Analyzing the multilevel structure of the European airport network

The multilayered structure of the European airport network (EAN), composed of con-nections and flights between European cities, is analyzed through the k-core decomposition of the connections network. This decomposition allows to identify the core, bridge and periphery lay-ers of the EAN. The core layer includes the best-connected cities, which include important business air traffic destinations. The periphery layer includes cities with lesser connections, which serve low populated areas where air travel is an economic alternative. The remaining cities form the bridge of the EAN, including important leisure travel origins and destinations. The multilayered structure of the EAN affects network robustness, as the EAN is more robust to isolation of nodes of the core, than to the isolation of a combination of core and bridge nodes.     

民用飞机空气导管内外温度分布研究

对空气导管内外温度分布进行了研究,建立具体的换热模型并采用两种方法进行了计算,同时还分析了导管布置对空气传热和流动特性的影响。     

防空导弹弹性振动抑制

基于防空导弹的数学模型,根据弹体弹性振动的特性,对抑制其振动的方法和稳定回路设计进行了研究。通过确定频带宽度稳定刚性弹体的姿态运动,采用陷波补偿相位稳定和增益稳定抑制弹性振动以稳定弹性弹体。给出了稳定回路的设计,并比较了不同方法的特点。     

空间拦截中只测量视线角速度的跟踪滤波器的可观性分析

建立了空间拦截中导弹与目标的相对运动方程。论述了卡尔曼滤波器的可观性准则，研究了跟踪滤波器的可观性，并分析了影响跟踪滤波器可观性的因素。数字仿真证实了理论的正确性。     

Strategic flight assignment approach based on multi-objective parallel evolution algorithm with dynamic migration interval

The continuous growth of air traffic has led to acute airspace congestion and severe delays, which threatens operation safety and cause enormous economic loss. Flight assignment is an economical and effective strategic plan to reduce the flight delay and airspace congestion by reasonably regulating the air traffic flow of China. However, it is a large-scale combinatorial optimization problem which is difficult to solve. In order to improve the quality of solutions, an effective multi-objective parallel evolution algorithm(MPEA) framework with dynamic migration interval strategy is presented in this work. Firstly, multiple evolution populations are constructed to solve the problem simultaneously to enhance the optimization capability. Then a new strategy is proposed to dynamically change the migration interval among different evolution populations to improve the efficiency of the cooperation of populations. Finally, the cooperative co-evolution(CC) algorithm combined with non-dominated sorting genetic algorithm II(NSGA-II) is introduced for each population. Empirical studies using the real air traffic data of the Chinese air route network and daily flight plans show that our method outperforms the existing approaches, multiobjective genetic algorithm(MOGA), multi-objective evolutionary algorithm based on decomposition(MOEA/D), CC-based multi-objective algorithm(CCMA) as well as other two MPEAs with different migration interval strategies.     

Measuring air traffic complexity based on small samples

Air traffic complexity is an objective metric for evaluating the operational condition of the airspace.It has several applications,such as airspace design and traffic flow management.Therefore,identifying a reliable method to accurately measure traffic complexity is important.Considering that many factors correlate with traffic complexity in complicated nonlinear ways,researchers have proposed several complexity evaluation methods based on machine learning models which were trained with large samples.However,the high cost of sample collection usually results in limited training set.In this paper,an ensemble learning model is proposed for measuring air traffic complexity within a sector based on small samples.To exploit the classification information within each factor,multiple diverse factor subsets (FSSs) are generated under guidance from factor noise and independence analysis.Then,a base complexity evaluator is built corresponding to each FSS.The final complexity evaluation result is obtained by integrating all results from the base evaluators.Experimental studies using real-world air traffic operation data demonstrate the advantages of our model for small-sample-based traffic complexity evaluation over other stateof-the-art methods.     

空气动力试验中的计量监督与保障

以具体事例说明了计量在空气动力试验中的作用，简述了对基地计量体系建立与发展的认识和体会。     

Robustness analysis metrics for worldwide airport network: A comprehensive study

Robustness of transportation networks is one of the major challenges of the 21st century. This paper investigates the resilience of global air transportation from a complex network point of view, with focus on attacking strategies in the airport network, i.e., to remove airports from the sys-tem and see what could affect the air traffic system from a passenger's perspective. Specifically, we identify commonalities and differences between several robustness measures and attacking strate-gies, proposing a novel notion of functional robustness: unaffected passengers with rerouting. We apply twelve attacking strategies to the worldwide airport network with three weights, and eval-uate three robustness measures. We find that degree and Bonacich based attacks harm passenger weighted network most. Our evaluation is geared toward a unified view on air transportation net-work attack and serves as a foundation on how to develop effective mitigation strategies.     

Atmospheric electrical conductivity measurements and modeling for application to air pollution studies

The experimentally measured ground level atmospheric electrical conductivity is validated from a simplified ion–aerosol model for which the inputs are ionization rate from surface radioactivity, aerosol density and meteorological parameters. Also estimated from the model is the reduction in conductivity for assumed aerosol levels. It is seen that for an increase of ambient aerosols by threefold the percent reduction in conductivity is 7% and it is 10% for an increase by sixfold. Thus, the variations in the measured ground level conductivity can be used to examine the atmospheric pollution, if any.     

A320系列飞机大气数据系统的维护

大气数据系统是飞机重要的机载系统。本文结合系统原理、工程技术资料和自身维护经验,对A320系列飞机大气数据系统日常维护中的一些常见故障和特殊故障进行分析,给出维护建议,并对系统维护中的注意事项进行提示与强调。