高温燃气流风洞非稳态运行过程实验和数值模拟研究

针对热考核用高温燃气流风洞运行过程中的非稳态过程开展研究，采用风洞实验与数值计算相结合的方法研究了风洞整体起动、扩压器背压抬升、关机三种过程中喷管、实验舱和扩压器内瞬态流动特性。实验结果揭示了燃气风洞诸多有趣的瞬态现象，且披露了一手实验数据。而通过数值计算能较好地复现上述瞬态现象；借助数值计算能合理地解释试验现象产生的原因；还能捕捉实验中无法观测到的现象；此外还评估了该风洞扩压器的抗反压裕度在10kPa以上。因此，数值方法是研究大型燃气风洞瞬态流动特性最重要的辅助手段。该研究可为类似风洞运行调试提供借鉴，并为风洞实际运行提供数据支撑。     

Precise orbit determination and baseline consistency assessment for Swarm constellation

Precise orbit determination (POD) and precise baseline determination (PBD) of Swarm satellites with 4 years of data are investigated. Ambiguity resolution (AR) plays a crucial role in achieving the best orbit accuracy. Swarm POD and PBD based on single difference (SD) AR and traditional double difference (DD) AR methods are explored separately. Swarm antenna phase center variation (PCV) corrections are developed to further improve the orbit determination accuracy. The code multipath of C1C, C1W and C2W observations is first evaluated and clear variations in code noise related to different receiver settings are observed. Carrier phase residuals of different time periods and different loop tracking settings of receiver are studied to explore the effect of ionospheric scintillation on POD. The reduction of residuals in the polar and geomagnetic equator regions confirms the positive impact of the updated carrier tracking loops (TLs) on POD performance. The SD AR orbits and orbits with float ambiguity (FA) are compared with the Swarm precise science orbits (PSOs). An average improvement of 27 %, 4 % and 16 % is gained in along-track, cross-track and radial directions by fixing the ambiguity to integer. For Swarm-A/B and Swarm-B/C formations, specific days are selected to perform the DD AR-based POD during which the average distance of the formation satellites is less than 5000 km. Satellite laser ranging (SLR) observations are employed to validate the performance of FA, SD AR and DD AR orbits. The consistency between the SD AR orbits and SLR data is at a level of 10 mm which shows an improvement of 25 % when comparing with the FA results. An SLR residuals reduction of 15 % is also achieved by the DD AR solution for the selected days. Precise relative navigation is also an essential aspect for spacecraft formation flying missions. The closure error method is proposed to evaluate the baseline precision in three dimensions. A baseline precision of 1–3 mm for Swarm-A/C formation and 3–5 mm for Swarm-A/B and Swarm-B/C satellite pairs is verified by both the consistency check and closure error method.     

Fractional order adaptive robust formation control of multiple quad-rotor UAVs with parametric uncertainties and wind disturbances

In recent times, multiple Unmanned Aerial Vehicles (UAVs) are being widely utilized in several areas of applications such as agriculture, surveillance, disaster management, search and rescue operations. Degree of robustness of applied control schemes determines how accurate a swarm of UAVs accomplish group tasks. Formation and trajectory tracking controllers are required for the swarm of multiple UAVs. Factors like external environmental effects, parametric uncertainties and wind gusts make the controller design process as a challenging task. This article proposes fractional order formation and trajectory tacking controllers for multiple quad-rotors using Super Twisting Sliding Mode Control (STSMC) technique. To compensate the effects of the disturbances due to parametric uncertainties and wind gusts, Lyapunov function based adaptive controllers are formulated. Moreover, Lyapunov theorem is used to guarantee the stability of the proposed controllers. Three types of controllers, namely fixed gain STSMC and fractional order Adaptive Super Twisting Sliding Mode Control (ASTSMC) methods are tested for the swarm of UAVs by performing the numerical simulations in MATLAB/Simulink environment. From the presented results, it is verified that in presence of wind disturbances and parametric uncertainties, the proposed fractional order ASTSMC technique showed improved robustness as compared to the fixed gain STSMC and integer order ASTSMC.     

遥测装备智能运维系统的研究与工程化实现

随着航天发射和在轨航天器管理任务的不断增加，为支撑各类测控需求，遥测站数量越来越多，测控系统越来越复杂。为了从整体降低对遥测任务及遥测装备的运维管理成本，提升运维信息的应用能力，为各类角色用户提供有效全面的信息支撑，需要建立体系化的遥测装备智能运维系统。构建多级智能化运维体系，通过现代化信息感知和传输技术实现装备信息的多维度快速获取、感知和汇聚，全局性掌控战斗资源，建设运维中心及信息处理平台完成数据的智能融合处理，通过对各装备、各时段数据的比较，关联挖掘信息，深层次利用运维数据，实现资源全景展示、装备状态监视与智能维护、运行效能评估、态势分析与预测等能力，为遥测资源和战斗力部署调度提供直接全面的决策支撑。     

Comparison of electron density measurements from CSES and Swarm satellites with GNSS ionospheric tomography data

Electron density measurements obtained from China Seismo‐Electromagnetic Satellite (CSES) and Swarm-B can play an increasingly important role in the study of ionosphere above F2 peak height. This study presented a comprehensive comparison of electron density products obtained from Langmuir probe mounted on CSES and Swarm-B with ionospheric tomography for a whole year period of 2019. CSES was fully compared with Swarm-B on a global scale, including both absolute and relative differences, and a new index called NFI was developed to better quantify the similarity between two latitudinal profiles of electron density. CSES and Swarm-B were then compared with tomography respectively in four regions, roughly located in America, Europe, Australia and China. Results indicated that CSES data are consistent with Swarm-B, as NFI values exceed 0.6 for most of the analyses. Tomography and Swarm-B were found to have a good agreement as their biases are less than 0.2 × 10⁵ el/cm³ in general. For the comparison between CSES and tomography, the bias increased to around 0.6 × 10⁵ el/cm³ but the standard deviation changed slightly, validating the underestimation of electron density by CSES. The spatiotemporal comparisons of CSES and Swarm-B with tomography showed that: 1) the differences in electron density were relatively low in middle latitudes and increased rapidly in the regions of equatorial ionization anomaly; 2) Swarm-B has a better consistent with tomography than CSES, but both are capable of detecting ionosphere anomalies such as midlatitude arcs; and 3) CSES and Swarm-B both can capture the seasonal changes of electron density, while their values are basically smaller than those from tomography in Spring and Summer months.     

国产支线飞机航线运营经济性分析框架

国产某支线飞机进入市场化运营阶段，运营经济性成为推动民机产业发展的主导因素，亟需基于该支线飞机运营数据和实践经验研究建立国产支线飞机航线运营经济性分析框架。首先进行支线飞机潜在边际收益的因果关系分析，随后从成本和收益角度分别构建直接运营成本模型、间接运营成本模型、潜在边际收益模型、运输收益模型等，然后从年度收入成本分析、寿命周期收入成本分析、飞机投资回报分析三个维度提出支线飞机航线运营的经济性分析指标，从而构建了国产支线飞机的航线运营经济性分析框架。基于案例研究，从客公里收入、吨公里成本、收入成本利润、静态投资回收期、动态投资回收期等方面对飞机进行经济性分析，最后提出国产支线飞机的优化设计与运营经济性的相关建议。     

大型航空运输企业航班恢复系统(RM)应用研究

随着航空公司机队规模和运营航线的不断扩大,在发生大面积航班延误时,航空公司需要快速计算出最优的航班恢复方案。为了提高运行控制效率,探索一种优化控制的方法,根据经济效益、航班正常等不同的目标要求,计算出最优的运行方案,最终达到快速、高效地调配航班。分析了大型航空运输企业不正常航班恢复的主要场景,在此基础上筛选了制约航班恢复的关键约束条件,设计了航班恢复和校验的基本逻辑,通过应对台风处置的实际案例,验证了某大型航司和美国世博公司的航班恢复系统(RM)在实际案例应用中的效果,总结了该航班恢复系统的优点和存在的风险及短板。实践表明,该系统可缩短2 h航班运行恢复时间,平均每个受影响航班减少延误30 min,减少相应的成本2万元,提升整体航班正常率3%~5%。     

面向一体化测试与运管的航天器指令技术研究

现有的航天器测试与运管程序通过word文档采用自然语言的方式进行描述，需要人工录入、集成、整合和校验，既浪费人力、时间，又容易因人为原因出错，不利于测试与运管程序在多用户间的快速交互，且存在安全隐患。针对该问题，借鉴NASA及ESA的PLEXIL、PLUTO、Timeliner-TLX、SCL等航天器指令设计经验，研究了面向航天器地面测试与在轨运管的航天器指令技术，该指令架构具备层次化、模块化、抽象化等高级程序特点，且具备对航天器进行工作过程监测与异常状态处置能力，便于航天器测试与运管程序的人机交互、数字化设计、交换共享与解译执行，可作为国内航天器测试与运管程序一体化设计的技术参考。     

空间核动力装置控制系统设计分析及启示

空间核动力装置执行深空任务具有复杂性和特殊性，对其控制系统的研发提出较多独特的挑战。研发具有高可靠性和高自主性的控制系统，一直是空间核反应堆领域的研究重点及难点之一。对美俄(苏联)从20世纪80年代至今典型空间堆控制系统的研发方案展开调研，分别从控制系统的总体要求、架构设计、启动控制策略、额定工况下功率控制方案等方面，对其设计现状进行分析和归纳，总结美俄不同型号空间堆控制系统的设计及其特殊性。在美俄空间堆控制系统设计的经验基础上，为不同型号空间堆装置控制系统的设计提供借鉴。     

A geographical and operational deep graph convolutional approach for flight delay prediction

Flight delay prediction has attracted great interest in civil aviation community due to its significant role in airline planning, flight scheduling, airport operation, and passenger service. Flight delay is affected by numerous factors and irregularly propagates in air transportation networks owing to flight connectivity, which brings critical challenges to accurate flight delay prediction. In recent years, Graph Convolutional Networks (GCNs) have become popular in flight delay prediction due to the advantage in extracting complicated relationships. However, most of the existing GCN-based methods have failed to effectively capture the spatial–temporal information in flight delay prediction. In this paper, a Geographical and Operational Graph Convolutional Network (GOGCN) is proposed for multi-airport flight delay prediction. The GOGCN is a GCN-based spatial–temporal model that improves node feature representation ability with geographical and operational spatial–temporal interactions in a graph. Specifically, an operational aggregator is designed to extract global operational information based on the graph structure, while a geographical aggregator is developed to capture the similar nature among spatially close airports. Extensive experiments on a real-world dataset demonstrate that the proposed approach outperforms the state-of-the-art methods with a satisfying accuracy improvement.