Search Results (1,042)

Providing regulation-compliant, high-fidelity training in aircraft maintenance remains challenging for institutions of education, where access to real aircraft, specialist tools, and operational environments is limited by cost, safety, and resource factors. This paper presents the design, in-house development, and pilot deployment of a virtual reality (VR) training system for an operationally critical maintenance procedure—Airbus A320 nose landing gear (NLG) wheel removal, strictly following the official Airbus Aircraft Maintenance Manual (AMM). Managed by an Agile-based methodology, the application, programmed with the Unity engine, uses full-size 3D CAD models and domain-expert input iteratively for quality-assured and rapid deployment. The system was piloted with aeronautical engineering students at the Vietnam Aviation Academy (VAA), achieving significant engagement and perceived gains for procedure knowledge and skill development. Positive comments emphasized the realistic, interactive, and repeatable quality of the simulation. Usability issues related to controller handling, cybersickness, and the absence of haptic feedback, however, suggest opportunities for refinement. This paper reports an early published case study of VR use in commercial aircraft maintenance training that is practically replicable and scalable, and developed in alignment with applicable civil aviation procedural requirements. It suggests that such a high-fidelity VR training platform can provide an accessible solution for aviation stakeholders to help bridge classroom training and real-world application in safety-critical training contexts. Full article

Severe and unpredictable wind conditions significantly disrupt flight safety, mission planning, and scheduling. Traditional wind forecasting methods rely on low-resolution mesoscale models or resource-intensive instrumentation. This study evaluates the accuracy of 40 m Large-Eddy Simulations (LESs), nested within a mesoscale framework, to better resolve hazardous wind phenomena over GrandSKY, North Dakota, the first large-scale commercial Uncrewed Aircraft System (UAS) test park in the United States, serving as a hub for UAS innovation and Beyond Visual Line of Sight operations. Using low-altitude airborne observations from Meteodrone flights, satellite data, and ground-based measurements, we assess the model’s accuracy in predicting wind speed and direction during both summer and winter. Results demonstrate that the 40 m LES provides improved predictions of wind gust variability compared to the 1 km forecast, and the impact on flight safety is quantified. The LES also reveals notable discrepancies in UAS flyability predictions, which result in up to a 17% reduction in operational windows during the summer. This study’s novelty lies in using a 40 m resolution LES nested within a 1 km WRF simulation, combined with multi-source observations, to resolve low-altitude turbulence and quantify its impact on UAS operations. A 10–18% correction factor can be applied to TKE (or derived wind variability) in coarser WRF runs to better estimate maximum wind speeds without LES. The findings highlight the potential of high-resolution LES modeling to support reliable UAS operations in weather-sensitive environments, laying the groundwork for broader integration of advanced simulation techniques in national airspace management systems. Full article

Aircraft emergency hydraulic pumps are safety-critical units whose intermittent operation complicates condition assessment and reduces the diagnostic value of conventional bulk physicochemical oil properties. This study evaluates the applicability of tribotechnical oil analysis for monitoring degradation of the NP-27T emergency hydraulic pump under controlled bench conditions. Four NP-27T units were tested on a dedicated hydraulic bench, and oil samples were collected at defined intervals during operation and after test completion. The diagnostic methodology combined elemental spectrometry (ICP-OES), particle counting interpreted with reference to ISO 4406, and analytical ferrography. The results showed that flow performance deterioration was accompanied by measurable changes in oil-borne wear indicators, although the sensitivity of the individual diagnostic channels varied among the tested units. In several cases, the coarse particle fraction (>15 μm) exhibited the clearest response to degradation, while Fe and Cu concentrations provided useful but not uniformly monotonic trends across all pumps. Using a pragmatic early warning criterion based on the first exceedance of 100 particles/mL in the >15 μm fraction, the coarse particle signal provided lead times of approximately 13–345 min before the flow-based rejection limit was reached in the four tested units. Ferrographic analysis identified cutting and fatigue debris, together with larger wear particles, in units approaching or reaching the flow-based rejection limit. Overall, the findings demonstrate that the combined use of elemental analysis, particle counting, and ferrography provides a practical multi-indicator framework for relating oil-diagnostic signals to functional degradation of the NP-27T hydrogenerator. Under the present bench conditions, flow proved to be a more sensitive degradation indicator than pressure. The proposed approach therefore represents a useful complementary tool for maintenance decision-making and for integration with vibration-based condition monitoring of aircraft hydraulic systems. Full article

Surface protection and functional modification of aircraft-certified aluminum alloys are essential for corrosion resistance, durability, and long-term airworthiness. At the same time, increasingly restrictive environmental regulations motivate the development of alternatives to legacy wet-chemical surface treatments. This study presents an integrated assessment of ultrafast femtosecond laser surface texturing as a surface functionalization approach for Aluminum 6061 alloys within an aerospace manufacturing and sustainability context. Ultrashort-pulse laser processing enables controlled micro- and nano-scale surface topographical modification with limited thermal impact, allowing adjustment of wettability and surface functionality while preserving bulk material integrity. As a dry and contactless process, femtosecond laser treatment eliminates the use of hazardous chemicals, reduces consumable inputs, and generates minimal secondary waste. A streamlined cradle-to-gate life cycle assessment conducted in accordance with ISO 14040/14044 indicates a lower global-warming potential per functional unit compared with conventional surface treatments, including anodization, plasma-assisted coatings, and organic coating systems. Complementary qualitative analyses addressing environmental health and safety, supply-chain risk, and ESG alignment indicate potential advantages related to occupational safety, regulatory compliance, waste management, and end-of-life recyclability. The investigation is performed on planar Aluminum 6061 reference surfaces with a treated area of 25 mm², providing a controlled laboratory-scale basis for analyzing process behavior, functional surface modification, and associated environmental metrics. Within this defined scope, the results support further evaluation of femtosecond laser surface texturing as a surface engineering option for future aerospace manufacturing. Full article

The development of supersonic aircraft presents significant challenges in ensuring safety during early design stages, particularly for fuel tank systems exposed to extreme thermal and structural loads. Conventional document-based zonal safety analysis methods are limited in their ability to capture dynamic interactions between spatial subsystem configurations and functional system behavior during early conceptual design, leading to delayed hazard identification. This study proposes an integrated framework combining computer-aided design (CAD) and model-based systems engineering (MBSE) to support early-stage zonal hazard analysis. The framework links spatial subsystem modelling with functional system architecture to enable iterative hazard identification and mitigation. Applied to the SA-24 Phoenix conceptual supersonic aircraft, the approach identifies critical risks, including fuel vaporization, over-pressurization, and structural fatigue, and evaluates mitigation strategies such as thermal insulation and redundant venting. Functional hazard analysis and fault tree analysis are used to assess failure scenarios and ensure compliance with EASA CS-25 requirements. Results indicate an estimated reduction of up to 40% in risk priority number (RPN) values for key thermal hazard pathways and a 25% reduction in conceptual design iteration time compared with conventional approaches. The findings demonstrate that CAD–MBSE integration offers a scalable and efficient methodology for early hazard identification, contributing to safer and more reliable supersonic aircraft design. Full article

With the rapid development of electric Vertical Take-Off and Landing (eVTOL) aircraft for urban air mobility, ensuring safe operation in complex low-altitude environments remains a major challenge. In particular, interactions with non-cooperative airspace users introduce uncertainties that are difficult to fully handle with current autonomous systems. To better understand these risks, a Monte Carlo simulation framework is developed to model random encounters between an eVTOL and uncontrolled unmanned aerial vehicles. The results show a relatively low collision probability of approximately 0.18%. However, a large proportion of encounters fall within an intermediate separation range of 100–200 m, indicating a high-frequency conflict region that still requires continuous monitoring and decision-making. Based on these observations, Fault Tree Analysis (FTA) is further applied to evaluate system-level safety under different operational architectures, incorporating revised assumptions on human reliability and system interactions. The results suggest that the inclusion of human pilots can contribute to reducing the probability of catastrophic failure compared with fully autonomous configurations, particularly in uncertain and non-cooperative scenarios. These findings suggest that, although full autonomy is a long-term goal, current intelligent systems still face limitations in dealing with uncertain and non-cooperative scenarios in urban airspace. In such situations, human operators can provide additional situational awareness and flexible decision-making, improving overall system robustness. Overall, a phased transition toward full autonomy, starting from a human–machine collaborative approach, appears to be a practical path to ensure safety, support certification, and enable the deployment of eVTOL systems. Full article

The dynamical tropopause layer pressure (DTLP) represents a key interface characterizing upper-tropospheric stratification and atmospheric dynamical structure. Its spatial morphology and gradient variations directly influence jet stream distribution as well as the intensity and location of clear-air turbulence (CAT). Over the Tibetan Plateau, complex terrain and pronounced dynamical variability result in a significantly lower tropopause height and enhanced horizontal gradients during winter. Aircraft cruising altitudes frequently approach or intersect the tropopause layer in this region, making accurate and fine-scale characterization of DTLP structures critically important for aviation safety. A deep learning-based DTLP retrieval model (Att-ResUNet_DEM) is developed by integrating terrain constraints and an attention mechanism. Using MERRA-2 reanalysis data as supervisory labels, the model incorporates a squeeze-and-excitation (SE) attention mechanism within a residual encoder–decoder framework, while a digital elevation model (DEM) is introduced as an additional input channel and fused with satellite brightness temperature data to explicitly account for terrain effects. A random forest (RF) model is implemented as a baseline for comparison. Compared with the RF model, the Att-ResUNet_DEM reduces the MAE and RMSE by 13.20% and 9.19%, respectively, while increasing the correlation coefficient to 0.76. Over the primary aviation corridors of the Tibetan Plateau, the Att-ResUNet_DEM model achieves a correlation coefficient(R) of 0.87, with markedly reduced gradient dispersion. A representative CAT case further confirms the model’s ability to capture the overall DTLP morphology and gradient enhancement zones. Overall, by combining a regionalized modeling strategy with terrain constraints, this study systematically improves DTLP retrieval accuracy and gradient consistency over complex terrain, providing a new technical pathway for high-resolution tropopause monitoring and aviation operation support. Full article

Fuel vapor can be ignited by lightning through various means, particularly through hot spot formation on fuel tank skins. The wing fuel tank cover and its surrounding outer plates together form part of the aerodynamic shape of an aircraft. The lightning protection design of the fuel system, including wing fuel tank, is of great significance for ensuring the aircraft safety. Based on the Joule heating and implosion effect, the damage response of a composite fuel tank cover subjected to lightning strikes is analyzed in this paper. The adopted method combines electrical–thermal coupling with explicit dynamics analysis. Firstly, a finite element model of the fuel tank cover is established using electrical–thermal coupling elements, and the lightning current impact simulation is carried out under given electrical boundary conditions and thermal boundary conditions. On one hand, the ablation criterion is determined by the Joule heating effect and the sublimation temperature of materials. The thermal damage of composite materials subjected to transient high currents is obtained through transient thermal analysis. On the other hand, special implosion elements are selected according to the temperature distribution obtained from the electrical–thermal coupling analysis. The original composite material model in the implosion region needs to be replaced with a new material model described by the high-explosive material model and the JWL equation of state. The von Mises stress distribution and pressure distribution on the structure after implosion are discussed in detail. The results show that concave pits are formed near the implosion zone. Unlike the thermal damage morphology defined by the ablation criterion, the implosion effect makes the damage distribution deviate from the initial fiber direction of each layer. The implosion dynamic method reveals the internal damage and pit and bulge phenomenon around the lightning attachment area to a certain extent. Full article

Aircraft brake torque tubes are safety-critical components subject to combined torsional and thermal loading. As such, in aging aircraft, fatigue cracks frequently occur at the side walls of the grooves near the fillet transitions. This study presents a detailed analysis of the stress–strain state of the torque tube support section using a thermo-mechanically coupled finite element model (FEM) developed in ANSYS 2023 R2 Workbench. The model parameters are based on operational and design data provided by Röder Component Service Center Ltd. Unlike previous studies using idealized models, this approach integrates real-world non-destructive testing (NDT) evidence to identify critical areas with high stress concentrations. The model evaluates stress distributions under normal and emergency braking. Results show that the baseline 1 mm groove fillet exhibits pronounced stress peaks, correlating with observed crack initiation sites. Increasing the fillet radius to 3 mm reduces peak equivalent stress and improves the safety-factor distribution, significantly lowering crack-initiation propensity. These findings demonstrate that even minor local geometric refinements can enhance the structural robustness of torque-transmitting components. This FE–inspection integration framework offers a transferable method for reliability assessment and design improvement in aging aircraft fleets. Full article

Artificial Intelligence of Things (AIoT) technologies shifted the structure of production systems, enabling the development of more intelligent, connected and sustainable manufacturing environments. However, some industrial sectors, such as aerospace manufacturing industry, fell behind in the adoption of these new technologies, mainly because of the high safety standards, strict reliability requirements and long lifespan of aircraft components. Due to low production volumes and complex manufacturing processes, this sector relies heavily on weakly automated legacy machines and production systems. This article proposes a methodology to ease the integration of AIoT technologies for retrofitting legacy industrial equipment in the aeronautical domain in order to achieve the requirements of modern industrial production systems, enabling the development of more flexible, efficient and interconnected manufacturing environments. The proposed methodology is validated through a case study where the Smart Retrofitting of a legacy aeronautical industrial machine is carried out. The case study focuses on the development of an AIoT-based architecture to implement a predictive maintenance system through vibration and infrared thermography monitoring. A three layer architecture is proposed based on Edge/Fog/Cloud Computing paradigms. A hybrid communication architecture is used, combining wired technologies for critical real-time control tasks and wireless technologies for enhanced flexibility and scalability. The results demonstrate the viability of the proposed methodology for retrofitting legacy aircraft manufacturing systems. Full article

This work presents the numerical assessment of a civil aircraft horizontal tailplane (HTP) using a fully parametric structural model developed through the Ansys Parametric Design Language (APDL). The objective is to evaluate the structural integrity, efficiency, and dynamic behavior of the HTP under realistic operational conditions within the HERFUSE Clean Aviation framework. The study includes linear static analyses for load distribution and critical stress regions, modal analysis for dynamic response characterization, and linear buckling analyses to determine stability assessment. Safety margins are computed for representative load cases across spars, skins, and ribs. The workflow will be integrated and connected to Multidisciplinary Optimization (MDO) loops for higher-level design trade-offs. Full article

The pitot tube is the core sensor for aircraft to obtain external atmospheric data, and its failure has a very important impact on flight safety. However, as its structure and principle are relatively simple, all manufacturers have not adopted available monitoring methods for its health status due to the perspective of cost and complexity reduction. The pitot tube fault warning method is conducted in this paper with a fully connected neural network (FCNN) method based on the data collected by the pitot tube itself. By constructing and selecting parameters and extracting fault features from flight record data, a pitot tube fault warning model based on an FCNN is constructed. The effectiveness of the proposed method is verified through pitot tube fault warning experiments based on actual flight record data, which can provide technical reference for pitot tube fault warning during aircraft route operation in the future. Full article

Emergency locator transmitters (ELTs) are key safety systems for post-crash aircraft localization and search-and-rescue operations. In more electric aircraft (MEA), however, their design and operation are increasingly influenced by complex electrical architectures, tighter equipment integration, and more demanding electromagnetic environments. This paper presents a narrative literature review of ELT technology from a MEA-oriented perspective. A practice-oriented narrative approach is adopted, examining ELTs through a dual lens: the evolution of the search and rescue (SAR) ecosystem and the progressive electrification of aircraft systems. The review addresses ELT fundamentals, classifications, operating principles, and interaction with the Cospas-Sarsat infrastructure, and examines the transition from legacy analog beacons to modern 406 MHz digital systems incorporating GNSS positioning, MEOSAR capabilities, second-generation beacon functionalities, and distress tracking features. Particular attention is given to integration challenges in MEA platforms, including autonomous energy supply, battery endurance, power quality disturbances, electromagnetic compatibility, installation robustness, antenna survivability, and certification constraints. The analysis highlights that ELT performance in MEA depends not only on the beacon itself, but also on the coupled interaction among device design, installation conditions, and the electrical environment. Finally, the review outlines research priorities for next-generation ELTs, including improved survivability assessment, energy-aware architectures, integration strategies based on electromagnetic compatibility, and certification-ready solutions compatible with future aircraft platforms. Full article

The growing need to reduce aviation’s carbon footprint and reliance on fossil fuels has prompted the exploration of alternative propulsion technologies. Fuel cell (FC) systems offer a sustainable solution, generating only water vapor as a by-product. This paper presents a conceptual study, focusing on subsystem integration and safety aspects, for an 80-passenger, hydrogen-powered aircraft developed within the European Union (EU) co-funded NEWBORN (NExt generation high poWer fuel cells for airBORNe applications) Project. The designed configuration incorporates wing-mounted pods housing fuel cells, an electric motor, an inverter, a Thermal Management System (TMS), and Balance of Performance (BoP). This configuration is an effort towards environmentally friendly solutions, addressing climate change and paving the way towards greener aviation. Full article

Currently, airport fleet maintenance is characterized by diverse aircraft models, densely concurrent tasks, and tightly coupled professional skills. Traditional specialized personnel allocation models often lead to severe human resource redundancy and high costs, whereas fully generalized models struggle to meet the strict safety and professional qualification requirements for complex maintenance. Scientifically allocating maintenance personnel to balance support costs and operational efficiency under the constraints of broad task scopes, varied personnel qualifications, and strict time limits has become a critical issue for ensuring stable fleet operations and overall airport efficiency. To address this issue, this study proposes an optimization method for aircraft fleet maintenance support personnel allocation based on an Improved Genetic Algorithm. First, the practical challenges are analyzed and a modeling framework is established by systematically examining the implementation processes, professional skill requirements, and time-consuming characteristics of common maintenance tasks across various aircraft models. Next, the minimum required number of maintenance personnel is calculated as a baseline constraint based on the man-hour method. Subsequently, incorporating practical engineering constraints such as cross-type aircraft support, an Improved Genetic Algorithm integrating adaptive crossover/mutation operators and an elite local hill-climbing strategy is designed to solve the allocation optimization problem. Finally, case studies under four allocation schemes and multiple ablation experiments are performed to comprehensively verify the reliability and rationality of the proposed method. The experimental results demonstrate that the optimal personnel allocation scheme obtained with this method saves approximately 10% to 11% in total human resource costs, when compared to the traditional independent support model. This study provides a scientific decision-making basis and technical support for the refined allocation of human resources in the context of fleet maintenance. Full article