Search Results (425)

In order to reduce aviation’s negative environmental effects and support international efforts to battle climate change, the International Civil Aviation Organization (ICAO) seeks to cut greenhouse gas (GHG) emissions. About 2–3% of the world’s CO₂ emissions come from aviation, and at high altitudes, the fraction of other GHGs that significantly alter the atmosphere is considerably greater. In this study, hourly wind speed data at 100 m height from ECMWF’s fifth-generation reanalysis (ERA-5) were used over a period of 40 years (1985–2025). Hourly assessments of wind speeds at 40 m and 80 m heights are conducted in ERA-5, with biases at specific ground locations rectified via the Global Wind Atlas (GWA). This research estimates and analyzes many factors, including Weibull statistical parameters, daily and monthly wind speed variations, cumulative distribution function (CDF), and atmospheric turbulence intensity. The energy generation from several wind turbine types at different elevations was assessed. The findings indicate that the examined location revealed fair potential for the construction of large-capacity wind energy units at heights equal to or above 80 m. Turbines that are less than 50 m tall are spread out at least 10 km around the airport runway. While turbines that are less than 150 m tall are spread out at least 15 km away from the airport runway. Full article

Surface congestion and taxiing delays at high-density airports increasingly constrain aviation sustainability, as ground-phase fuel consumption and emissions constitute a significant share of total airport emissions. Existing studies typically decouple air traffic flow management from ground resource scheduling, hindering coordinated optimization of punctuality, environmental benefits, and resource utilization. This paper proposes a multi-objective optimization method for runway-taxiway systems oriented toward air–ground collaborative decision-making, integrating Calculated Take-Off Time (CTOT) compliance constraints. A tri-objective mixed-integer programming model is formulated to minimize CTOT deviation, total taxiing time, and runway workload imbalance. A hybrid intelligent algorithm, SSA-SCA-NSGA-II, is designed with a bidirectional elite feedback mechanism to address this NP-hard problem. Validation uses real operational data of 58 departure flights during a peak period at Beijing Daxing International Airport. The results demonstrate that the proposed method achieves effective trade-offs on the Pareto front: CTOT compliance rate increased from 77.6% to 89.7–96.6%; total taxiing time decreased from 692 min to 551–635 min; and dual-runway utilization imbalance declined from 5.2% to 1.7–3.8%. These improvements translate into quantifiable sustainability gains: fuel consumption is reduced by 1425–3525 kg and CO₂ emissions by 4503–11,139 kg per peak hour, alongside a 19-percentage point improvement in punctuality that lowers passenger delay costs and reduces controller coordination workload. By simultaneously advancing environmental sustainability (carbon footprint reduction), economic sustainability (fuel and operational cost savings), and social sustainability (service punctuality and labor efficiency), the framework provides a measurable, monitorable, and policy-relevant decision-support tool for green airport surface operations aligned with sustainable development goals (SDGs). Full article

A significant low-level wind shear event that occurred at Xining Caojiabu Airport on 10 April 2019 was comprehensively analyzed. The analysis utilized data from the airport’s ground automatic weather observation system (AWOS), lidar detection data, ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), and ETOPO2v2 topographic data from the National Oceanic and Atmospheric Administration (NOAA). The analysis focused on the evolution of meteorological elements during the wind shear, lidar characteristics, large-scale environmental features, and the main influencing systems. The results indicate that this was a typical “easterly backflow” low-level wind shear event, representing a special type of cold-frontal low-level wind shear, with the wind shear occurring in the prefrontal area as the cold front approached the airport. During the passage of the wind shear, the AWOS stations at Runways 29 and 11 sequentially recorded pressure increases and temperature decreases, reflecting the gradual intrusion of cold air from east to west into the airport. Lidar Plan Position Indicator (PPI), Range-Height Indicator (RHI), and Doppler Beam Swinging (DBS) modes revealed that the wind shear appeared as convergence between southeast and northwest winds, with an impact on the airport that moved from east to west and from bottom to top, belonging to a meso-γ-scale system. The evolution of the sea-level pressure field, pressure-change field, frontogenesis function, and temperature advection indicated that cold air first moved eastward along the Hexi Corridor and then poured back into the Huangshui River Valley through the topographic gap at the eastern end of the Qilian Mountains. The easterly wind converged with the westerly wind, and the topographic funneling effect strengthened the easterly backflow and promoted its westward advance, leading to the occurrence of low-level wind shear. The large-scale influencing systems of this event included a transverse trough over Mongolia at 500 hPa, an upper-level frontal zone, an upper-level jet stream, and a surface cold front. The favorable conditions for the formation of this “easterly backflow” low-level wind shear were the strengthening of baroclinicity in the upper-level frontal zone, intensified cold advection, momentum downward transport induced by the upper-level jet and ageostrophic secondary circulation, and the easterly backflow and wind speed enhancement caused by the special topography. Full article

The quality of meteorological data from a certain type of commercial aircraft flying between Hong Kong and Shanghai is investigated in this study with a special focus on wind-related parameters, including the horizontal wind speed, horizontal wind direction, and eddy dissipation rate (EDR). The novelty of the study is the analysis of flight data on a new route between Hong Kong and Shanghai. The method for calculating the EDR from Quick Access Recorder (QAR) data of the studied aircraft type is first described. Then, we analyze seven flights operating between Hong Kong and Shanghai in 2025, when Hong Kong was affected by two typhoons, Wipha and Ragasa. Both low-level and enroute wind data are considered. The quality of QAR-based wind data is established through comparison with (a) QAR data from other airline flights separated by 10 min and by one runway from the studied aircraft; (b) headwind and EDR observations from Doppler Light Detection and Ranging (LIDAR) systems at Hong Kong International Airport (HKIA); and (c) reanalysis data of a global numerical weather prediction (NWP) model for the enroute phase of the studied aircraft type. The QAR-based wind data is found to have sufficient quality for the study of low-level windshear and turbulence as well as meteorological applications such as upper-air wind monitoring and data assimilation into NWP models. The wind data collected in the enroute phase is studied further by considering an extended period of July and September 2025 with 151 sets of valid QAR data. The horizontal wind speed and wind direction from the QAR are in general agreement with the model reanalysis data, noting the different nature of the matched data (e.g., averaging period, model grid resolution). Full article

Trajectory optimization during the terminal area energy management (TAEM) phase is pivotal for achieving accurate runway alignment and enhancing landing safety in autonomous aircraft operations. In the presence of initial state uncertainties in TAEM phase, conventional pseudo-spectral methods still suffer from robustness limitations and exhibit a strong dependence on the quality of the initial guess. Therefore, this paper proposes the composite African vulture optimization algorithm (CAVOA), a meta-heuristic framework designed to automate trajectory optimization. An in-depth examination of the heading alignment cone (HAC) trajectory model enables effective heading adjustments prior to landing, augmented by a tailored dynamic pressure profile to ensure safe touchdown velocities. By incorporating dynamic opposition learning, intelligent boundary processing, and composite exploration, CAVOA enhances global search efficiency. These enhancements are substantiated through comparisons with benchmark function optimization, Wilcoxon rank sum tests, and convergence analysis. Numerical simulations validate that CAVOA reliably directs autonomous aircraft to predefined touchdown states, demonstrating superior performance in complex aerial environments. Full article

Decommissioned airfields are increasingly recognized as strategic sites for ecological regeneration, climate adaptation, and the creation of new public spaces. However, research on their transformation has predominantly focused on the environmental performance of Nature-based Solutions (NBS), often overlooking the role of inherited spatial morphology in structuring regeneration processes and outcomes. This paper proposes an AI-assisted, morphology-based proto-ontological framework for analyzing and designing post-airfield architecture. The framework was developed through the inductive and comparative analysis of a corpus of 32 urban post-airfield regeneration projects, from which recurrent inherited morphologies, transformation actions, spatial devices, and NBS were identified and structured into a relational sequence. The framework was then applied to two contrasting case studies: Maurice Rose Airfield Park (Frankfurt) and Xuhui Runway Park (Shanghai); these were selected for their different transformation logics. The results show that similar airfield morphologies can generate markedly different climatic, ecological, social, and memory-related outcomes depending on how they are transformed and linked to NBS. The study demonstrates that inherited airfield morphologies are not passive remnants but operative spatial structures, and that NBS should be understood as spatially embedded and form-generating design components. The proposed proto-ontology offers a transferable analytical model and a basis for future computational and generative design applications. Full article

Runway systems serve as the critical interface between airports and terminal airspace, and their efficient operation is essential for balancing air traffic demand and airport capacity. With the continuous growth of air traffic, intelligent runway demand and capacity management has become increasingly important for mitigating congestion and delays. This paper presents a comprehensive review of runway capacity–demand management from both supply-side and demand-side perspectives. On the supply side, runway configuration selection is reviewed, including runway configuration capacity envelopes, influencing factors, and existing optimization methodologies, such as prescriptive models, descriptive models, and reinforcement learning approaches. On the demand side, flight runway sequencing for arrivals, departures, and integrated arrival–departure operations is systematically analyzed. Problem analogies, operational characteristics, optimization objectives, and solution algorithms are discussed in detail. A critical comparison of existing methodologies is conducted from the perspectives of solution quality, real-time capability, human interpretability, technology readiness, trust requirements, and human–AI collaboration. Finally, future research directions are identified, including integrated runway management, multi-airport coordination, uncertainty-aware optimization, human–AI decision support, AI-enabled runway management, and integrated manned–unmanned operations. The review provides a reference for researchers, airport operators, air navigation service providers, and decision-support system developers seeking to improve runway operational efficiency and safety. Full article

The performance of the aircraft anti-skid braking system is critical to the ground operational safety of an aircraft. Conventional Pressure Bias Modulation (PBM) can suffer from deep skidding under low runway friction coefficients or low aircraft speeds. To address these issues, a composite control strategy based on Gaussian Quantum Particle Swarm Optimization (GQPSO) is proposed. This strategy employs the GQPSO algorithm for offline Proportional–Integral–Derivative (PID) parameter optimization, followed by real-time adaptive scheduling through a lookup table to accommodate varying speed domains and runway conditions. Simultaneously, by integrating the main-wheel dynamics model and friction characteristics, a runway identification function based on a Back Propagation Neural Network (BPNN) is designed to provide runway status information. The stability of the controller is verified via phase-plane analysis and Monte Carlo simulation. Subsequently, comparative Hardware-in-the-Loop (HIL) tests are conducted among PBM, PSO-PID, and the proposed GQPSO-PID controller under various runway conditions. The experimental results demonstrate that this composite controller can adapt to different speed domains and runway conditions, stably track the target slip ratio, effectively suppress skidding, and significantly improve braking efficiency, as well as exhibiting excellent robustness and control performance. Full article

Multi-runway sequencing of unmanned aerial vehicles (UAVs) at temporary disaster relief aerodromes presents a priority-heterogeneous scheduling problem under class-asymmetric wake turbulence constraints. We formulate this as a priority-weighted Markov decision process with a deliberately minimalist reward—per-step class weights for completed landings, with no shaping or hand-crafted safety logic—and extend it with per-UAV operational deadlines (encoding en-route endurance consumption) and per-runway queue capacity constraints that produce a non-trivial action mask. We train a Proximal Policy Optimisation (PPO) agent and benchmark it against six baselines spanning deterministic optimisation (Joint-LA-1), stochastic lookahead (Stochastic-LA), and online tree search (MCTS). Across 100 paired evaluation episodes, PPO matches the operational standard Priority-FCFS within 2.7% (p = 0.124, not significant); Joint-LA-1, the strongest non-learned baseline, outperforms PPO by 3.2% (p = 0.043). Despite near-identical aggregate throughput, PPO autonomously develops a runway specialisation pattern—concentrating 60% of high-priority landings on a single strip while routing 93% of emergency arrivals to the remaining strips—that emerges entirely from the reward signal. Under looser deadlines, the PPO–PFCFS gap narrows to −0.5%, and wake symmetry ablation reveals that PPO outperforms Priority-FCFS by 46.5% when the asymmetric wake structure is removed. These results demonstrate that priority-aware capacity reservation can emerge without embedded domain knowledge, and that simple heuristics are near-optimal under tight operational constraints—a finding with direct implications for autonomous scheduling in disaster relief aviation. Full article

Currently, improving runway utilization under operational safety constraints has become a critical concern for small and medium airports. Existing research focuses primarily on landing-phase runway occupation time, while predictive studies on the takeoff phase remain limited. Analysis of 1749 Quick Access Recorder (QAR) records from ten airports reveals that departure runway occupation time is strongly correlated with ground speed at liftoff (0.72) and airport elevation (0.67) but weakly correlated with aircraft weight and meteorological conditions, providing guidance for feature engineering. To address the prediction of departure runway occupation time, this study proposes a TCN-FEP hybrid model. The model employs an enhanced Temporal Convolutional Network (TCN) module with multi-scale convolutions (kernel sizes 3, 5, 7) and dilated convolutions (rates 2, 4, 8) to capture multi-scale feature interactions, alongside a Feature Enhancement Projection (FEP) module that maps local features into a high-dimensional latent space for implicit relationship mining and global information integration. Experimental results demonstrate that the proposed TCN-FEP model achieves an MSE of 90.20, RMSE of 9.49, MAE of 5.84 s, MAPE of 3.80%, and R² of 0.97, outperforming Informer (MSE 117.95), Longformer (MSE 132.11), XGBoost (MSE 92.30), and LightGBM (MSE 91.45). Under 5% outlier injection, MSE increases by 7.9%, compared to 24.3% for LSTM and 18.4% for Informer. With 94% of prediction errors within ±5 s, the model’s accuracy may offer a useful reference for runway resource optimization at small and medium airports. Full article

High-velocity multi-projectile impacts from accidental external debris (e.g., uncontained engine debris or runway stones) on the liquid-filled fuel tanks of modern unmanned aerial vehicles (UAVs) induce complex Fluid–Structure Interaction (FSI) and Hydrodynamic Ram (HRAM) effects, resulting in highly complex dynamic response mechanisms. This study combines high-velocity impact tests with Three-Dimensional Digital Image Correlation (3D-DIC) technology and employs FSI finite element simulations based on the Structured Arbitrary Lagrangian–Eulerian (S-ALE) algorithm to thoroughly investigate the dynamic response mechanisms of liquid-filled containers penetrated by dual projectiles under different spatial spacings and temporal intervals. The results indicate that variations in the spatiotemporal parameters of dual projectiles significantly reconstruct the fluid load field: small spacing and short temporal intervals induce strong wave interference and superposition, generating an amplified composite loading effect that causes a sharp increase in target plate impulse and deformation energy. Conversely, small spacing and long temporal intervals trigger a significant “cavity shielding” phenomenon, causing the subsequent projectile to travel through the existing cavity, which massively suppresses the effective generation of its load and energy transfer. Furthermore, fluid displacement induced by cavity intersection generates secondary pressure waves; the petal hole evolution of the rear plate is dictated by the formation of plastic hinge lines, presenting four typical deformation modes—oblique cross, normal cross, asymmetric pentagon, and hexagon—depending on the degree of spatiotemporal coupling. This study reveals the laws governing the enhanced HRAM effect of dual projectiles, providing key theoretical support for the lightweight protection design and crashworthiness evaluation of long-endurance commercial UAV fuel tanks. Full article

This paper arises from an ARPA-E-sponsored project seeking design opportunities to retrofit existing aircraft with hybrid electric propulsion systems. Engineers typically configure aircraft to fly a given payload over a long range, which is subject to field performance constraints. In practice, operators fly transport aircraft (civilian and military) in a manner where dispatch consciously trades payload and/or range to enable safe operations to and from short runways. This work describes a simple yet novel analytical process suitable for inclusion in conceptual design or technology portfolio trade study evaluations to assess the impacts of weight-restricted dispatch upon usable payloads. We find that options that increase low-speed thrust may maintain or improve the useful payload even if it substantially increases aircraft fixed weight. Conversely, otherwise desirable technologies that decrease low-speed thrust may severely impact the useful payload of aircraft operating to and from short runways. Full article

Runway friction is a critical factor for aircraft operational safety, yet the role of adhesion in wet friction remains insufficiently understood, especially in areas where tyre rubber contaminates the surface. This study evaluated approximate adhesive contribution for representative common runway surfaces, using contact angle measurements and British pendulum tester friction tests. The results show that approximate adhesion influence varies strongly with surface type: negligible on cement concrete, 16% to 19% on rubber-contaminated asphalt, and up to 49% on roughened rubber. A linear correlation between friction and contact angle confirmed that wetting behaviour governs adhesion-driven friction. Friction tests at different temperatures also confirmed the adhesive nature of the temperature influence on friction. The analysis further indicates that material properties and greater effective surface area correlate with stronger adhesive contributions, explaining material-specific differences in friction performance. These findings may provide a conceptual basis for interpreting variability in continuous friction measurements and suggest the importance of considering adhesion effects in runway surface characterisation and maintenance systems. Full article

Runway microtexture is a key parameter governing pavement friction. In recent years, several microtexture assessment methods have been developed; however, understanding of microtexture evolution under operational conditions, as well as the effects of maintenance techniques, remains limited. In this study, a runway at an Australian airport was investigated using laser profilometry. Measurements were conducted across multiple transverse sections, including aircraft touchdown and mid-runway zones. Microtexture deterioration rates were evaluated based on the estimated number of tire–pavement contacts, and aggregate polishing was assessed at different locations. Measurements were also performed after rubber contamination removal and rejuvenation treatments. The results indicate that approximately 25% of total microtexture reduction can be attributed to surface polishing, with a lower contribution in touchdown zones due to the protective effect of rubber deposits. A non-linear degradation trend was observed in touchdown zones, where approximately 1100 tire contacts reduced average microtexture roughness from 18 μm to 11 μm. Rubber removal effectively restored microtexture close to its original levels across the runway width. A rejuvenation treatment with a covering of fine sand initially improved microtexture; however, rapid deterioration occurred due to loss of the sand coating. These findings improve the understanding of microtexture evolution under operational runway conditions, albeit only at a case study level, and support more effective runway maintenance planning and intervention strategies. Full article

This article discusses the anti-skid braking control mechanism of aircrafts. Aircrafts use a sliding-mode controller (SMC) to generate the desired braking torque on its wheels to stop while landing. Potential runway variations and load differences on the wheels are considered, affecting the friction force on each wheel. Variations in the friction force generate drag torque, causing aircrafts to drift away from the runway. In order to counteract the drift, we propose a supervisory consensus controller, which adjusts the braking torque of each wheel to achieve equal force on each wheel. We consider a wireless communication channel between the supervisory controller and each wheel’s brake controller in an attempt to reduce cabling. As wireless communication needs to deal with potential communication losses that affect the overall control performance, a new control model that can accommodate communication losses has been devised. The proposed model is evaluated, and we demonstrate how well the consensus controller works over a noisy channel. Simulation results demonstrate that the proposed consensus-based control significantly improves braking performance, reducing drag torque and achieving up to 15–20% reduction in landing distance under 25% packet loss compared to baseline approaches. Full article