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Accurate aircraft turnaround time prediction is an important way to coordinate the operation time of airport ground service and improve the efficiency of airport operation. In this paper, by analyzing the aircraft turnaround operation process, a description model based on Time Transition Petri Net is proposed. The model describes the flight turnaround operation process and the logical relationship of the operation. According to the model, a dynamic prediction method of turnaround time based on Bayesian theorem is designed. According to the actual landing time of the flight, the aircraft turnaround time is predicted. The specific method is to obtain the prior probability distribution and joint distribution law of each operation link according to the flight history data, and use Shapiro-Wilke to test the prior probability distribution of each link. Based on the analysis and comparison between the actual turnaround data of a large airport in China and the forecast data proposed in this paper, the root-mean-square error 3.75 minutes and the mean absolute error 3.40 minutes can be calculated. This paper contributes to the improvement of flight punctuality rate and airport clearance level. [ABSTRACT FROM AUTHOR]

The spread of the COVID-19 had profoundly affected the development of the air transportation. In order to determine the changes in air transportation volume associated with the development of the epidemic, this paper takes Southwest China as the study area. Monthly data and methods, such as the coefficient of variation, rank-size analysis and spatial matching index, were applied. The results found that: (1) during 2020–2022, there was a positive relationship between passenger volume and epidemic development, while freight volume increased for most airports in the first quarter of 2020–2022, particularly in the eastern region; (2) From the perspective of changes in air transportation volume under the development of the COVID-19, among various types of airports, the changes in transportation volume of main trunk airports were more significant than those of regional feeder airports in remote areas; (3) however, under the influence of the epidemic, main trunk airports still exhibited stronger attraction in passenger volume. That is to say, the passengers who chose to travel by air still tended to choose the main trunk airports and formed the agglomeration distribution pattern which around high-level airports in the provincial capital. Whereas the freight volume had a tendency of equalization among airports in Southwest China; (4) Over the course of time, the consistency of the spatial distribution of the number of cases and the passenger or freight volume in southwest China gradually increased. Among them, the spatial matching rate of the passenger volume and the number of COVID-19 cases was always higher than that of the cases and freight volume, which might indicate that there was a stronger correlation relationship. Therefore, it is proposed that the construction of multi-center airport system should be strengthened, the resilience of the route network for passenger transportation should be moderately enhanced, and the risk-resistant capacity of mainline airports and airports in tourist cities should be upgraded, so as to provide references for the orderly recovery of civil aviation and regional development. [ABSTRACT FROM AUTHOR]

The construction of airport runways or other infrastructures on soft soil might risk damage and create potential hazards if inappropriate foundation treatments have been conducted. Preloading on soft soil is a commonly used ground improvement method in airport runway construction, owing to the cost efficiency and simplicity of this method. However, the theoretical basis for the design parameter estimation of this method has not been fully understood, for example, preloading height calculation and preloading time determination. In this paper, calculation models of settlement characteristics for soft soil preloading treatment and influence factors of preloading for soft soil are proposed, in accordance with Terzaghi one-dimensional consolidation theory. Preloading is counted as a dynamic process in this theory, and the settlement calculation model is expressed as an integration formula. In addition, a simplified calculation model is proposed in this paper for a specific condition of preloading treatment. Reliability of the models was verified with in situ data from an airport runway construction site in China. Results from multiple analysis reveal that preloading treatment can significantly increase the total settlement and consolidation, and accelerate the settlement rate of soft soil. Sensitivity analysis of the theoretical model found that preloading height is the key parameter affecting the preloading efficiency when ignoring the material type of soft soil. Moreover, the thickness of soft soil is the critical input parameter, as analyzing the factors affects the preloading height, and preloading treatment is a continues process rather than an instantaneous process, as can be noted from analyzing the settlement characteristics of the two loading conditions. The proposed settlement characteristic model provides valuable information for the design of preloading parameters of similar projects. Preloading is a simple and widely used method for improving the strength of soft soil; the design of preloading parameters mainly relies on the construction of a trial site or engineering judgment. The theoretical basis of this method is still weak. Thus, this paper proposes a settlement characteristic model under preloading conditions, which was verified by utilizing in situ data from an airport runway construction site. In addition, the influences of design parameters on such settlement characteristics as preloading height and thickness of backfill soil were analyzed. It was found that preloading height is the key parameter affecting the settlement characteristics of preloading treatment. In addition, sensitivity analysis was conducted on the preloading height design using an analytical model, and the results show that the thickness of soft soil is the critical factor affecting the preloading height. In that case, accurate site investigation is significant for the preloading design of soft soil. [ABSTRACT FROM AUTHOR]

Given the pressing requirements for sustainable development in civil aviation, conducting a synergistic evolution analysis of the supply and demand aspects in the airport green development holds great significance. This analysis helps achieve sustainable airport development and facilitates the green transformation of civil aviation development. Taking a collaborative learning approach and utilizing historical data from Guangzhou Baiyun International Airport spanning 2008 to 2019, the supply-demand composite system for airport green development was deconstructed into two subsystems-demand and supply-and relevant evaluation index systems were established in this paper. A screening and optimization model of supply and demand synergy indicators for airport green development was constructed, and it was solved using a simulated annealing genetic algorithm. The Haken model was constructed to analyze the synergistic evolutionary relationship of the composite system of supply and demand for green airport development in two stages. The results indicate a shift in the order parameter of the co-evolution of the supply-demand composite system at Guangzhou Baiyun International Airport, moving from the demand subsystem in the first stage (2008-2015) to the supply subsystem in the second stage (2016-2019). The co-evolution of the airport supply-demand composite system has entered a new stage, but has not reached a high level of synergy. The study not only contributes theoretically by explaining the interaction mechanism between supply and demand for airport green development, but also offers targeted suggestions for achieving high-quality synergistic evolution of supply and demand for airport green development., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Wan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Based on the perspective of flight technology and flight safety, the unsaturated clayey foundation soil of a high plateau airport in the mountainous area of southwest China is taken as the research object, and the calculation method of the composite modulus of CFG pile composite foundation with the soil between the piles as the unsaturated soil is established according to the relevant characteristics of unsaturated soil, and the calculation method of the composite foundation's settlement is carried out on the basis of this method. At the same time, Plaxis finite element analysis software is used to model the actual project and numerically analyze the settlement characteristics of the composite foundation. Finally, the calculation results of the two methods are compared and studied with the actual settlement monitoring values on site. The study shows that: 1) the theoretical analysis method is able to consider the effects of pile length, pile modulus, and matrix suction in unsaturated soil of rigid piles on the composite modulus, which is more in line with the reality than the conventional composite modulus method that does not consider the unsaturated nature of the soil between the piles; 2) the resultant values computed by the theoretical and numerical analysis methods recommended in this paper are both smaller than those measured at the site but the difference is within the range of 10%, so that in the actual plateau of the High Plains airports can choose the two analysis methods recommended in this paper to conduct related research. [ABSTRACT FROM AUTHOR]

This research focused on the relationships among 34 major airports in China, analyzing how these relationships are influenced by spatial dependence and heterogeneity. Using a spatial econometric model, it found that passenger traffic in China's airports displays a mutually driven aggregation effect. Furthermore, the study revealed that the airport relationship changes from complementarity to competition as the geographic distance between them decreases. The study also classified the main airports in China into three hierarchical levels and found significant complementarity and competition among those within the hub-and-spoke network structure. Specifically, this study identified a complementary relationship among regional trunk and local branch airports, as-well-as significant competition among hub airports. Crucially, the study suggests that the absence of a hub airport weakens the collaborative interactions between different types of airports, emphasizing the critical importance of hub airports for the connectivity and operational efficiency of China's airport network. [ABSTRACT FROM AUTHOR]

To promote the application of automated vehicles in large airports, in this study, we present an integrated optimization method for scheduling Unmanned follow-me cars. The scheduling process is divided into three phases: Dispatch, Guidance, and Recycle. For the Dispatch phase, we establish a vehicle assignment model, to allocate the vehicle resource equitably. For the Guidance phase, we offer an quantitative way, to measure the spacing between Unmanned follow-me car and aircraft. To optimize the efficiency of airport operation in the three phases and ensure safety, the collaborative planning model, and the conflict prediction model are established. An improved grey wolf optimization algorithm is adopted to enhance the convergence speed and generalization performance. A case study at Ezhou Huahu Airport in China demonstrates the effectiveness of the methods. The results show that the model of collaborative planning can make the balance of path selection, Unmanned follow-me car's working time, and departure sequence. The convergence speed of the improved algorithm has been increased by 18.75%. The inequity index of vehicle assignment is only 0.015731, and the spatiotemporal distribution of conflicts is influenced by the airport's surface layout. [ABSTRACT FROM AUTHOR]

Though the impact of urban vegetation on air quality and the microclimate has attracted increasing attention, there have been few studies quantitatively assessing this impact in North China, where air pollution is severe. In this study, we investigated the impact of urban forests and urban parks on air quality and the microclimate in Jinan, northern China. Six sites were chosen to represent urban forest, urban park, and downtown areas, respectively. The results indicate that urban forest can effectively reduce PM2.5 and ozone (O3) concentrations in the warm season, when temperatures are higher and plants are lush. The PM2.5 and O3 concentrations in the urban forest areas were 6.3–6.5 μg m−3 and 21–23 μg m−3 lower than those in downtown areas during the period of 10:00–15:00. In contrast, urban park areas can reduce PM2.5 concentrations but have little impact on gaseous pollutants such as nitrogen dioxide and O3. Furthermore, both urban forest and urban park areas reduced temperatures, by approximately 4.1–6.8 °C and 1.36 °C, respectively, and increased relative humidity, by about 13.4–12.9% and 0.9%, promoting a more comfortable thermal environment for residents. Therefore, this study highlights the crucial role of urban vegetation in improving air quality and creating a comfortable environment for residents. [ABSTRACT FROM AUTHOR]

Efficient aircraft turnaround operations at airports are vital to ensure overall air traffic network performance. After the outbreak of COVID-19, the traditional aircraft ground handling process has changed significantly due to new requirements put forward by the pandemic prevention and control policy. To better understand how COVID-19 has affected ground handling operations, a discrete-event simulation model of turnaround is established to analyze the change in the whole turnaround process before and after the pandemic. The critical path of turnaround operations was used to identify the significantly affected subprocesses to which airports should pay attention. For a case study on the two busiest airports in China, the aircraft turnaround time increased by about 18% after COVID-19. Cabin cleaning, catering, and passenger embarking were the main processes in causing this increase. By evaluating the impact mechanism of COVID-19 on turnaround operations, the study sheds light on strategic, tactical, and operational approaches for relevant authorities. [ABSTRACT FROM AUTHOR]

Aircraft icing due to severe cold and local factors increases the risk of flight delays and safety issues. Therefore, this study focuses on optimizing de-icing allocation and adapting to dynamic flight schedules at medium to large airports. Moreover, it aims to establish a centralized de-icing methodology employing unmanned de-icing vehicles to achieve the dual objectives of minimizing flight delay times and enhancing airport de-icing efficiency. To achieve these goals, a mixed-integer bi-level programming model is formulated, where the upper-level planning guides the allocation of de-icing positions and the lower-level planning addresses the collaborative scheduling of the multiple unmanned de-icing vehicles. In addition, a two-stage algorithm is introduced, encompassing a Mixed Variable Neighborhood Search Genetic Algorithm (MVNS-GA) as well as a Multi-Strategy Enhanced Heuristic Greedy Algorithm (MSEH-GA). Both algorithms are rigorously assessed through horizontal comparisons. This demonstrates the effectiveness and competitiveness of these algorithms. Finally, a model simulation is conducted at a major northwestern hub airport in China, providing empirical evidence of the proposed approach's efficiency. The results show that research offers a practical solution for optimizing the use of multiple unmanned de-icing vehicles in aircraft de-icing tasks at medium to large airports. Therefore, delays are mitigated, and de-icing operations are improved. [ABSTRACT FROM AUTHOR]