Search Results (154)

Temperature and related thermal comfort metrics at a representative 9-member ensemble of airports in Europe are presented using a combination of historical (1985–2014) and future projection (2035–2064) timescales under a variety of forcing scenarios. Data are shown for summer (June–July–August) and the nine sites are further grouped into `oceanic’, `continentally influenced’, and `Mediterranean coastal’ climate types, which ameliorates visualisation and provides more generalised policy-relevant results. Using the Humidex metric, it is shown that some airports in southern Europe may enter a `dangerous’ (>45 C) regime of human discomfort. This would be accompanied by economic impacts related to longer mandated rest periods for ground workers, as well as increased water intake and changes to health and safety training. The coincidence of the 38 C flash point of kerosene jet fuel with perturbed daily maximum temperature occurrence thresholds at some sites will likely also have knock-on effects on safety practices since some sites may experience 70% of future summer days with temperatures exceeding this value. Using an 18 C threshold for defining cooling and heating `degree days’, increases in cooling requirements are projected to be larger than reductions in heating for continental and Mediterranean sites, and heatwave occurrence (3 or more days at or above the 95th historical percentile) may increase by a factor of 10. From a building and infrastructure services perspective, increased temperature variability around larger average values has the potential to reduce safe runway lifetimes and increase structural fatigue in large-span steel terminal buildings. Full article

The growing dominance of low-cost carriers (LCCs) in global air transport has intensified the need for airport terminal facilities that reflect their simplified, efficiency-driven operating principles. Traditional Level of Service (LOS) standards, based on International Air Transport Association’s Airport Development Reference Manual (IATA ADRM), were primarily designed for traditional air carriers or full-service network carriers (FSNCs) and may lead to over-dimensioned or misaligned airport terminal facilities when applied to airports with dominance of LCCs. This study presents the first newly developed computational tool called Airport Terminal Facilities Software (ATFS) as a methodological and conceptual advance in airport terminal planning, that integrates LOS guidelines differentiated by airline business models. The methodology integrates spatial–temporal LOS parameters, specific facility capacity formulas, and peak-hour demand calculations of airport terminal facilities. Results from the case study conducted at Pula Airport show substantial differences between IATA and LCC LOS outcomes, i.e., applying LCC LOS guidelines can significantly reduce required areas for the several airport terminal facilities. Findings confirm that new LCC LOS guidelines and the ATFS tool can optimize airport terminal facilities, reduce or reconfigure excessive or empty space, and improve passenger flow efficiency at LCC-dominant airports. Full article

Observations of building-induced airflow disturbances arising from the new terminal building at the Hong Kong International Airport (HKIA) are documented in this paper. Two case studies are conducted: one involving turbulent flow downstream of the building and another involving a coherent “building-induced wave”. To capture these phenomena under realistic atmospheric forcing, we employ a coupled mesoscale–computational fluid dynamics modelling system. This approach integrates mesoscale boundary-layer conditions with building-resolving simulations for real airport disturbance analysis. The main features of the actual observation are largely captured by the simulations. As such, the simulated data are studied to find out the reason for the difference in the airflow behavior. The difference could be related to the stability of the “background” atmospheric boundary layer. This stability is influenced by a number of complicated factors, including the background mesoscale atmospheric stability, Foehn effect of the terrain, and solar heating of the sea/land surface. The study further discusses potential implications for runway operations using aviation-relevant indicators, including the 7-knot criterion and turbulence intensity. Full article

Uncrewed aircraft systems are expected to revitalize traffic activities at under-utilized airports. These airports are often located in uncontrolled airspace and do not have an operating control tower to provide separation services for approaching aircraft. This presents unique challenges for the integration of uncrewed aircraft at non-towered airports. This paper offers a methodology to systematically assess traffic activities and quantify flight behaviors of crewed aircraft using historical flight data. To integrate uncrewed traffic in high-density traffic scenarios or during off-nominal flight situations, this paper assesses the concept of a holding stack above the traffic pattern airspace to handle increased traffic uncertainty and to provide safe integration procedures. Twelve non-towered airport environments, relevant for initial uncrewed cargo operations across Germany, California, and Texas, are investigated to assess concept feasibility and real-world implementation. Based on the interaction of various quantitative measures, results are presented on the feasibility of holding stacks in the terminal airspace and the influence of crewed aircraft’s historical flight behavior on different integration procedures for uncrewed aircraft. The analysis of various measures suggests that six airports are comparatively suitable candidates for holding layers above the airport traffic pattern, with holding altitudes to start between 2500 and 3500 feet above the ground. Full article

Airport environment often exposes passengers to stress, negatively impacting health and wellbeing. This study links plant visibility to passenger stress in Jakarta Terminal 3, applying the Stimulus-Organism-Response model to address a gap in airport research. The mixed methods included a combination of questionnaires (N = 104) and field observations. Statistical and behavioural analyses triangulated the findings. Respondents exhibit positive attitudes towards plants: 78% prefer lush images and 88% agree that seeing plants reduces stress. At the stimulus stage, awareness is high (86%), but visibility varies by zone. Stress levels peak at baggage claim (49%) and other processing areas. At the organism level, visibility is linked to stress only at arrival, with results suggesting that passengers who did not see plants are 4.57 times more likely to have high stress. At the response stage, results suggest that stress is not associated with dwell time, activities, or plant demand. However, those who see plants are 2.21 times more likely to request planting. The findings suggest prioritising plant visibility over volume, highlighting the need for broader scope and diverse data types in future research to yield more robust conclusions. Full article

In this paper, we propose a cooperative security method for unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) based on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm to address the scenario of unauthorized rogue drones (RDs) intruding into an airport’s restricted airspace. The proposed method integrates artificial intelligence techniques with engineering solutions to enhance the autonomy and effectiveness of air–ground cooperation in airport security. Specifically, the MADDPG algorithm enables the Security Interception UAVs (SI-UAVs) to autonomously detect and counteract RDs by optimizing their decision-making processes in a multi-agent environment. Additionally, Particle Swarm Optimization (PSO) is employed for distance-based target assignment, allowing each SI-UAV to autonomously select intruder targets based on proximity. To address the challenge of limited SI-UAV flight range, a power replenishment mechanism is introduced, where each SI-UAV automatically returns to the nearest UGV for recharging after reaching a predetermined distance. Meanwhile, UGVs perform ground patrols across different airport critical zones (e.g., runways and terminal perimeters) according to pre-designed patrol paths. The simulation results demonstrate the feasibility and effectiveness of the proposed security strategy, showing improvements in the reward function and the number of successful interceptions. This approach effectively solves the problems of target allocation and limited SI-UAV range in multi-SI-UAV-to-multi-RD scenarios, further enhancing the autonomy and efficiency of air–ground cooperation in ensuring airport security. Full article

This paper presents the results of personal exposure measurements to Radiofrequency Electromagnetic Fields from 2.4 GHz and 5.85 GHz Wi-Fi frequency bands. Measurements were taken in several specific scenarios: within international airports terminals, during takeoff, inside airplanes while flying with and without onboard Wi-Fi service (including while actively using a Wi-Fi connection), and during landing. Data were recorded onboard four international flights (two-round trip flights), from Spain to Mexico, and from Spain to Belgium. Two personal exposimeters, EME SPY 140 and EME Spy Evolution, were used to collect intensity level measurements in each scenario. During the outbound, the mean exposure value inside the airplane flight was 93.9 µW/m² in the 2.4 GHz Wi-Fi frequency band and 46.4 µW/m² in the 5.85 GHz Wi-Fi band (Spain to Mexico), and 7.29 µW/m² in the 2.4 GHz Wi-Fi band and 2.40 µW/m² in the 5.85 GHz Wi-Fi band (Spain to Belgium). For the return flight, the average value was 26.7 µW/m² in the 2.4 GHz Wi-Fi band and an average of 9.87 µW/m² in the 5.85 GHz Wi-Fi band (Mexico to Spain), and 3.24 µW/m² in the 2.4 GHz Wi-Fi band and 1.23 µW/m² in the 5.85 GHz Wi-Fi band (Belgium to Spain). Personal exposure levels to RF-EMFs from the Wi-Fi frequency band inside an airplane, even at the airport, are very low and well below the reference levels established by the international guidelines (10 W/m²). Full article

The standing seam metal roof system is wind-sensitive due to its light weight and decreasing stiffness as the span increases, and in recent years there have been a number of wind-exposed damages to the structures where these roof systems have been applied. In order to study the wind-uplifted resistance reliability of different types of standing seam metal roof systems, and then to evaluate their safety level, a reliability analysis framework was developed. The proposed approach integrates the Latin Hypercube Sampling–Monte Carlo Simulation (LHS–MCS) method to assess the wind-uplifted resistance reliability of standing seam metal roof systems. Taking Jinan Yaoqiang International Airport Terminal Building’s standing seam Al-Mg-Mn roof system and Urumqi Tianshan International Airport Transportation Center’s standing seam Al-Zn-plated steel roof system as the objects of research, the research was carried out from the aspects of wind uplift test, wind tunnel test, finite element simulation, and wind-uplifted resistance reliability analysis. The study shows the following: the wind-uplifted resistance bearing capacity of the roof systems is significantly affected by the width of the roof panel, the spacing of the fixed support, the thickness of the roof panel, and the diameter of end interlocking; the effects of the differences in structural parameters and roof types are eliminated by the introduction of a damage index, and the failure forms of different types of roof systems can be unified, and the corresponding limit state function can then be deduced; based on the LHS–MCS method, the reliability indexes of the two common types of standing seam metal roof systems were obtained to be 3.0975 and 3.2850, respectively, which are lower than the requirements of the code for the first safety level, and it is recommended that reinforcement measures be prioritized at the connection points between roof panel and support, such as reducing the spacing of the fixed support or decreasing the diameter of end interlocking, to improve the structural safety. The above study can provide a reference for the safety level assessment, wind resistant design, and sustainable operation and maintenance of different types of standing seam metal roof systems. Full article

Clustering of aircraft trajectories in terminal airspace is essential for procedure evaluation, flow monitoring, and anomaly detection, yet it is challenged by dense traffic, irregular sampling, and diverse maneuvering behaviors. This study proposes a unified framework that integrates dynamics-aware segmentation, Transformer–Variational Autoencoder (Transformer–VAE)-based representation learning, and density-aware clustering with joint optimization. A dynamic-feature Minimum Description Length (DFE-MDL) algorithm is introduced to preserve maneuver boundaries and reduce reconstruction errors, while the Transformer–VAE encoder captures nonlinear spatiotemporal dependencies and generates compact latent embeddings. Clusters are initialized using Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) and further refined through Kullback–Leibler (KL) divergence minimization to improve consistency and separability. Experiments on large-scale ADS-B data from Guangzhou Baiyun International Airport, comprising over 27,000 trajectories, demonstrate that the framework outperforms conventional geometric and deep learning baselines. Results show higher reconstruction fidelity, clearer cluster separation, and reduced computation time, enabling interpretable flow structures that reflect operational practices. Overall, the framework provides a data-driven and scalable approach for terminal-area trajectory analysis, offering practical value for STAR/SID compliance monitoring, anomaly detection, and airspace management. Full article

The port of Gaženica, managed by the Port Authority of Zadar, is open to public traffic of special economic interest to the Republic of Croatia. Situated outside Zadar’s city centre, with convenient access to the airport and A1 highway, this port presents significant opportunities for Zadar County’s economic growth. While also serving as a cargo and fishing port, as the second-largest passenger port in Croatia, the port of Gaženica prioritises the development of cruise ship traffic. The expansion of intermodal traffic is being facilitated through the development of a multipurpose terminal to accommodate general, roll-on/roll-off, and containerised cargo (full and empty containers). The rising number of passenger ships—particularly cruise ships—along with the increasing passenger, vehicle, and cargo traffic, poses a significant risk of pollution due to dust, noise, greenhouse gases, and other pollutants. Considering these risks, the use of alternative energy sources, decarbonisation of maritime transport, the separation of waste by type, and the proper handling and disposal of ship waste are of utmost importance. The aim of this study is to present and analyse the green transition process of the port of Gaženica through the results that have been achieved or are yet to be achieved through the implementation of green projects by the Port Authority of Zadar. For this purpose, a mixed-methods approach combining project analysis and the qualitative analysis of emissions data is used. It is important to highlight that the method of interviews with relevant representatives of institutions involved in the project was also used to gain insight into financial and infrastructural challenges, the accessibility of certain data, and potential improvements in implementation. The research results indicate that the port of Gaženica has completed four green projects, while another four are currently being implemented, with their completion expected by 2026. The research concludes that it is necessary to strengthen environmental awareness regarding proper waste disposal among all stakeholders in maritime transport, including the local community, businesses, and local authorities. The results demonstrate a need to focus on certification with the aim of strengthening the green transition process through involvement in the EcoPorts and Green Award certification schemes. It is also necessary to actively improve the public availability of data from the base station in the port of Gaženica to inform the public about environmental impacts in real time (24/7) while facilitating data collection for statistical reporting purposes. Full article

This study presents a Digital Twin–Mixed Reality (DT–MR) framework for the immersive and interactive supervision of automated container terminals (ACTs), addressing the fragmented data and limited situational awareness of conventional 2D monitoring systems. The framework employs a middleware-centric architecture that integrates heterogeneous subsystems—covering terminal operation, equipment control, and information management—through standardized industrial communication protocols. It ensures synchronized timestamps and delivers semantically aligned, low-latency data streams to a multi-scale Digital Twin developed in Unity. The twin applies level-of-detail modeling, spatial anchoring, and coordinate alignment (from Industry Foundation Classes (IFCs) to east–north–up (ENU) coordinates and Unity space) for accurate registration with physical assets, while a Microsoft HoloLens 2 device provides an intuitive Mixed Reality interface that combines gaze, gesture, and voice commands with built-in safety interlocks for secure human–machine interaction. Quantitative performance benchmarks—latency ≤100 ms, status refresh ≤1 s, and throughput ≥10,000 events/s—were met through targeted engineering and validated using representative scenarios of quay crane alignment and automated guided vehicle (AGV) rerouting, demonstrating improved anomaly detection, reduced decision latency, and enhanced operational resilience. The proposed DT–MR pipeline establishes a reproducible and extensible foundation for real-time, human-in-the-loop supervision across ports, airports, and other large-scale smart infrastructures. Full article

As the demand for air transportation surges, issues like flight conflicts and air-route congestion within multi-airport terminal areas have grown progressively more serious. Analyzing the evolution of air traffic situations in these areas can effectively enhance the air traffic’s early-warning capability, reduce flight conflicts, and alleviate air-route congestion. This paper proposes a method for analyzing the evolution of air traffic situations in multi-airport terminal areas based on flight segment–flight state interdependent network. First, a flight segment–flight state interdependent network model is established. This interdependent network model consists of an upper-layer flight state network, a lower-layer air-route network, and coupling edges. The upper-layer network is constructed with aircraft as nodes and flight conflicts between aircraft as edges. The lower-layer network takes air-routes as nodes and the connection relationships between air-routes as edges. The inter-layer coupling edges are determined by judging the relationship between aircraft and air-routes. If an aircraft is on a certain air-route, there exists a coupling edge between the aircraft node and the air-route node. On this basis, by comprehensively considering three network indicators, namely node degree, weighted clustering coefficient, and node strength, the overall air traffic situation value is obtained. Finally, experimental verification and analysis were conducted in an actual flight scenario of a multi-airport terminal area in the Guangdong–Hong Kong–Macao Greater Bay Area. The results show that the proposed method can accurately reflect the air traffic situation. The time-series analysis of the situation evolution reveals that the evolution process has chaotic characteristics. Full article

Key air route segments refer to route segments that play a hub-supporting role in the air transportation network of a specific airspace, and whose traffic anomalies (such as saturation or delay) are likely to trigger chain reactions through segment correlations. Identifying these segments and implementing resource allocation bias and targeted optimization for them can significantly improve network operational efficiency and alleviate delays. Current key segment identification methods only consider the physical connection status between individual air route segments, ignoring the spatiotemporal correlation of traffic changes among segments. To address this issue, this paper proposes a key segment identification method based on a segment-related network. Firstly, redundant search paths are reduced through the pruning of low-impact indicators, and an improved FP-Growth algorithm is proposed to analyze segment correlations. On this basis, a segment-related network is constructed, where segments serve as nodes and correlations between segments serve as edges. This network integrates the changing relationship between segment flows and the physical connections between segments, thereby improving the accuracy of identification. Finally, in the segment-related network of the Guangdong-Hong Kong-Macao Multi-Airport Terminal Area, key segments such as Pingzhou-Conghua, Pingzhou-Gaoyao, and Zhuhai-Nanlang are identified using degree centrality, PageRank, eigenvector centrality, and global centrality analysis methods. Full article

An analysis of air traffic complexity in multi-airport terminal areas can assist air traffic controllers in accurately assessing the air traffic situation and collaboratively managing air traffic flows, thereby enhancing the utilization of airspace resources and reducing flight delays. This paper proposes an air traffic complexity analysis method for multi-airport terminal areas based on a route segment–flight state interdependent network. The interdependent network model consists of an upper-layer flight state network, a lower-layer route segment network, and inter-layer coupling edges. The upper-layer network is constructed with aircraft as nodes and flight conflicts between aircraft as edges. The lower-layer network uses route segments as nodes and the connectivity between route segments as edges. The inter-layer coupling edges are determined by evaluating the relationship between aircraft and route segments—if an aircraft is on a specific route segment, a coupling edge exists between the corresponding aircraft node and route segment node. Based on this model, node-level complexity metrics are established to analyze the importance and complexity of individual route segments. Additionally, network-level complexity metrics are introduced to assess the overall air traffic complexity in multi-airport terminal areas. Finally, the method proposed in this paper is validated using flight scenarios in the Guangdong–Hong Kong–Macao Greater Bay Area. By comparing and analyzing the results with the actual situation, it is shown that the proposed method can accurately assess the air traffic complexity in multi-airport terminal areas. Full article

Terminal Aerodrome Forecasts (TAFs) and long TAFs are issued by forecasters in the Hellenic National Meteorological Service for the upcoming 9 or 24 h respectively, for all airports to aid in flight planning. The most important predicted parameters are wind speed and direction, weather phenomena, and visibility. A verification procedure comparing TAFs to Meteorological Aerodrome Reports (METARs) can be helpful for improving the skills of forecasters. To this end, software was developed to read the raw format structure of TAFs and METARs and compare them. The wind speed and direction for each forecast hour are verified according to thresholds specified by the International Civil Aviation Organization (ICAO), and a summary is produced, showing correct, overestimated, and underestimated percentages. A weather phenomenon, such as rain (RA) or thunderstorm (TSRA), is usually given inside a probability time window in a TAF (e.g., PROB40 TEMPO RA). In such a case, the occurrence or absence of the phenomenon and its frequency inside the time window are considered when determining the forecaster’s skill (correct, false alarm, or miss), evaluated using categorical indices such as POD, ETS, and FAR over a number of TAFs. A similar procedure is carried out for visibility range intervals. In this study, verification was performed for a test period of January 2023 for 14 Greek airports. Results indicate generally good performance in predicting wind speed and direction, and also demonstrate the TAFs accuracy in detecting phenomena like rain, although with a notable tendency for false alarms. A systematic tendency to underestimate actual visibility, especially inside TEMPO statements is observed. Full article