual-frequency range estimation and TEC estimation are found to exceed the meter and 10 TEC units level, respectively.     

某型航空活塞发动机排气门烧蚀机理

针对某型航空活塞发动机在运行中因使用国产高铅燃油而时常发生较严重的排气门烧蚀故障的问题,通过对该型发动机上全新、使用过以及已烧蚀排气门的微观金相分析,结合该型发动机的结构设计和实际运行环境分析这种排气门烧蚀故障的发生机理,认为排气门运行温度过高导致排气门密封面上的抗腐蚀保护层被破坏掉是导致排气门烧蚀的根本原因,而高铅燃油中的铅沉积在排气门密封面上导致排气门散热不良是排气门过热的主要原因.据此提出改用低铅燃油减少铅沉积以改善排气门散热条件、降低排气门运行温度的解决方案,经实际运行测试证明排气门密封面上的抗腐蚀保护层得到了有效保护,解决了该型发动机的排气门烧蚀故障.      

基于特征正交分解法的翼型结冰冰形快速预测

为加快翼型结冰冰形的计算速度,提出了一套基于特征正交分解(POD)法的结冰冰形快速预测算法.通过计算流体动力学(CFD)数值模拟计算得到的冰形结果作为样本,以结冰温度单参数变化时为例,详细介绍了POD法预测结冰冰形的实现步骤.考虑结冰温度、结冰时间以及液态水含量的影响,完成了单参数、两参数与三参数变化时的POD结冰冰形快速预测.通过算例结果发现:完成POD预测计算只需几秒钟且POD法与CFD法得到的冰形吻合较好,仅在冰角附近有较小差别,表明POD方法能够快速、准确地得到翼型的结冰冰形.      

过冷大水滴飞溅特性数值分析

针对过冷大水滴（SLD）撞击结冰表面的飞溅现象,开发了基于欧拉法的二维算法程序,该程序将LEWICE飞溅模型和FENSAP飞溅模型耦合到水滴流场控制方程中进行求解,实现了对SLD撞击特性的准定常计算。根据水滴飞溅模型中对于飞溅生成子水滴质量和速度等信息的定义,通过定义控制方程中的源项,将其耦合到控制方程的求解中,进而研究水滴飞溅效应对于撞击特性的影响。研究发现,由于水滴的飞溅作用,导致翼型壁面附近的液态水含量（LWC）分布发生变化;通过对上述两种典型的SLD飞溅模型进行计算分析,发现了SLD撞击特性的一些共性和不同,并揭示了SLD撞击效应的一般特点。     

Near real-time modeling of global ionospheric vertical total electron content using hourly IGS data

The International GNSS Service (IGS) has been providing reliable Global Ionospheric Maps (GIMs) since 1998. The Ionosphere Associate Analysis Centers (IAACs) model the global ionospheric Total Electron Content (TEC) and generate the daily GIM products within the context of the IGS. However, the rapid and final daily GIM products have a latency of at least one day and one week or so, respectively. This limits the value of GIM products in real-time GNSS applications. We propose and develop an approach for near real-time modeling of global ionospheric TEC by using the hourly IGS data. We perform an experiment in a real operating environment to generate near real-time GIM (named BUHG) products for more than two years. Final daily GIM products, Precise Point Positioning (PPP) based VTEC resources, and JASON-3 Vertical TEC (VTEC) measurements are collected for testing the performance of BUHG. The results show that the performance of BUHG is very close to that of the daily GIM products. Also, there is good agreement between BUHG and PPP-derived VTEC as well as with JASON-3 VTEC. It is possible that BUHG would be further improved with an increase in available hourly GNSS data.     

基于旋转多圆柱的冰风洞水滴参数分析方法

阐述了基于旋转多圆柱测量仪的冰风洞水滴参数分析方法.对二维圆柱的水滴撞击特性进行了计算分析;对二维旋转圆柱的霜状冰结冰过程进行了数值模拟;根据水滴参数对旋转圆柱结冰量的影响, 结合数学逼近的方法, 编制了由旋转多圆柱测量结果分析计算冰风洞水滴参数的软件, 最后用国外试验数据对软件分析结果进行了验证, 结果表明:计算方法正确, 可以实现冰风洞水滴参数快速测量.      

银-锑合金电镀工艺研究

研究了镀液组分及电镀工艺条件对银锑合金镀层锑含量和沉积速度的影响,研究结果表明,镀层锑含量随电流密度、氰化钾含量、酒石酸锑钾含量的增大而明显提高,随氢氧化钾含量的增加而明显降低,温度、酒石酸钾钠对镀层锑含量影响不大;镀层沉积速度由电流密度决定,镀液组分对其影响不大.根据上述研究结果及霍尔槽试验结果确定了镀液配方及电镀工艺参数,并对按此工艺镀出的镀层进行了全面性能检测.     

NNSS卫星测量参数求解TEC

论述了应用色散多普勒技术,在求解测站上空大面积TEC的方法中,卫星相对测站径向速度变化对电离层产生的微分多普勒频移的影响,找到了比较好的修正方法,并对若干测量计算结果进行了由定性到定量分析,绘出了测站上空任一点TEC的日变化曲线。      

Calibration errors in determining slant Total Electron Content (TEC) from multi-GNSS data

The global navigation satellite system (GNSS) is presently a powerful tool for sensing the Earth's ionosphere. For this purpose, the ionospheric measurements (IMs), which are by definition slant total electron content biased by satellite and receiver differential code biases (DCBs), need to be first extracted from GNSS data and then used as inputs for further ionospheric representations such as tomography. By using the customary phase-to-code leveling procedure, this research comparatively evaluates the calibration errors on experimental IMs obtained from three GNSS, namely the US Global Positioning System (GPS), the Chinese BeiDou Navigation Satellite System (BDS), and the European Galileo. On the basis of ten days of dual-frequency, triple-GNSS observations collected from eight co-located ground receivers that independently form short-baselines and zero-baselines, the IMs are determined for each receiver for all tracked satellites and then for each satellite differenced for each baseline to evaluate their calibration errors. As first derived from the short-baseline analysis, the effects of calibration errors on IMs range, in total electron content units, from 1.58 to 2.16, 0.70 to 1.87, and 1.13 to 1.56 for GPS, Galileo, and BDS, respectively. Additionally, for short-baseline experiment, it is shown that the code multipath effect accounts for their main budget. Sidereal periodicity is found in single-differenced (SD) IMs for GPS and BDS geostationary satellites, and the correlation of SD IMs over two consecutive days achieves the maximum value when the time tag is around 4?min. Moreover, as byproducts of zero-baseline analysis, daily between-receiver DCBs for GPS are subject to more significant intra-day variations than those for BDS and Galileo.     

Neural network prediction of the topside electron content over the Euro-African sector derived from Swarm-A measurements

This study presents the first prediction results of a neural network model for the vertical total electron content of the topside ionosphere based on Swarm-A measurements. The model was trained on 5 years of Swarm-A data over the Euro-African sector spanning the period 1 January 2014 to 31 December 2018. The Swarm-A data was combined with solar and geomagnetic indices to train the NN model. The Swarm-A data of 1 January to 30 September 2019 was used to test the performance of the neural network. The data was divided into two main categories: most quiet and most disturbed days of each month. Each category was subdivided into two sub-categories according to the Swarm-A trajectory i.e. whether it was ascending or descending in order to accommodate the change in local time when the satellite traverses the poles. Four pairs of neural network models were implemented, the first of each pair having one hidden layer, and the second of each pair having two hidden layers, for the following cases: 1) quiet day-ascending, 2) quiet day-descending, 3) disturbed day-ascending, and 4) disturbed day-descending. The topside vertical total electron content predicted by the neural network models compared well with the measurements by Swarm-A. The model that performed best was the one hidden layer model in the case of quiet days for descending trajectories, with RMSE = 1.20 TECU, R = 0.76. The worst performance occurred during the disturbed descending trajectories where the one hidden layer model had the worst RMSE = 2.12 TECU, (R = 0.54), and the two hidden layer model had the worst correlation coefficient R = 0.47 (RMSE = 1.57).In all cases, the neural network models performed better than the IRI2016 model in predicting the topside total electron content. The NN models presented here is the first such attempt at comparing NN models for the topside VTEC based on Swarm-A measurements.