Aircraft Fleet Research Articles

A contribution to mitigate NOx and H2O emissions for a hydrogen-powered hypersonic vehicle

AbstractHypersonic transport fueled with liquid hydrogen (LH2-HST) is currently considered as long-term future technology of civil aviation to fly with speeds greater than Mach 5 at stratospheric altitudes of 25–38 km. In this paper, we present a comprehensive methodology to assess the emission mitigation potential (via NOx and H2O) of future LH2-HST through operational measures, considering realistic constraints such as the sonic boom carpet as well as tolerable g-forces acting on the passengers while flying with hypersonic speeds. Both NOx- and H2O-optimal 4D-trajectories are identified by a brute-force algorithm that varies the initial cruise altitude from 30 to 36 km. As case study, the Mach 8 passenger aircraft STRATOFLY-MR3, which was conceptually developed in the framework of the H2020 STRATOFLY project, is operated on a single route from Brussels (BRU) to Sydney (MYA). The findings are highlighted as relative changes regarding MR3's design flight altitude set at 32 km, respectively, 105 000 ft. As scientific contribution, 3D emission inventories are calculated and made publicly available for a world fleet of MR3 aircraft operated along the BRU-MYA route on both NOx- and H2O-optimal mission profiles in the year 2075.

Integration of Foundation Models and Federated Learning in AIoT-Based Aircraft Health Monitoring Systems

The study presents a comprehensive framework for integrating foundation models (FMs), federated learning (FL), and Artificial Intelligence of Things (AIoT) technologies to enhance aircraft health monitoring systems (AHMSs). The proposed architecture uses the strengths of both centralized and decentralized learning approaches, combining the broad knowledge capture of foundation models with the privacy-preserving and adaptive nature of federated learning. Through extensive simulations on a representative aircraft fleet, the integrated FM + FL approach demonstrated consistently superior performance compared to standalone implementations across multiple key metrics, including prediction accuracy, model size efficiency, and convergence speed. The framework establishes a robust digital twin ecosystem for real-time monitoring, predictive maintenance, and fleet-wide optimization. Comparative analysis reveals significant improvements in anomaly detection capabilities and reduced false alarm rates compared to traditional methods. The study conducts a systematic evaluation of the benefits and limitations of FM, FL, and integrated approaches in AHMS, examining their implications for system robustness, scalability, and security. Statistical analysis confirms that the integrated approach substantially enhances precision and recall in identifying potential failures while optimizing computational resources and training time. This paper outlines a detailed aviation ecosystem architecture integrating these advanced AI technologies across centralized processing, client, and communication domains. Future research directions are identified, focusing on improving model efficiency, ensuring generalization across diverse operational conditions, and addressing regulatory and ethical considerations.

The future of airport noise: a comprehensive analysis of population exposure at Dublin airport 2023 to 2030

There are conflicting trends in the impact of aircraft noise as increased air traffic is offset by advancements in low noise aircraft technology. This paper considers the case of Dublin Airport and projects the noise impact of operations over the timeline to 2030. The airport projects an (Average Annual Growth Rate) of 1.2 %, translating to an estimated rise in annual air traffic movements from over 212736 flights in 2023 to around 244635 flights in 2030. This estimated increase poses not only logistical challenges for airports but also an escalation in noise pollution in the surrounding areas. The most significant challenge in predicting future airport noise exposure lies in the shifts in aircraft fleet distribution and the adoption of technology in newer generations of aircraft. This paper evaluates the most likely combination of fleet distribution and technology uptake. In 2023, the noise footprint is projected to affect a population of approximately 105762 people with Lden ≥ 55 dB. By 2030, this exposure increases to 168267 people. The increase in air traffic numbers also leads to a notable increase in nighttime flights, bringing nighttime noise exposure Ln ≥ 50 dB from 127720 in 2023 to 189376 in 2030.

An approximate dynamic programming approach for solving aircraft fleet engine maintenance problem: Methodology and a case study

We consider a long-term engine maintenance planning problem for an aircraft fleet. The objective is to guarantee sufficient on-wing engines to reach service levels while effectively organizing shop visits for engines. However, complexity arises from intricate maintenance policies and uncertainty in engine deterioration. To address this problem, we propose a graph-based approach representing high-dimensional engine statuses and transitions. We then formulate the problem as a multi-stage stochastic integer program with endogenous uncertainty. We develop an approximate dynamic programming algorithm enhanced by dynamic graph generation and policy-sifting techniques so as to reduce the computational overhead in large problems. We demonstrate the efficacy of our method, compared with other popular methods, in terms of running time and solution quality. In the case study, we present an implementation in a real-world decision system in China Southern Airlines, in which the proposed method works seamlessly with other supporting modules and significantly improves the efficiency of engine maintenance management.

Risk assessment of continued airworthiness event of transport aircraft rudder pedal strut damage

Abstract To ensure the safe operation of aircraft after delivery, a set of continued airworthiness risk assessment processes and methods for transport aircraft is studied and proposed, including unsafe condition identification, consequence severity determination, occurrence possibility assessment, risk level determination, and reaction time calculation. The continued airworthiness risk matrix is established. Based on the established process and method, the risk assessment is carried out for the continued airworthiness event of transport aircraft rudder pedal strut damage. The relationship between the risk level of the fleet aircraft and the flight duration is determined, and the reaction time of the unsafe condition of the aircraft in each flight duration is calculated. The results show that the process and method are feasible.

Aircraft Skin Machine Learning-Based Defect Detection and Size Estimation in Visual Inspections

Aircraft maintenance is a complex process that requires a highly trained, qualified, and experienced team. The most frequent task in this process is the visual inspection of the airframe structure and engine for surface and sub-surface cracks, impact damage, corrosion, and other irregularities. Automated defect detection is a valuable tool for maintenance engineers to ensure safety and condition monitoring. The proposed approach is to process the captured feedback using various deep learning architectures to achieve the highest performance defect detections. Additionally, an algorithm is proposed to estimate the size of the detected defect. The team collaborated with TUI’s Airline Maintenance Team at Luton Airport, allowing us to fly a drone inside the hangar and use handheld cameras to collect representative data from their aircraft fleet. After a comprehensive dataset was constructed, multiple deep-learning architectures were developed and evaluated. The models were optimized for detecting various aircraft skin defects, with a focus on the challenging task of dent detection. The size estimation approach was evaluated in both controlled laboratory conditions and real-world hangar environments, providing insights into practical implementation challenges.

First Results of Airborne GNSS Radio Occultation Sounding From Airbus Commercial Aircraft

AbstractThe lack of high vertical resolution atmospheric thermodynamic structure observations inside or near major weather events impedes our understanding of physical processes and their predictability in numerical weather prediction (NWP) models. Airborne Global Navigation Satellite System (GNSS) radio occultation (airborne radio occultation [ARO]) has proven to be a viable remote sensing option to offer dense soundings near flight tracks. The global fleet of commercial aircraft already equipped with GNSS receivers could be leveraged to produce an unprecedented number of ARO soundings along global flight paths. Eleven cases of atmospheric bending angle and refractivity profiles were successfully retrieved and compared with the colocated European Center for Medium‐Range Weather Forecasting global reanalysis data. Good quality measurements are obtained with median refractivity differences less than 1% in the middle and upper troposphere, between 5.5 and 11.5 km. Given the use of aircraft data (e.g., Aircraft Meteorological DAta Relay) for data assimilation, incorporating ARO profiles would be a valuable addition, further enhancing the accuracy of aviation and weather forecasts.

Predicting airport noise impact to 2040: Traffic growth and technology uptake

While the volume of air traffic continues to rise, there are concurrent shifts in aircraft fleets and advancements in technology aimed at enhancing aircraft efficiency, sustainability, and minimizing noise footprints. These simultaneous developments contribute to the complexity of forecasting airport noise associated with future air traffic. This study presents various scenarios of technology adoption for the years 2030 and 2040 at a European airport, namely Dublin Airport, encompassing changes in fleet distribution. Aircraft are classified into different generations to reflect their technological advancements. Projections indicate an anticipated growth in the wide body fleet at Dublin Airport from 2023 to 2040, while the shares of narrow body, regional jet, and turboprop fleets are expected to decline. Each forecast year showcases three distinct technology uptake scenarios, with noise contour lines at Lden = ▪(A) and Lnight = ▪(A) being compared. To assess the impact of these changes on airport noise, the study evaluates alterations in area and population exposure. In general, the findings suggest a trend of increasing population exposure coinciding with the rise in air traffic. Nevertheless, the increase of wide body aircraft at Dublin Airport further increases the noise impact in 2030. Anticipated growth sees new generation 2 aircraft reaching up to ▪ by 2040, leading to a reduction in 2040 noise contour lines compared to 2030—though not returning to the levels observed in 2023.

Electric Taxiing System. Kinetic Energy Recovery System as an Electric Taxiing Solution: Economic and environmental analysis: Phenom 300 case study

The aviation industry has thrived in recent years, with a significant increase in passenger numbers, leading to the development of larger aircraft fleets and the expansion of airport infrastructure. In 2019, more than 4.5 billion passengers traveled by airplane, which represents an 80% increase compared to 2009. As a consequence, this growth has also resulted in longer taxiing times for aircraft, increasing fuel consumption and operational costs. The industry's CO2 emissions have quadrupled since the 1960s, with over 1 billion tons released in 2019, contributing to global warming. Given that the improvements being made to current propulsion systems and the production of over 600 million liters of SAF (Sustainable Aviation Fuel) in 2023 do not seem sufficient to meet the ambitious goals set by regulators and operators, the logical solution would be to develop a system capable of moving the aircraft on the ground using alternative, cleaner, and cheaper energies, such as electric power. This paper explores the latest advancements in electric propulsion systems, specifically focusing on external and onboard systems. After the state of the art is established, this paper will cover a case study and propose a new alternative for an onboard system called ETS – Electric Taxiing System. The ETS is a 100% electric system for ground handling operations designed to use only the kinetic energy stored in a battery pack, which is recovered during aircraft landing and braking events. Although there are some studies on this topic, the author considers this paper to be more comprehensive as the results computed here take into account 96 variables, 60 simulations, several flight plans, and real-world data. The case study focuses on the implementation and dimensioning of the ETS, considering electric motor power and torque, and battery capacity for the Embraer Phenom 300. A brief economic and environmental analysis was also conducted, considering the operation of NetJets Europe, the world's leading and largest private jet company.

Aviation noise in the United States: The current state of FAA research on community response

While today's civilian aircraft fleet is quieter than at any time in the history of jet-powered flight, the Federal Aviation Administration (FAA) continues to receive complaints about aircraft noise affecting communities across the United States. Additionally, the FAA's Neighborhood Environmental Survey (NES) has shown that community response to aviation noise in the United States has changed and the dose-response relationship between noise and annoyance such as the one represented by the Shultz Curve is no longer representative of communities' lived experiences. This paper will examine the current aviation noise environment in the United States and how the nature of aviation noise and the characteristics of communities that raise significant noise concerns in the United States have changed since the start of widespread use of commercial jet-powered aircraft in the 1960s. This paper will also explore the changing nature of community response to aviation noise based on the FAA's latest research findings on aviation noise and annoyance as detailed in follow-on analyses to the NES.

Validation of an Abaqus impact wave propagation model

Structural Health Monitoring (SHM) is an important topic in aircraft industry to reduce the maintenance costs and increase the availability of an aircraft fleet through automating the determination of the health of the aircraft structure and systems using on-site sensors, like piezoelectric (PZT) and optic fibre Bragg grating (FBG) sensors that are often applied in SHM sensor networks. A finite element model for wave propagation due to an impact is very desirable to enable the design of optimal sensor network configurations for SHM applications, to obtain a better understanding of wave propagation (especially in composite structures) and also to generate simulated (virtual) test data for SHM algorithm development. Therefore, an Abaqus explicit finite element (FE) model was developed for wave propagation due to impacts. To validate such a model, a series of impact tests were performed with a drop tower on an aluminium clamped square panel, at different impact energy levels and different impact locations. On the panel, eight FBG and six PZT sensors were installed. These experimental results were used to validate the FE model, in which the impacts were simulated and the computed PZT and FBG sensor responses were compared against the experimental results. The paper will present the impact test setup, the finite element model and the validation results. The main focus of the paper will be the sensitivity analysis, identifying the model parameters that significantly affect the impact sensor responses and their optimal settings. A very good correlation between the numerical and experimental results was obtained. In near future work, the model will be extended to a (thermoplastic) composite panel, for which experimental results on a flat composite panel already have been collected, and a stiffened composite panel representative of an actual horizontal tail plane are planned.

Autonomous sortie scheduling for carrier aircraft fleet under towing mode

Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft carrier. The primary difficulty exactly lies in the spatiotemporal coordination, i.e., allocation of limited supporting resources and collision-avoidance between heterogeneous dispatch entities. In this paper, the problem is investigated in the perspective of hybrid flow-shop scheduling problem by synthesizing the precedence, space and resource constraints. Specifically, eight processing procedures are abstracted, where tractors, preparing spots, catapults, and launching are virtualized as machines. By analyzing the constraints in sortie scheduling, a mixed-integer planning model is constructed. In particular, the constraint on preparing spot occupancy is improved to further enhance the sortie efficiency. The basic trajectory library for each dispatch entity is generated and a delayed strategy is integrated to address the collision-avoidance issue. To efficiently solve the formulated HFSP, which is essentially a combinatorial problem with tightly coupled constraints, a chaos-initialized genetic algorithm is developed. The solution framework is validated by the simulation environment referring to the Fort-class carrier, exhibiting higher sortie efficiency when compared to existing strategies. And animation of the simulation results is available at www.bilibili.com/video/BV14t421A7Tt/. The study presents a promising supporting technique for autonomous flight deck operation in the foreseeable future, and can be easily extended to other supporting scenarios, e.g., ammunition delivery and aircraft maintenance.

АНАЛІЗ ШЛЯХІВ МОДЕРНІЗАЦІЇ ЛІТАКІВ АН-2 З УРАХУВАННЯМ ВИМОГ EASA ЩОДО CS 23 LEVEL 4 ТА ЗАБЕЗПЕЧЕННЯ ПЕРЕВЕЗЕННЯ 10–19 ПАСАЖИРІВ

The article is devoted to the actual problem of modernization of the An-2 aircraft taking into account the EASA requirements for CS23 Level 4 to ensure the possibility of transporting 10–19 passengers. An overview of options for the modernization of the An-2 aircraft with replacement of engines and changing the design of the airframe has been carried out. An option to modernize the fleet of An-2 aircraft with the installation of a power plant that meets the requirements of the CS 23 Level 4 is proposed to ensure the possibility of transporting the number of passengers corresponding to the carrying capacity of the aircraft and the safety of passenger transportation. Options for the modernization of the An-2 type aircraft without or with minimal modification of the airframe, as well as options for the modification of the aircraft with the installation of a turboprop engines with a change of the airframe, have been considered. The advantages of using the modernization of the aircraft with its minimal modification have been characterized: they decrease the cost of maintenance of the power plant and fuel costs, engine maintenance in the field, as well as warm-up and start-up of the power plant are facilitated, and the aircraft dragin flight is reduced. It was established that the passengers capacity limits the transportation of passengers in new planes. Some completed improvement projects are listed: options for the modernization of the An-2 aircraft, options for modifying the airframe of the aircraft into a braced monoplane, options for a two-engine aircraft based on the An-2 airframe with one propeller, and options for the configuration of two engines under the cowling. Various schemes for installing two engines under the cowling: horizontally in a row, horizontally with downward displacement relative to the axis of the propeller, vertically in the plane of symmetry of the aircraft. Conclusions have been made about expediency of installing two turboprop engine with a single propeller drive instead of the existing power plant with a single piston engine to upgrade the An-2 type aircraft in service, and that it will allow to ensure the efficiency of passenger transportation in accordance with the existing requirements of the EASA CS 23 Level 4 and the maximum utilization of the aircraft

Deep learning methodologies based on metaheuristics for predictive engine maintenance

Recently, there has been an increase in concerns about the accessibility, security, and reliability of aviation engines. To prevent engine failures which can be quite serious, it is important to take effective measures. The objective is to create a deep learning simulation that can accurately predict an aircraft engine's viability and remaining usefulness using meta-heuristic techniques to improve its performance. These techniques discover the optimal hyper parameters and architecture for the deep learning model. This will help minimize downtime and maintenance costs for the aircraft fleet by handling complex data such as sensor readings and past maintenance records while also adapting to changing conditions over time. Since training deep learning models can be computationally intensive, meta-heuristic methods increase their robustness. The aim is to enhance performance by increasing the accuracy rate and reducing mean squared losses of multiple deep learning methods used for predicting aircraft engine maintenance by hybridizing them with metaheuristic algorithms.

Improving the calculation module for estimating pollutant emission from conventional and hybrid regional aircraft

For the aviation sector, it is extremely important to devise revolutionary solutions in the field of technology to restrain the potential impact of civil aviation on the environment to the level of the established strategic goals of ACARE (FlightPath2050). The introduction of innovative technologies (improvement of the combustion chamber, the introduction of electric hybrid power plants on airplanes, and the use of alternative aviation fuel) will ensure the sustainable growth of air transportation. To assess the effectiveness of advanced technologies, it is extremely important to have a model for calculating global/local emissions that takes into account the parameters of the flight path of conventional and hybrid aircraft, operational characteristics of the aircraft engine and hybrid powerplant, and the features of sustainable fuel. The improved module for calculating emission indices by combining the module for calculating the parameters of the flight path and the results of calculating the thermogas-dynamic calculation of the aircraft engine makes it possible to detect the influence of fuel consumption (engine thrust) on the values of the emission indices. This feature is representative for evaluating the efficiency of hybrid powerplants because the electrification of the aircraft fleet is primarily aimed at reducing fuel consumption. The analysis of simulation results reveals that the fuel consumption and EINOx are significantly reduced (for the climb stage – 25 %; for the descent stage – 30 %) for the hybrid AN26 compared to the conventional AN26. The specified operational measure, in the part of the low-pitch descend, significantly reduces EICO for the hybrid AN26 by an average of 50 % compared to the descend stage for the conventional trajectory. The results of calculations for the entire flight path demonstrate that the use of a hybrid power plant for An26 contributes to an average reduction of fuel consumption by 10 %, NOx emissions by 25 %, water vapor emissions by 10 %, and CO2 by 10 %.

GRAPHIC SUPPORT FOR THE OPERATION OF AIRCRAFT POWER UNITS

The main task of operators is to maintain the airworthiness of aircraft by implementing the technologies outlined in the sets of documents attached to standard products.Engines, the main source of energy for flight, usually work in conjunction with many systems, each of which, in turn, is accompanied by instructions and manuals to ensure operability. In accordance with accepted practice, most of the disaggregated information is provided in text form. These forces you to remember the necessary data or constantly search for it in dozens of updated and replaced pages of the provided technologies, or create your own convenient techniques that allow you to conduct parametric analyzes and develop decisions on control actions to correct the technical condition. Using examples of power plants with turboprop engines, approaches to the development and application of step-by-step unified graphical generalizations of processes and control parameter values, combined with indications of characteristics setting elements, are proposed. For the full cycle of work, the article proposes the most convenient, applicable to different types of power plants, unified method for constructing compact representations of all information in a generalized form. Recommendations have been developed for monitoring, adjusting characteristics and making decisions on the prospects for further operation.The methods have been tested under operating conditions, having confirmed their convenience and effectiveness at different stages of operation, and can be recommended for inclusion in Flight Operations Manuals created by airlines in relation to the range of operating conditions of their aircraft fleet.

Financial and Economic Situation and Development Features of Aviation Industry Entities

The relevance of the problem is determined by the fact that under the conditions of sanction pressure on the economy of the Russian Federation and periodic restrictions on the movement of air vehicles in international airspace, gaps arise in the continuity of functioning of aviation industry entities, creating barriers to obtaining and maximizing profi ts. The purpose of the study is to analyze the fi nancial and economic situation of aviation industry entities and determine the conditions for their further development. Materials and research methods — the systematic approach and situational analysis used in writing the article were based on processing the resources of information retrieval systems: GARANT, Consultant Plus. Also, the use of abstraction, grouping and series of dynamics of revenue, cost and profi t of the largest airlines in Russia made it possible to identify the priorities and causes of the fi nancial decline of the leaders of the national aviation market. As a result of the analysis of indicators of transport work and the aircraft fleet of the Russian air transport system, the reasons and possibilities for ensuring the availability of air transportation through the implementation of government support measures, including subsidizing the transportation of citizens and the development of regional transportation, were established. The article provides facts based on the results of the analysis of the Comprehensive Program of the current state and development of the aviation industry of the Russian Federation until 2030, among which important attention is paid to the need to achieve a gradual reduction in the number of foreign-made aircraft fl eet. The article reflects that the priority factors influencing the determination of consumer choice in the aviation market are: effective on-board technologies; network route offers and various loyalty programs for regular customers of passenger services. The authors of the article identified the reasons for the decline of PJSC Aeroflot, which was experiencing fi nancial difficulties and the risk of losses. The directions for further development of the largest airlines in Russia have been determined, taking into account «targeted» subsidizing measures and improving measures of state support for subjects of the Russian airline business.

Nose-Over and Nose-Down Accidents in General Aviation: Tailwheels and Aging Airplanes

Safety in General Aviation has been a continuous concern. About 12% of all airplane accidents in General Aviation involve nose-overs and nose-down events. A total of 134 accidents reported by the National Transportation Safety Board that include nose-overs and nose-downs were analyzed for their main causes. It was found that 35% of the defining events involved a loss of control on the ground while 58% of the total dataset involved tailwheel-type aircraft. A relatively high proportion of aircraft built before 1950 were found, which are also aircraft that have tailwheel-type landing gear, and thereby a higher propensity for ground loops and nose-overs. It is shown that the high accident rate in General Aviation, especially for accidents that did not result in a fatality, was, to an important extent, explained by tailwheel and older aircraft in the US General Aviation airplane fleet struggling with controlling the aircraft on the ground. Attention to this group of aircraft in future studies may help to more effectively address the relatively high accident rates in General Aviation.

Giraffes and Zebras on the Runway: the AMREF Flying Doctors (AFD) of Africa

In remote regions of Kenya, access to healthcare remains a persistent challenge, exacerbated by vast distances, rough terrain, and inadequate infrastructure. Amidst these obstacles, the AMREF Flying Doctors (AFD) based in Nairobi at Wilson Airport emerge embodying the spirit of medical outreach and innovation. Founded with the mission to provide timely medical assistance to underserved communities, this esteemed organization utilizes air transport to bridge the geographical barriers that often impede access to essential healthcare services.Since its inception, the Flying Doctors of Nairobi have played a pivotal role in delivering emergency medical care, conducting evacuations, and facilitating medical outreach programs across Kenya, Africa and the world. Operating with precision and efficiency, their fleet of aircraft is able to respond to emergencies, delivering medical teams and supplies to remote areas with the necessary celerity and exactness.Providing timely medical assistance, emergency evacuations, and specialized care to areas inaccessible by conventional means the service operates through a network of dedicated medical professionals, aviation experts, and technological infrastructure, ensuring rapid response and efficient delivery of medical services.This article follows a volunteer doctor and the author on the exciting journey to the Flying Doctors of Africa, based at Wilson Airport/Nairobi who reach out to a patient in medical needs from a rural airstrip within the Maasai Mara on which wild animals roam to medical evacuations which can span the entire globe.

A new method of fault diagnosis for aeroengines with dispersedly clumped gas path parameters

In an aircraft fleet with multiple aeroengines in service, the gas path parameter measurement values from engines of the same type are dispersed within a certain range due to manufacturing technology, assembly tolerances, operation conditions, and maintenance. This dispersion cannot be ignored and makes it impossible to apply unified health diagnosis criteria to all engines. To address this issue, a fault diagnosis solution for aeroengines with dispersedly clumped gas path parameters based on meta aero-engine is proposed. The concept of meta aero-engine is proposed to derive an engine group with dispersedly clumped parameters. To diagnose engines, a sphenophyllum classifier is proposed, which has a unified judgement criterion. A new weak classifier ensemble method based on divide-and-conquer is proposed to enhance the classification ability of the sphenophyllum classifier. The results of the basic classifier are partitioned and then analyzed in combination with the results of other classifiers in the classifier ensemble method. The effectiveness of the proposed method is verified through turbofan engine simulation dataset. The proposed method has strong interpretability for engine fleet with dispersedly clumped gas path parameters.