Analysis of Airport Risk Propagation in Chinese Air Transport Network

Zhang, Xuejun; Zhao, Shuaizhe; Mei, Hao

doi:10.1155/2022/9958810

Cited by 3 publications

(2 citation statements)

References 45 publications

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“…Wang et al [6] estimated a statistical model to identify the relationship between transfer flow and the network properties in a joint bus and metro network. Zhang et al [7] applied complex network theory to analyze the evolution of the risk propagation airport network. Zhou et al [8] made use of complex network science indicators with spatial cognition weighted accessibility combining full urban rail network, road network, and pedestrian network.…”

Section: Introductionmentioning

confidence: 99%

Invulnerability of the Urban Agglomeration Integrated Passenger Transport Network under Emergency Events

2022

IJERPH

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Urgent natural environmental events, such as floods, power failures, and epidemics, result in disruptions to the traffic system and heavy disturbances in public requirements. In order to strengthen the ability of the transport network to handle urgent natural environmental issues, this paper simulates the disruption situation of traffic stations in the urban agglomeration by attacking nodes, and evaluates the ability of the transport network to resist disruptions (i.e., invulnerability). Firstly, the model of the urban agglomeration integrated passenger transport network is established based on complex network theory. The highway network, railway network, and coupling network are combined into a multi-layer network space structure, and the edge weight is calibrated by travel time and cost. Secondly, the invulnerability simulation process including multiple attack modes under random and deliberate attack strategies is sorted out. By improving the traditional network efficiency indicator, the network impedance efficiency indicator is proposed to measure network performance, and the network relative impedance efficiency indicator is used to evaluate network invulnerability and identify key nodes. Finally, Chengdu–Chongqing urban agglomeration is taken as a case study. The results show that the network does not collapse quickly and it shows certain invulnerability and robustness under continuous random attacks. Network performance and invulnerability are not necessarily positively correlated. The failure of individual nodes that are small in scale but act as transit hubs may significantly degrade the network performance. The identified key nodes have significance for guiding the construction, maintenance, and optimization of the urban agglomeration passenger transport network, which is conducive to promoting public safety.

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Section: Introductionmentioning

confidence: 99%

Invulnerability of the Urban Agglomeration Integrated Passenger Transport Network under Emergency Events

2022

IJERPH

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“…Wu et al used the identification of air traffic complexity to evaluate flight safety and quality [29]. Zhang et al's team used complex networks to perform a risk analysis of the flight network, which helped to reduce risk propagation and delays [30]. erefore, it is feasible to use the complex network theory to analyze civil aviation safety issues.…”

Section: Introductionmentioning

confidence: 99%

Identifying Key Risk Factors in Air Traffic Controller Workload by SEIR Model

Heng

Wen

2022

Mathematical Problems in Engineering

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To address the controller workload with the forecast, the capacity of the air traffic management system is effectively enhanced. It should be based on a specific analysis of the controller workload. In the current controller workload studies, there is no clear means to analyze the process of controller workload development propagation. In this paper, we propose a new method for analyzing the factors influencing the controller workload. This method takes into account the influence of various situations in the actual work of controllers and objectively quantifies the complexity of work conditions. A complex network is constructed by treating various factors as nodes and the complexity relationships between these nodes as edges. The complexity network was then tested using the contagion model. The sum of the number of times of infecting other nodes and being infected in the detection result was defined as the infection capacity of the nodes, and the point with the strongest infection capacity was controlled and analyzed. The results show that the point with the strongest infection capacity is the key factor for the development of controller workload generation. In addition, the analysis of the key factors using a backpropagation neural network shows that the prediction of the controller workload can be made by the key factors. It will provide a new effective method to control controller workload and improve air traffic control capability.

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Temporal Variation of Airborne Dust Concentrations in the Mogao Grottoes, Dunhuang, China

Zhang

Tan

Zhang

et al. 2022

Front. Environ. Sci.

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Dust storms bring a large quantity of dust aerosols from arid and semi-arid regions of the Earth. However, real-time dust concentration data for dust storms in arid regions, important for wind erosion studies, are still limited. Here, temporal variation of airborne dust concentrations in the Mogao Grottoes, Northwest China, during the monitoring period from February to October 2012 and typical dust storms under different wind directions were analyzed. Results reveal that the monthly mean total suspended particle (TSP), particulate matter less than 10 μm (PM10), and particulate matter less than 2.5 μm (PM2.5) concentrations gradually decreased from February to October. The daily mean dust concentrations fluctuated with the day, with extreme values occurring mainly on February, March, and April. The daily mean PM10/TSP ratio ranged from 0.67 to 0.98 (mean of 0.82), and the PM2.5/PM10 ratio ranged from 0.31 to 0.73 (mean of 0.55), indicating PM10 dominated in TSP. In typical dust storms, the maximum real-time concentrations can reach 16, 000–21, 000 μg TSP m−3, ∼11, 000 μg PM10 m−3, and 3000–3500 μg PM2.5 m−3, and extreme real-time dust concentrations of 50358.03 μg TSP m−3, 33100.86 μg PM10 m−3, and 7502.59 μg PM2.5 m−3 were recorded. Coincidence of the dry climate and windy season and sufficient dust sources in the surrounding environment contributed to the high dust concentrations in the Mogao Grottoes. To achieve the goal of minimizing the damage of falling dust to the murals and statues, establishing a dust storm early warning system and improving the existing sand control system are recommended.

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Analysis of Airport Risk Propagation in Chinese Air Transport Network

Cited by 3 publications

References 45 publications

Invulnerability of the Urban Agglomeration Integrated Passenger Transport Network under Emergency Events

Invulnerability of the Urban Agglomeration Integrated Passenger Transport Network under Emergency Events

Identifying Key Risk Factors in Air Traffic Controller Workload by SEIR Model

Temporal Variation of Airborne Dust Concentrations in the Mogao Grottoes, Dunhuang, China

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