This paper aims to capture the interdependency among the sequence of flight delays due to airline operations in airports, weather, and air traffic control conditions. A copula function is used to determine the distribution of delay sequence and examine the propagation effects. Using the actual data sourced from an airline in Asia Pacific region, it is found that flight delays could propagate to downstream airports/airlines, where the strength of delays was decreased, passed on, or increased. Considering the possible effects of increased delays under air traffic control or airline factors, scenarios that adjust flight schedules with additional buffer time were created and analyzed. Results show that, by adding buffer time efficiently, flight schedules can become more reliable.
In this paper, we develop a route-traffic-based method for detecting community structures in airline networks. Our model is both an application and an extension of the Clauset-Newman-Moore (CNM) modularity maximization algorithm, in that we apply the CNM algorithm to large airline networks, and take both route distance and passenger volumes into account. Therefore, the relationships between airports are defined not only based on the topological structure of the network but also by a traffic-driven indicator. To illustrate our model, two case studies are presented: American Airlines and Southwest Airlines. Results show that the model is effective in exploring the characteristics of the network connections, including the detection of the most influential nodes and communities on the formation of different network structures. This information is important from an airline operation pattern perspective to identify the vulnerability of networks.
Clean-energy substitution technology for existing residential buildings in cities is an inevitable choice for sustainable development and low-carbon ecological city construction. In this paper, the current status of energy-saving renovation and renewable-energy applications for existing residential buildings in various cities in China was summarized by using statistical methods. The geographical distribution of clean-energy power generation in primary energy production in China was explored in depth. According to different climatic divisions for existing urban residences, clean-energy production and consumption were analyzed and predicted based on the STIRPAT model. The results show that the energy consumption of urban residential buildings in 2016 increased by 43.6% compared with 2009, and the percentage of clean energy also increased from 7.9% to 13.4%. Different climatic regions have different advantages regarding clean energy: nuclear power generation leads in the region that experiences hot summers and warm winters, whereas wind and solar power generation lead in the cold and severely cold regions. The present results provide basic data support for the planning and implementation of clean-energy upgrading and transformation systems in existing urban residences in China.
This paper investigates flight delay propagation in air transportation networks (ATNs) by considering both network structures and airport operation performance. An airport susceptible-infected-recovered (ASIR) model is established based on the mechanism of epidemic spreading, where the focus is on the impact of the infection rate in order to properly map and understand the probability of delay propagation. Different network configurations are abstracted under complex network theory, in which the ASIR model can be simulated upon. The simulation results show that the original airport traffic, airport connection and the level of airport turnaround services play important roles in influencing delay propagation in different airports. In addition, changes of network structure such as the emerging of secondary hubs can also influence the delay propagation. INDEX TERMS flight delay propagation, infection rate, network structures, ASIR model, flight delay simulation. HAOYU ZHANG is pursuing a Ph.D. degree in Science: Geography at the Geography Department at Ghent University (UGent, Belgium). Her research focuses on Transportation Planning and Management, Transportation network optimization, Complex network theory and Flight delay propagation and controlling. She participates in the Natural Science Foundation of China Project (71201081) and has published 8 publications on these topics, 3 of them are on SCI indexed and 3 are EI indexed.
This paper examines flight delay propagation in air transport networks. Delays add to additional costs, inefficiencies, and unsustainable development. An integrated flight-based susceptible-infected-susceptible (FSIS) model was developed to analyse the flight delay process from a network-based perspective. The probability of flight delay propagation was determined using a translog model. The model was applied to an airline network consisting of thirty-three routes involving three airlines. The results show that the propagation probability is network-related and varies across different routes. The variation is related to the flight frequencies at airports, route distances, scheduled buffer times, and the propagated delay time. Whereas buffer time has a greater impact on smaller airports, flight movement has a greater impact on larger airports. Having a better understanding of how delays happen can help the development of strategies to avoid them. This will lead to less costs, higher efficiencies, and more sustainable airport and airline development.
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