Search Results (109)

Due to the limited endurance of UAVs, especially in scenarios involving large areas and dense target nodes, it is challenging for multiple UAVs to complete diverse tasks while ensuring timely execution. Toward this, we propose a cross-platform system consisting of an aircraft carrier (AC) and multiple UAVs, which makes unified task planning for included heterogeneous platforms to maximize the efficiency of the entire combat system. The carrier-based UAV swarm mission planning problem is formulated to minimize completion time and resource utilization, taking into account large-scale targets, multi-type tasks, and multi-obstacle environments. Since the problem is complex, we design a decoupled framework to simplify the solution by decomposing it into two levels: upper-level AC path planning and bottom-level multi-UAV cooperative mission planning. At the upper level, a drop point determination method and a discrete genetic algorithm incorporating improved A* (DGAIIA) are proposed to plan the AC’s path in the presence of no-fly zones and radar threats. At the bottom level, an improved differential evolution algorithm with a market mechanism (IDEMM) is proposed to minimize task completion time and maximize UAV utilization. Specifically, a dual-switching search strategy and a neighborhood-first buying-and-selling mechanism are developed to improve the search efficiency of the IDEMM. Simulation results validate the effectiveness of both the DGAIIA and IDEMM. An animation of the simulation results is available at simulation section. Full article

To meet the requirements of the high spatiotemporal three-dimensional (3D) airflow field within the glide path corridor during carrier-based aircraft/unmanned aerial vehicles (UAVs) landings, this paper proposes a prediction method for high spatiotemporal resolution 3D ship airwake along the glide path by integrating computational fluid dynamics (CFD), backpropagation (BP) neural network, and Doppler wind lidar (DWL). Firstly, taking the conceptual design aircraft carrier model as the research object, CFD numerical simulations of the ship airwake within the glide path region are carried out using the Poly-Hexcore grid and the detached eddy simulation (DES)/the Reynolds-averaged Navier–Stokes (RANS) turbulence models. Then, using the high spatial resolution ship airwake along the glide path obtained from steady RANS computations under different inflow conditions as a sample dataset, the BP neural network prediction models were trained and optimized. Along the ideal glide path within 200 m behind the stern, the correlation coefficients between the predicted results of the BP neural network and the headwind, crosswind, and vertical wind of the testing samples exceeded 0.95, 0.91, and 0.82, respectively. Finally, using the inflow speed and direction with high temporal resolution from the bow direction obtained by the shipborne DWL as input, the BP prediction models can achieve accurate prediction of the 3D ship airwake along the glide path with high spatiotemporal resolution (3 m, 3 Hz). Full article

Carrier-based aircraft recovery is a critical and challenging phase in maritime operations due to the turbulent airwake generated by aircraft carriers, which significantly increases the workload of flight control systems and pilots. This study investigates the airwake effects of an aircraft carrier under varying wind direction conditions. A high-fidelity mathematical model combining delayed detached-eddy simulation (DDES) with the overset grid method was developed to analyze key flow characteristics, including upwash, downwash, and lateral recirculation. The model ensures precise control of aircraft speed and trajectory during landing while maintaining numerical stability through rigorous mesh optimization. The results indicate that the minimum lift occurs in the downwash region aft of the deck, marking it as the most hazardous zone during landing. Aircraft above the deck are primarily influenced by ground effects, causing a sudden increase in lift that complicates arresting wire engagement. Additionally, the side force on the aircraft undergoes an abrupt reversal during the approach phase. The dual overset mesh technique effectively captures the coupled motion of the hull and aircraft, revealing higher turbulence intensity along the glideslope and a wider range of lift fluctuations compared to stationary hull conditions. These findings provide valuable insights for optimizing carrier-based aircraft recovery procedures, offering more realistic data for simulation training and enhancing pilot preparedness for airwake-induced disturbances. Full article

This study evaluates the feasibility and benefits of introducing battery-powered hybrid electric aircraft (HEA) into regional airline operations. Using 2019 U.S. domestic flight data, the ERJ175LR is selected as a representative aircraft, and several HEA variants are designed to match its mission profile under different battery technologies and power management strategies. These configurations are then tested across over 800 actual daily flight sequences flown by a regional airline. The results show that well-designed HEA can achieve 3–7% fuel savings compared to conventional aircraft, with several variants able to complete all scheduled missions without disrupting turnaround times. These findings suggest that HEA can be integrated into today’s airline operations, particularly for short-haul routes, without the need for major infrastructure or scheduling changes, and highlight opportunities for future co-optimization of aircraft design and operations. Full article

The scheduling of carrier-based aircraft departure operations is subject to stringent temporal, spatial, and resource constraints. Conventional approaches struggle to yield exact solutions or provide a comprehensive mathematical description of this complex, dynamic process. This study proposes a simulation-based optimization method, establishing a high-fidelity simulation model for aircraft departure scheduling. To address the coupled challenges of path planning under spatial constraints and station matching/sequencing under operational constraints, we developed (1) a deep reinforcement learning (DRL)-based path planning algorithm (AAE-SAC), and (2) an enhanced particle swarm optimization (PSO) algorithm (LTA-HPSO). This integrated two-stage framework, termed LTA-HPSO + AAE-SAC, facilitates efficient, collision-free departure scheduling optimization. Simulation experiments across varying sortie scales were conducted to validate the framework’s effectiveness and robustness. Notably, for a complex scenario involving 24 aircraft with diverse priorities and stringent spatial constraints, LTA-HPSO + AAE-SAC achieved an average solution time of 185.19 s, reducing scheduling time by 26.18% and 49.54% compared to benchmark algorithms (PSO + Heuristic and PSO + SAC, respectively). The proposed LTA-HPSO + AAE-SAC framework significantly enhances the quality and robustness of carrier-based aircraft departure scheduling. Full article

The operational integrity of the BeiDou-3 Navigation Satellite System (BDS-3) has been significantly challenged by electromagnetic interference, particularly from Distance Measuring Equipment (DME) ground beacons to the newly implemented B2a signal, since its full operational deployment in 2020. This study developed a comprehensive interference evaluation model based on receiver signal processing principles to quantify the degradation of B2a signal reception performance under DME interference scenarios. Leveraging empirical data from the DME beacon network in the Chinese mainland, we systematically analyzed the interference effects through an effective carrier-to-noise ratio ($C/N_0$), signal detection probability, carrier tracking accuracy, and demodulation bit error rate (BER). The results demonstrate that the effective $C/N_0$ of the B2a signal degrades by up to 3.25 dB, the detection probability decreases by 33%, and the carrier tracking errors and BER increase by 2.57° and 5.1%, respectively, in worst-case interference scenarios. Furthermore, significant spatial correlation was observed between the interference hotspots and regions of high aircraft density. DME interference adversely affected the accuracy, availability, continuity, and integrity of the airborne BeiDou navigation system, thereby compromising civil aviation flight safety. These findings establish a scientific foundation for developing Minimum Operational Performance Standards for B2a signal receivers and for strategically optimizing DME beacon deployment throughout the Chinese mainland. Full article

This paper proposes a multi-granularity retrieval algorithm based on an unsupervised image augmentation network. The algorithm designs a feature extraction method (AugODNet_BRA) rooted in image augmentation, which efficiently captures high-level semantic features of images with few samples, small targets, and weak features through unsupervised learning. The Omni-Dimensional Dynamic Convolution module and Bi-Level Routing Attention mechanism are introduced to enhance the model’s adaptability to complex scenes and variable features, thereby improving its capability to capture details of small targets. The Omni-Dimensional Dynamic Convolution module flexibly adjusts the dimensions of convolution kernels to accommodate small targets of varying sizes and shapes. At the same time, the Bi-Level Routing Attention mechanism adaptively focuses on key regions, boosting the model’s discriminative ability for targets in complex backgrounds. The optimized loss function further enhances the robustness and distinctiveness of features, improving retrieval accuracy. The experimental results demonstrate that the proposed method outperforms baseline algorithms on the public dataset CUB-200-2011 and exhibits great potential for application and practical value in scenarios such as carrier-based aircraft tail hook recognition. Full article

Electric aviation is the future development direction of aviation industry technology. Electric vertical take-off and landing aircraft(eVTOL) is an important carrier of electric aviation, whose technology research and development, processing and manufacturing, airworthiness certification and industrialization boom have been set off around the world. The electric propulsion technology has achieved rapid development as the key technology of eVTOL. Aiming at the demand for high torque density and high reliability of electric propulsion system, the paper analyzed the technical indexes of electric motor products of domestic and foreign benchmark enterprises. The key technologies such as motor integration, new electromagnetic topology, lightweight structure design, and high efficiency cooling is studied. It is pointed out that in order to pursue the high torque density and fault-tolerance performance, the integrated precise modeling of motor and controller, advanced materials and manufacturing technology are the development trend of the electric propulsion technology. The breakthrough of eVTOL electric propulsion technology can accelerate the commercial operation of civil eVTOL and promote the development of new quality productive forces. Full article

This study is situated against the background of shortages in the agricultural labor force and shortages of cultivated land. In order to improve the intelligence level and operational efficiency of agricultural machinery and solve the problems of difficulties in recognizing navigation lines and a lack of real-time performance of transplanters in the crop-free ridge environment, we propose a crop-free-ridge navigation line recognition method based on an improved YOLOv8 segmentation algorithm. First, this method reduces the parameters and computational complexity of the model by replacing the YOLOv8 backbone network with MobileNetV4 and the feature extraction module C2f with ShuffleNetV2, thereby improving the real-time segmentation of crop-free ridges. Second, we use the least-squares method to fit the obtained point set to accurately obtain navigation lines. Finally, the method is applied to testing and analyzing the field experimental ridges. The results showed that the average precision of the improved neural network model using this method was 90.4%, with a Params of 1.8 M, a FLOPs of 8.8 G, and an FPS of 49.5. The results indicate that the model maintains high accuracy while significantly outperforming Mask-RCNN, YOLACT++, YOLOv8, and YOLO11 in terms of computational speed. The detection frame rate increased significantly, improving the real-time performance of detection. This method uses the least-squares method to fit the 55% ridge contour feature points under the picture, and the fitting navigation line shows no large deviation compared with the image ridge centerline; the result is better than that of the RANSAC fitting method. The research results indicate that this method significantly reduces the size of the model parameters and improves the recognition speed, providing a more efficient solution for the autonomous navigation of intelligent carrier aircraft. Full article

To address the key challenges of poor real-time interaction, insufficient integration of operating rules, and limited virtual–physical synergy in current carrier-based aircraft scheduling simulations, this study proposes an immersive digital twin platform that integrates a two-layer genetic algorithm (GA) with hardware-in-the-loop (HIL) semi-physical validation. The platform architecture combines high-fidelity 3D visualization-based modeling (of aircraft, carrier deck, and auxiliary equipment) with real-time data exchange via TCP/IP, establishing a collaborative virtual–physical simulation environment. Three key innovations are presented: (1) a two-tier genetic algorithm (GA)-based scheduling model is proposed to coordinate global planning and dynamic execution optimization for carrier-based aircraft operations; (2) a systematic constraint integration framework incorporating aircraft taxiing dynamics, deck spatial constraints, and safety clearance requirements into the scheduling system, significantly enhancing tactical feasibility compared to conventional approaches that oversimplify multidimensional operational rules; (3) an integrated virtual–physical simulation architecture merging virtual reality interaction with HIL verification, establishing a collaborative digital twin–physical device platform for immersive visualization of full-process operations and dynamic spatiotemporal evolution characterization. Experimental results indicate that this work bridges the gap between theoretical scheduling algorithms and practical naval aviation requirements, offering a standardized testing platform for intelligent carrier-based aircraft operations. Full article

Hybrid electric propulsion architectures offer a promising solution for reducing fuel consumption and emissions in aviation. However, the introduction of dual-energy carriers adds complexity to preliminary aircraft design, particularly in terms of power distribution, failure analysis, and compliance with operational regulations. Key challenges include defining failure cases, which requires refining conventional constraint analysis for hybrid electric aircraft and integrating failure scenarios into mission analysis to meet certification specifications and regulatory requirements. This study presents a unified methodology that combines an analytical constraint analysis with a higher-fidelity numerical design loop implemented in the SUAVE framework to address these challenges. Key innovations include the introduction of new parameters—such as the supplied shaft power ratio—and the ability to assess failure scenarios through the definition of the critical loss of thrust, thereby extending the analysis beyond conventional one-engine-inoperative cases. The methodology also integrates an energy management strategy that dynamically allocates power between the primary and secondary energy carriers, thereby capturing the interaction between energy (mission analysis) and power (constraint analysis) requirements. The results from both the constraint and mission analyses, including en-route alternate aerodrome scenarios, demonstrate that employing batteries as the secondary energy carrier can reduce the oversizing of primary power sources. However, their effective utilization is highly sensitive and may necessitate adjustments in energy sizing. These findings underscore the importance of incorporating dual-energy carrier considerations early in the design process and highlight the impact of critical loss of thrust conditions on hybrid electric aircraft configurations, ultimately benefiting researchers and engineers. Full article

Aviation is one of the most important industries in the current global scenario, but it has a significant impact on climate change due to the large quantities of carbon dioxide emitted daily from the use of fossil kerosene-based fuels (jet fuels). Although technological advancements in aircraft design have enhanced efficiency and reduced emissions over the years, the rapid growth of the aviation industry presents challenges in meeting the environmental targets outlined in the “Flightpath 2050” report. This highlights the urgent need for effective decarbonisation strategies. Hydrogen propulsion, via fuel cells or combustion, offers a promising solution, with the combustion route currently being more practical for a wider range of aircraft due to the limited power density of fuel cells. In this context, this paper designs and models a nitrogen–hydrogen heat exchanger architecture for use in an innovative hydrogen-propelled aircraft fuel system, where the layout was recently proposed by the same authors to advance sustainable aviation. This system stores hydrogen in liquid form and injects it into the combustion chamber as a gas, making the cryogenic heat exchanger essential for its operation. In particular, the heat exchanger enables the vaporisation and superheating of liquid hydrogen by recovering heat from turbine exhaust gases and utilising nitrogen as a carrier fluid. A pipe-in-pipe design is employed for this purpose, which, to the authors’ knowledge, is not yet available on the market. Specifically, the paper first introduces the proposed heat exchanger architecture, then evaluates its feasibility with a detailed thermodynamic model, and finally presents the calculation results. By addressing challenges in hydrogen storage and usage, this work contributes to advancing sustainable aviation technologies and reducing the environmental footprint of air travel. Full article

Flight tests and wind tunnel experiments face difficulties in investigating the impact of aircraft carrier air-wake on the landing process. Meanwhile, numerical methods generally exhibit low overall computational efficiency in solving such problems. To address the computational challenges posed by the disparate spatiotemporal scales of the ship air-wake and aircraft motion, a domain precursor inflow method is developed to efficiently generate unsteady inflow boundary conditions from precomputed full-domain air-wake simulations. This study investigates the aerodynamic variability of carrier-based aircraft during landing through the turbulent air-wake generated by an aircraft carrier, employing a hybrid RANS-LES methodology on dynamic unstructured overset grids. The numerical framework integrates a delayed detached-eddy simulation (DDES) model with a parallel dynamic overset grid approach, enabling high-fidelity simulations of coupled aircraft carrier interactions. Validation confirms the accuracy of the precursor inflow method in reproducing air-wake characteristics and aerodynamic loads compared to full-domain simulations. Parametric analyses of 15 distinct landing trajectories reveal significant aerodynamic variability, particularly within 250 m of the carrier, where interactions with island-generated vortices induce fluctuations in lift (up to 25%), drag (18%), and pitching moments (30%). Ground effects near the deck further amplify load variations, while lateral deviations in landing paths generate asymmetric forces and moments. The proposed methodology demonstrates computational efficiency for multi-scenario analysis, providing critical insights into aerodynamic uncertainties during carrier operations. Full article

Today’s airport passenger terminals are required to be planned and designed to ensure flexibility for future adjustments at minimal cost, but also to respond to changes in demand and/or needs of passengers, airlines, and aircraft. To achieve these goals for airports and their operators, planning must be flexible and balanced. Recent data show that the airline business model of low-cost carriers continues to grow, especially after the pandemic. The analysis of the passenger traffic demand and shares of airline business models against the capacity of the existing airport terminal facilities can indicate whether certain adjustments are needed to meet the future conditions. In this research, forecasting of traffic demand and shares of airline business models was made. The forecasting tools of Python and MS Excel were used. Based on traffic demand forecasts and the dominant airline business model, guidelines for future airport terminal planning were proposed for the case-study airport. An example of the adjustment of airport terminal facilities at Pula Airport passenger terminal is provided using AutoCAD, according to forecasted traffic demand and the dominant share of low-cost carriers. Full article

Carrier-based aircraft (CBA) landing involves complex system engineering characterized by strong non-linearity, significant coupling and susceptibility to environmental disturbances. To address uncertainties in parameters, carrier air-wake disturbances and other challenges inherent to CBA landing, this paper presents a longitudinal automatic landing system based on adaptive fuzzy sliding-mode control. This system was developed to improve control accuracy and stability during the critical landing phase. Furthermore, this paper analyzes components of carrier air-wake and motion conditions for ideal landing points on the carrier deck, and designs a sliding-mode surface with the integral term. An adaptive fuzzy sliding-mode controller based on equivalent and switching controls is constructed, which exhibits stability under the Lyapunov stability condition. Moreover, a Monte Carlo simulation method is employed to verify the simulation of the automatic landing control system. Owing to its impressive dynamic performance and robustness, the proposed control method can track expected values with high accuracy in a complex environment, thereby satisfying the CBA landing requirements. Full article