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.     

Observations of the ozone and nitrogen dioxide profiles in the TROICA-4 experiment

To investigate the vast area of Russia, a mobile scientific facility based in a railway carriage was developed. It is capable to perform continues measurements being coupled in a passenger train traveling along railroads. It was first equipped with a spectrometer for remote sensing of ozone and nitrogen dioxide in the atmosphere for the transcontinental observations into the chemistry of the atmosphere-4 expedition performed from February 18 to March 5, 1998. A twilight DOAS method, which was applied for retrieval of the nitrogen dioxide profiles basing on spectral measurements at the visible wavelengths (434–451 nm), is described in the paper. Main features of a new algorithm for retrieval of the ozone profile and total content using the differential structure of the UV spectrum (310–335 nm) are presented. The ozone and nitrogen dioxide contents are obtained and shortly validated against available alternative data.     

Identifying vital edges in Chinese air route network via memetic algorithm

Due to rapid development in the past decade, air transportation system has attracted considerable research attention from diverse communities. While most of the previous studies focused on airline networks, here we systematically explore the robustness of the Chinese air route network, and identify the vital edges which form the backbone of Chinese air transportation system. Specifically, we employ a memetic algorithm to minimize the network robustness after removing certain edges, and hence the solution of this model is the set of vital edges. Counterintuitively, our results show that the most vital edges are not necessarily the edges of the highest topological importance, for which we provide an extensive explanation from the microscope view. Our findings also offer new insights to understanding and optimizing other real-world network systems.     

飞机敏捷性与空空导弹攻击区综合研究

基于飞行力学与控制,导弹制导与攻击区,计算机仿真等理论和技术,针对飞机的三轴方向提出了一种敏捷性矢量的估算方法,建立了求解攻击区的弹道方程组,并利用二分法求解导弹攻击区,通过数值计算求得两种情况,（即无敏捷性载机地敏捷性目标,敏捷性载机对无敏捷性目标）下空空导弹攻击区,并对计算结果进行了分析,得出飞机敏捷性对导弹攻击区和影响规律和最优攻防策略,为空战决策和新型飞机的预研设计提供了参考。     

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.     

Physics results with the ARGO-YBJ experiment

ARGO-YBJ is a multipurpose experiment consisting in a dense sampling air shower array with 93% sensitive area located at very high altitude. The apparatus is in stable data taking since November 2007 at the YangBaJing Cosmic Ray Laboratory (Tibet, PR China, 4300 m a.s.l., 606 g/cm²). In this paper we report the main results in Gamma-Ray Astronomy and Cosmic Ray Physics after about 3 years of operation.     

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。