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Engine failure after take-off (or one engine being inoperative) is an exercise conducted as part of multi-engine flight training and on-going competency checking. To prepare pilots to manage a real in-flight emergency, this exercise has traditionally been conducted immediately after take-off. This has led to increased risks of fatal accidents due to the reduced height at which these exercises are typically conducted. Yet, there is variation in the heights stipulated in training procedures published by different stakeholders worldwide. Additionally, the conduct of the exercise has resulted in fatal accidents worldwide. This paper aims to review the previous literature on aviation training and aviation occurrence data to determine what empirical data exists to support the method of conducting simulated engine failures. Peer-reviewed academic publications on aviation training, aviation occurrence databases such as aviation investigation reports, and guidance materials published by aviation authorities on simulated training exercises will be included in this paper. It was found that the previous research on these exercises has focused on the transfer of motion cues or pilot responses to abnormal situations, but did not include specific data comparing pilot performance at different heights above ground level. A review of aviation occurrences found that actual engine failures occurred at higher heights that those used in simulated engine failures. A comparison of the guidance published by aviation authorities identified variations in the minimum altitude published and differing justifications for the minimum height chosen. Future research is needed to compare pilot performance during simulated engine failures to determine the ideal height to conduct the exercise to be representative of an actual engine failure while maintaining safety margins. [ABSTRACT FROM AUTHOR]

The integration of artificial intelligence of things (AIoT) is transforming aviation health monitoring systems by combining extensive data collection with advanced analytical capabilities. This study proposes a framework that enhances predictive accuracy, operational efficiency, and safety while optimizing maintenance strategies and reducing costs. Utilizing a three-tiered cloud architecture, the AIoT system enables real-time data acquisition from sensors embedded in aircraft systems, followed by machine learning algorithms to analyze and interpret the data for proactive decision-making. This research examines the evolution from traditional to AIoT-enhanced monitoring, presenting a comprehensive architecture integrated with satellite communication and 6G technology. The mathematical models quantifying the benefits of increased diagnostic depth through AIoT, covering aspects such as predictive accuracy, cost savings, and safety improvements are introduced in this paper. The findings emphasize the strategic importance of investing in AIoT technologies to balance cost, safety, and efficiency in aviation maintenance and operations, marking a paradigm shift from traditional health monitoring to proactive health management in aviation. [ABSTRACT FROM AUTHOR]

The assessment of the cognitive workload experienced by air traffic controllers is a complex and prominent issue in the research community. This study introduces new indicators related to gamma waves to detect controllers' workload and develops experimental protocols to capture their EEG data and NASA-TXL data. Then, statistical tests, including the Shapiro-Wilk test and ANOVA, were used to verify whether there was a significant difference between the workload data of the controllers in different scenarios. Furthermore, the Support Vector Machine (SVM) classifier was employed to assess the detection accuracy of these indicators across four categorizations. According to the outcomes, hypotheses suggesting a strong correlation between gamma waves and an air traffic controller's workload were put forward and subsequently verified; meanwhile, compared with traditional indicators, the indicators associated with gamma waves proposed in this paper have higher accuracy. In addition, to explore the applicability of the indicator, sensitive channels were selected based on the mRMR algorithm for the indicator with the highest accuracy, β + θ + α + γ, showcasing a recognition rate of a single channel exceeding 95% of the full channel, which meets the requirements of convenience and accuracy in practical applications. In conclusion, this study demonstrates that utilizing EEG gamma wave-associated indicators can offer valuable insights into analyzing workload levels among air traffic controllers.

As urbanization and population growth escalate, the challenge of noise pollution intensifies, particularly within the aviation industry. This review examines current insights into noise-induced hearing loss (NIHL) in aviation, highlighting the risks to pilots, cabin crew, aircraft maintenance engineers, and ground staff from continuous exposure to high-level noise. It evaluates existing noise management and hearing conservation strategies, identifying key obstacles and exploring new technological solutions. While progress in developing protective devices and noise control technologies is evident, gaps in their widespread implementation persist. The study underscores the need for an integrated strategy combining regulatory compliance, technological advances, and targeted educational efforts. It advocates for global collaboration and policy development to safeguard the auditory health of aviation workers and proposes a strategic framework to enhance hearing conservation practices within the unique challenges of the aviation sector., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Humans working in modern work systems are increasingly required to supervise task automation. We examined whether manual aircraft conflict detection skill predicted participants' ability to respond to conflict detection automation failures in simulated air traffic control. In a conflict discrimination task (to assess manual skill), participants determined whether pairs of aircraft were in conflict or not by judging their relative-arrival time at common intersection points. Then in a simulated air traffic control task, participants supervised automation which either partially or fully detected and resolved conflicts on their behalf. Automation supervision required participants to detect when automation may have failed and effectively intervene. When automation failed, participants who had better manual conflict detection skill were faster and more accurate to intervene. However, a substantial proportion of variance in failure intervention was not explained by manual conflict detection skill, potentially reflecting that future research should consider other cognitive skills underlying automation supervision., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2024. Published by Elsevier Ltd. All rights reserved.)

Aviation is a vital modern transportation sector connecting millions of passengers globally. Sustainable aviation development holds substantial community benefits, necessitating effective management of its environmental impacts. This paper addresses the need for an accurate and cost-effective aircraft noise monitoring model tailored to non-towered general aviation airports with limited resources for official air traffic data collection. The existing literature highlights a heavy reliance on air traffic data from control facilities in prevailing aircraft noise modeling solutions, revealing a disparity between real-world constraints and optimal practices. Our study presents a validation of a three-stage framework centered on a low-cost transponder unit, employing an innovative experimental and analytical approach to assess the model's accuracy. An economical Automatic Dependent Surveillance-broadcast (ADS-B) receiver is deployed at Purdue University Airport (ICAO Code: KLAF) to estimate aircraft noise levels using the developed approach. Simultaneously, a physical sound meter is positioned at KLAF to capture actual acoustic noise levels, facilitating a direct comparison with the modeled data. Results demonstrate that the developed noise model accurately identifies aircraft noise events with an average error of 4.50 dBA. This suggests the viability of our low-cost noise monitoring approach as an affordable solution for non-towered general aviation airports. In addition, this paper discusses the limitations and recommendations for future research. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic negatively affected many sectors including aviation and travel. Travel bans and forced lockdowns prevented transportation activity, especially air travel. Accordingly, huge amounts of emission reductions occurred. On the other hand, travel restrictions are not the only cause of emissions reductions. Changing travel intention in the era of Covid-19 is another important factor that affects aviation emissions. This paper aims to investigate the Landing/Take-Off (LTO) emission changes at Turkish airports. An emission inventory has been implemented for the years 2019 and 2020 to reveal the impacts of Covid-19 on aviation emissions. Domestic, international, and cargo flights have been included in the inventory. According to the results, total emissions of SO2, CO2, CO, NOx, NMVOC, CH4, N2O, and PM2.5 have decreased in 2020 compared to 2019 by 49.8%, 49.7%, 41.0%, 52.6%, 40.0%, 33.8%, 49.8%, and 50.3%, respectively. Total CO2 reductions in the Q2, Q3, and Q4 periods of 2020 compared to that of 2019 are 87%, 50% and 43%, respectively. Another aim of this paper is to find the underlying reasons for emission reductions. For Turkish airports, emission reductions have resulted from travel bans in Q2. After the relaxation of restrictions with the declaration of the "New Normal" in Turkey, flight traffic rebounded to a certain level but was lower than 2019 levels. Therefore, changing travel intention is the main cause of emission reductions in Q3 and Q4 of 2020. The results of this study contribute to both the areas of air pollution and tourism management. [ABSTRACT FROM AUTHOR]

The paper explores a chronological account of major aviation-related terrorist incidents, including the hijacking of aircraft and attacks such as those on September 11, 2001. These events underscore the vulnerabilities within civil aviation security and highlight the psychological impact of such attacks. This study emphasizes the need for advanced technologies and stringent national and international regulations to combat aviation terrorism. It discusses the evolution of aviation security measures, the importance of a holistic approach involving airlines, airport authorities, security forces, and governmental bodies, and the necessity of information sharing and best practices adoption. Additionally, the paper addresses the economic implications of aviation security, advocating for better data collection and analysis to optimize resource allocation and enhance overall safety. The ongoing development of aviation security strategies, driven by evolving threats and technological advancements, is critical for safeguarding passengers and ensuring the resilience of the global aviation industry against terrorist threats. [ABSTRACT FROM AUTHOR]

In risk and safety assessments of aviation systems, engineers generally pay more attention to the risks of hardware or software failure and focus less on the risks caused by human errors. In this paper, a (FRAHE) method is proposed for identifying this critical error type and determining the risk severity of human errors. This method accounts for the human error probability as well as the impacts of human errors on the system. The fuzzy inference approach is employed in this paper to address the uncertainty and issues of imprecision that arise from insufficient information and scarce error data and a risk assessment model of human error is developed. The model can be used to precisely describe the relationship between the output risk severity and the input risk indicators, including the human error probability, the error impact probability, and the human error consequence. A case study of the approach task is presented to demonstrate the availability and reasonability of the model. The risk-based modeling method can not only provide valuable information for reducing the occurrence of critical errors but also be used to conduct prospective analyses to prevent unsafe incidents or aviation accidents., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Guo, Suo. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The spread of the COVID-19 had profoundly affected the development of the air transportation. In order to determine the changes in air transportation volume associated with the development of the epidemic, this paper takes Southwest China as the study area. Monthly data and methods, such as the coefficient of variation, rank-size analysis and spatial matching index, were applied. The results found that: (1) during 2020-2022, there was a positive relationship between passenger volume and epidemic development, while freight volume increased for most airports in the first quarter of 2020-2022, particularly in the eastern region; (2) From the perspective of changes in air transportation volume under the development of the COVID-19, among various types of airports, the changes in transportation volume of main trunk airports were more significant than those of regional feeder airports in remote areas; (3) however, under the influence of the epidemic, main trunk airports still exhibited stronger attraction in passenger volume. That is to say, the passengers who chose to travel by air still tended to choose the main trunk airports and formed the agglomeration distribution pattern which around high-level airports in the provincial capital. Whereas the freight volume had a tendency of equalization among airports in Southwest China; (4) Over the course of time, the consistency of the spatial distribution of the number of cases and the passenger or freight volume in southwest China gradually increased. Among them, the spatial matching rate of the passenger volume and the number of COVID-19 cases was always higher than that of the cases and freight volume, which might indicate that there was a stronger correlation relationship. Therefore, it is proposed that the construction of multi-center airport system should be strengthened, the resilience of the route network for passenger transportation should be moderately enhanced, and the risk-resistant capacity of mainline airports and airports in tourist cities should be upgraded, so as to provide references for the orderly recovery of civil aviation and regional development., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The operating room is the environment where harm to the patient is most likely. Robotic surgery was listed as one of the top 10 health hazards as late as 2020. Taking inspiration from other fields of application, such as aeronautics, checklists have been increasingly implemented in medical practice over the years, becoming essential components of the operating theatre. In addition to checklists, simulation has taken on a fundamental importance in reducing errors. This paper aims to provide a narrative review to assess the importance of checklists and training in robotic surgery and how they improve the outcome. A comprehensive literature search from January 2000 to September 2023 was conducted. A total of 97 articles were included in the initial search. Eleven studies were deemed relevant and were considered eligible for full-text reading. Among these, ten studies focused on the analysis of training effectiveness. An article in our review assessed the benefits of introducing checklists in the operating room. Innovations created in aviation, such as checklists and simulation, have entered the medical field to prevent human error. Developing dedicated checklist and surgical teams, through theoretical and practical training, has become essential in modern medicine. Tools such as checklists, training, and simulation are among the best methods to reduce adverse medical events. [ABSTRACT FROM AUTHOR]

This paper explores the predominantly male-dominated aviation sector and highlights the benefits of increasing female representation. The key objectives are to analyze the gender pay gap, assess the current gender imbalance, and explore how addressing these issues could contribute to the sector's sustainability and operational success. A combined quantitative and qualitative methodology is employed, including scenario-building based on monetary indicators and achievements from other industries where female workforce participation has been enhanced. The results demonstrate that closing the gender pay gap and boosting female participation in air transport operations, in line with supranational recommendations, can lead to significant financial gains and operational improvements. The study concludes that promoting gender equity is not only a social imperative but also a crucial factor for achieving sustainability goals within aviation. [ABSTRACT FROM AUTHOR]

Visibility is one of the key meteorological parameters with special importance in aviation meteorology and the transportation industry. Nevertheless, it is not a straightforward task to automatize visibility observations, since the assistance of trained human observers is still inevitable. The current paper attempts to make the first step in the process of automated visibility observations: it examines, by the approaches of artificial intelligence (AI), whether light points in the target area can or cannot be automatically detected for the purposes of night-time visibility observations. From a technical point of view, our approach mimics human visibility observation of the whole circular horizon by the usage of camera imagery. We evaluated the detectability of light points in the camera images (1) based on an AI approach (convolutional neural network, CNN) and (2) based on a traditional approach using simple binary thresholding (BT). The models based on trained CNN achieved remarkably better results in terms of higher values of statistical metrics, and less susceptibility to errors than the BT-based method. Compared to BT, the CNN classification method indicated greater stability since the accuracy of these models grew with increasing pixel size around the key points. This fundamental difference between the approaches was also confirmed through the Mann–Whitney U test. Thus, the presented AI-based determination of key points' detectability in the night with decent accuracy has great potential in the objectivization of everyday routines of professional meteorology. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has transformed the way human-computer interaction (HCI) teams are able to collaborate and coordinate in various domains, including aviation. AI's transformative capabilities can enhance teamwork, efficiency, and safety, particularly in risk management. AI's ability to process vast amounts of data and provide real-time insights enables informed decision-making and automation of repetitive tasks in aviation. By combining the strengths of AI and humans, outlined in our modified version of the 'HABA-MABA' framework, a dynamic teamwork relationship emerges, provided roles are successfully allocated. AI systems are able to act as intelligent assistants, offering timely recommendations, fostering effective communication, and facilitating coordination among crew members. Its adaptability and capacity for learning improve collaboration abilities, tailoring strategies to meet the team's specific needs. This paper explores the theories, considerations, and implications of human-AI teams in aviation, highlighting potential benefits, training recommendations, and future research directions. While human-AI teams offer numerous benefits, addressing the risks, limitations, and ethical considerations is crucial to ensuring safe and efficient operations. Future research must prioritize transparency, explainability, adaptability, and real-world testing to unlock the full potential of human-AI teams and foster successful integration across diverse domains. [ABSTRACT FROM AUTHOR]

Contrails are line-shaped clouds formed in the exhaust of aircraft engines that significantly contribute to global warming. This paper confidently proposes integrating advanced image segmentation techniques to identify and monitor aircraft contrails to address the challenges associated with climate change. We propose the SegX-Net architecture, a highly efficient and lightweight model that combines the DeepLabV3+, upgraded, and ResNet-101 architectures to achieve superior segmentation accuracy. We evaluated the performance of our model on a comprehensive dataset from Google research and rigorously measured its efficacy with metrics such as IoU, F1 score, Sensitivity and Dice Coefficient. Our results demonstrate that our enhancements have significantly improved the efficacy of the SegX-Net model, with an outstanding IoU score of 98.86% and an impressive F1 score of 99.47%. These results unequivocally demonstrate the potential of image segmentation methods to effectively address and mitigate the impact of air conflict on global warming. Using our proposed SegX-Net architecture, stakeholders in the aviation industry can confidently monitor and mitigate the impact of aircraft shrinkage on the environment, significantly contributing to the global fight against climate change., Competing Interests: NO authors have competing interests., (Copyright: © 2024 Nobel et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

With China being the world's largest emitter of greenhouse gases and its aviation sector burgeoning, the environmental performance of Chinese airlines has global significance. Amidst rising demands for eco-friendly practices from both customers and regulators, the interplay between airport infrastructure and environmental performance becomes pivotal. This research offers an innovative methodology to gauge the environmental performance of Chinese airlines, emphasizing the distance traveled between airports using weighted additive utility functions. Leveraging neural networks, the study investigates the impact of various airport infrastructural characteristics on environmental performance. Noteworthy findings indicate that ground control measures, automatic information services at origin airports, surface concrete on runways at both ends, and a centerline lighting system in destination airports positively influence environmental performance. In contrast, longer and wider runways at origin airports, increased distances to control towers, and asphalt runways at destination airports adversely affect it. These insights not only underscore the importance of strategic infrastructure enhancements for reducing carbon footprints but also hold profound policy implications. As global climate change remains at the forefront, fostering sustainable airport infrastructure in China can significantly contribute to worldwide mitigation efforts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Introduction: Continuing flight into adverse weather remains a significant problem in general aviation (GA) safety. A variety of experiential, cognitive, and motivational factors have been suggested as explanations. Previous research has shown that adverse weather accidents occur further into planned flights than other types of accident, suggesting that previous investment of time and effort might be a contributing factor. The aim of this study was to experimentally determine the effect of prior commitment on general aviation pilots' decision-making and risk-taking in simulated VFR flights., Method: Thirty-six licensed pilots 'flew' two simulated flights designed to simulate an encounter with deteriorating coastal weather and a developing extensive cloud base underneath the aircraft as it crossed a mountain range. After making a decision to continue or discontinue the flight, pilots completed a range of risk perception, risk taking, and situational awareness measures., Results: Visual flight rules were violated in 42% of the flights. Prior commitment, in terms of distance already flown, led to an increased tendency to continue the flight into adverse weather in the coastal 'scud running' scenario. Continuing pilots perceived the risks differently and showed greater risk tolerance than others. These 'bolder' pilots also tended to be more active and better qualified than the others., Conclusions: There are undoubtedly multiple factors underlying any individual decision to continue or discontinue a flight. The willingness to tolerate a higher level of risk seems to be one such factor. This willingness can increase with time invested in the flight and also seems to be related to individual flight qualifications and experience., Practical Applications: All pilots might benefit from carefully structured simulator sessions designed to safely teach practical risk management strategies with clear and immediate feedback., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author. Published by Elsevier Ltd.. All rights reserved.)

Research has shown that timing is modulated by mental workload, making duration judgments a measure of cognitive demand, alongside subjective assessments, and physiological measurements. Yet, it is unclear whether such findings can be extended in less controlled setups. By employing air traffic controllers in a real aviation environment, we tested whether tasks with different levels of cognitive load can affect their timing behavior. Participants completed temporal production, verbal estimation, and passage of time judgments, while actively engaging in real flight control sessions. Subjective assessments of task demands, as well as physiological responses (cardiac and electrodermal activity) were also measured. Accuracy of the produced intervals was measured at two distinct phases of the flight (during low-load cruising vs. high-load landing) and under two different task load manipulations (controlling one vs. two helicopters and speaking in native vs. non-native language). Analysis of interval production accuracy showed that during the high-load landing phase significant overproductions were made, compared to the low-load cruising phase, and landing two helicopters led to greater overproductions compared to landing only one. The duration of the two-helicopter sessions was significantly overestimated compared to the single-helicopter ones, and the passage of time was felt significantly faster. Subjective assessments of workload were positively correlated with the temporal estimations and passage of time judgments, and skin responses were positively correlated with the produced intervals. Overall, our results are consistent with past research, suggesting that mental workload modulates time perception in complex, real-world environments, thus making timing behavior a reliable index of the workload changes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In recent years, the rapid growth of air traffic has intensified pressure on the air transport system, leading to congestion problems in airports and airspace. The projected increase in demand exacerbates these issues, necessitating immediate attention. Additionally, there is a growing concern regarding the environmental impact of the aviation sector. To tackle these challenges, the adoption of advanced methods and technologies shows promise in expanding current airspace capacity and improving its management. This paper presents an overview of sustainable aviation, drawing on publications from academia and industry. The emphasis is on optimizing both flight and ground operations. Specifically, the review delves into recent advancements in airline operations, airport operations, flight operations, and disruption management, analyzing their respective research objectives, problem formulations, methodologies, and computational experiments. Furthermore, the review identifies emerging trends, prevailing obstacles, and potential directions for future research. [ABSTRACT FROM AUTHOR]

Reliable testing of aviation components depends on the quality and configuration flexibility of measurement systems. In a typical approach to test instrumentation, there are tens or hundreds of sensors on the test head and test facility, which are connected by wires to measurement cards in control cabinets. The preparation of wiring and the setup of measurement systems are laborious tasks requiring diligence. The use of smart wireless transducers allows for a new approach to test preparation by reducing the number of wires. Moreover, additional functionalities like data processing, alarm-level monitoring, compensation, or self-diagnosis could improve the functionality and accuracy of measurement systems. A combination of low power consumption, wireless communication, and wireless power transfer could speed up the test-rig instrumentation process and bring new test possibilities, e.g., long-term testing of moving or rotating components. This paper presents the design of a wireless smart transducer dedicated for use with sensors typical of aviation laboratories such as thermocouples, RTDs (Resistance Temperature Detectors), strain gauges, and voltage output integrated sensors. The following sections present various design requirements, proposed technical solutions, a study of battery and wireless power supply possibilities, assembly, and test results. All presented tests were carried out in the Components Test Laboratory located at the Łukasiewicz Research Network–Institute of Aviation. [ABSTRACT FROM AUTHOR]

This paper summarizes the findings of a detailed assessment of synthetic, electricity-based fuels for use in aviation, shipping, and road transport. The fuels considered correspond to the most promising alternatives that were analyzed as part of the German research project BEniVer (Begleitforschung Energiewende im Verkehr—Accompanying Research for the Energy Transition in Transport) initiated by the German Federal Ministry for Economic Affairs and Climate Action (BMWK). Focusing on usage, infrastructure, and ecological analyses, several e-fuels were evaluated and compared to fossil fuels according to the specific sector. It turns out that for all sectors evaluated, the existing sustainable synthetic fuels are already compatible with current technology and regulations. In shipping and road transport, the use of advanced, sustainable fuels will allow for a more distinct reduction in emissions once technology and regulations are adopted. However, standard-compliant synthetic gasoline and diesel are considered the most promising fuels for use in road transport if the transition to electricity is not realized as quickly as planned. For the aviation sector, the number of sustainable aviation fuels (SAFs) is limited. Here, the current aim is the introduction of a 100% SAF as soon as possible to also tackle non-CO2 emissions. [ABSTRACT FROM AUTHOR]

Air travel market has changed significantly by the emergence of a lowcost carrier (LCC). The LCCs offer lower fares and fewer frills than the traditional full service carriers (FSCs). The key competitive advantage of the LCCs is their ability to offer significantly lower fares, or at least to create the image of offering lower fares, while being able to generate profits by having low unit costs. LCCs have reshaped the competitive environment within air travel markets and have made significant impacts in the domestic passenger markets, which had previously been largely controlled by FSCs. The new demand for air travel experience through the low fares of low-cost airlines increases the likelihood of choosing not only low-cost airlines but also existing large airlines when choosing air travel. This generally equates to the intention of customers to move to more advanced products as their experience with new products increases. Therefore, the purpose of this study is to theoretically discuss the operating characteristics and market ripple effects of low-cost airlines, and to explore the theoretical implications of existing papers. [ABSTRACT FROM AUTHOR]

Reinforcement learning (RL) has seen an uptick in research interest in recent years, with many papers published in a plethora of different fields, topics and applications. A lot of that can be attributed to the recent advancements in machine learning (ML) and deep learning (DL) as a whole, the power of deep neural networks and the incorporation of them into reinforcement learning algorithms and techniques. This marriage of deep neural networks and traditional reinforcement learning methods has enabled reinforcement learning algorithms to achieve incredible results in use-cases that were previously deemed to be too complex. One of these highly complex scenarios is the realm of flight. In the last few years the number of papers published in this field has increased dramatically, but there is a fairly big divide between two major categories (quadcopters vs. fixed-wing aircraft). There is published work focusing on reinforcement learning using quadcopters, also known as drones, and there is published work focusing on fixed-wing aircraft, the more traditional aircraft, commonly referred to as airplanes. This paper focuses on the latter and will give an overview over the current state of reinforcement learning in the field of fixed-wing aviation. It will look into available toolkits usable for research as well as give an overview of different fields and tasks within reinforcement learning for fixed-wing aircraft control tasks. It contributes by providing detailed information about the methodologies used in each paper, while pointing out each paper’s contributions as well. A total of 48 papers on fixed-wing RL and airplane control are discussed. With the main focus lying on papers published post 2015, after the publication of Mnih et al.’s impactful deep RL paper.

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Engine failure after take-off (or one engine being inoperative) is an exercise conducted as part of multi-engine flight training and on-going competency checking. To prepare pilots to manage a real in-flight emergency, this exercise has traditionally been conducted immediately after take-off. This has led to increased risks of fatal accidents due to the reduced height at which these exercises are typically conducted. Yet, there is variation in the heights stipulated in training procedures published by different stakeholders worldwide. Additionally, the conduct of the exercise has resulted in fatal accidents worldwide. This paper aims to review the previous literature on aviation training and aviation occurrence data to determine what empirical data exists to support the method of conducting simulated engine failures. Peer-reviewed academic publications on aviation training, aviation occurrence databases such as aviation investigation reports, and guidance materials published by aviation authorities on simulated training exercises will be included in this paper. It was found that the previous research on these exercises has focused on the transfer of motion cues or pilot responses to abnormal situations, but did not include specific data comparing pilot performance at different heights above ground level. A review of aviation occurrences found that actual engine failures occurred at higher heights that those used in simulated engine failures. A comparison of the guidance published by aviation authorities identified variations in the minimum altitude published and differing justifications for the minimum height chosen. Future research is needed to compare pilot performance during simulated engine failures to determine the ideal height to conduct the exercise to be representative of an actual engine failure while maintaining safety margins.

Aviation is a vital modern transportation sector connecting millions of passengers globally. Sustainable aviation development holds substantial community benefits, necessitating effective management of its environmental impacts. This paper addresses the need for an accurate and cost-effective aircraft noise monitoring model tailored to non-towered general aviation airports with limited resources for official air traffic data collection. The existing literature highlights a heavy reliance on air traffic data from control facilities in prevailing aircraft noise modeling solutions, revealing a disparity between real-world constraints and optimal practices. Our study presents a validation of a three-stage framework centered on a low-cost transponder unit, employing an innovative experimental and analytical approach to assess the model’s accuracy. An economical Automatic Dependent Surveillance-broadcast (ADS-B) receiver is deployed at Purdue University Airport (ICAO Code: KLAF) to estimate aircraft noise levels using the developed approach. Simultaneously, a physical sound meter is positioned at KLAF to capture actual acoustic noise levels, facilitating a direct comparison with the modeled data. Results demonstrate that the developed noise model accurately identifies aircraft noise events with an average error of 4.50 dBA. This suggests the viability of our low-cost noise monitoring approach as an affordable solution for non-towered general aviation airports. In addition, this paper discusses the limitations and recommendations for future research.

Conventional Life Cycle Assessment (LCA) methods are able to assess environmental impact using significant resources (including time and data). However, due to the challenges associated with data collection these can still suffer from issues including representation accuracy, comparability, data availability, data quality, and uncertainty. This paper describes a new streamlined, high-level framework which seeks to solve these issues through rigorous and iterative application of existing standardised LCA methodologies whilst continually engaging with stakeholders. This new framework has been applied to an aviation case study, which seeks to investigate the potential environmental impact of implementing sustainable aviation fuel (including fuels based on used cooking oil, power to liquid technology, and hydrogen) and digitalisation of training regimes within a UK aircraft manufacturer. These are currently major areas of focus to enable the decarbonisation of the global aviation sector. The proposed framework allowed for efficient joint interpretation of results by different stakeholders, and therefore enabled effective strategic decision making without requiring the granular level of data detail demanded by conventional LCA frameworks. The case study has shown that each scenario offers potential reductions in global warming potential, fine particulate matter formation, and water consumption for an aircraft; but only when the associated supply chain is just as sustainable as the scenario in question. Overall, this research has shown that applying the new framework allows for rapid evaluation of decarbonisation technologies through rigorous environmental assessment to a degree accuracy which still enables strategic decision making, but without the use of unnecessary resources. Although this framework has been developed to work across product, platform, or system, further work should seek to apply it in different contexts as a LCA enabler within technological developments including exploration of other aviation decarbonisation pathways to achieve net zero. • Novel high-level framework improves efficiency in life cycle assessment. • Stakeholder-driven framework applied in an aviation case study. • Sustainable aviation fuels and training digitalisation reduce environmental impact. • Global environmental performance depends on sustainability in supply chain. • Framework allows rapid evaluation of decarbonisation technologies towards net zero. [ABSTRACT FROM AUTHOR]

Environmental concerns attract growing attention in aviation. Airlines and other aviation stakeholders are increasingly committed to more environmentally friendly operations. This paper aims to expand the understanding of the airlines' environmental attitudes and map best practices in the sector. To achieve this goal, the authors followed a two-stage analysis. Initially, a number of interviews were conducted with a focus group of key respondents from six Greek airlines, to draw the general picture of their environmental awareness. In the second stage, the authors studied the market's dominant airlines as a case to gain a deeper understanding of how an Environmental Management System (EMS) is deployed in practice and to allow for best practices to emerge. The research findings highlight the need for EMSs to become an integral part of airlines' operational strategy and the imperative for an articulate regulatory framework able to enhance the airlines' eco-path through concrete guidelines and knowledge exchange. • Larger airlines are in a better position to meet the environmental requirements and to plan a long-term environmental policy. • Air travel demand decline in 2020 due to Covid-19 had a two-sided effect regarding the environmental impact of aviation. • Detailed monitoring and data collection is an essential element of all Environmental Management Systems. • Coordinated action is needed involving all stakeholders for the implementation of operational procedures to mitigate noise. • Academic institutions in cooperation with non-profit environmental organizations may achieve the protection of biodiversity. [ABSTRACT FROM AUTHOR]

In this work, we explored the feasibility of using a transformer-based time-series forecasting architecture, known as the Temporal Fusion Transformer (TFT), for anomaly detection using threaded track data from the MITRE Corporation's Transportation Data Platform (TDP) and digital flight data. The TFT architecture has the flexibility to include both time-varying multivariate data and categorical data from multimodal data sources and conduct single-output or multi-output predictions. For anomaly detection, rather than training a TFT model to predict the outcomes of specific aviation safety events, we train a TFT model to learn nominal behavior. Any significant deviation of the TFT model's future horizon forecast for the output flight parameters of interest from the observed time-series data is considered an anomaly when conducting evaluations. For proof-of-concept demonstrations, we used an unstable approach (UA) as the anomaly event. This type of anomaly detection approach with nominal behavior learning can be used to develop flight analytics to identify emerging safety hazards in historical flight data and has the potential to be used as an on-board early warning system to assist pilots during flight. [ABSTRACT FROM AUTHOR]

Objective: To evaluate neck muscle coactivation across different levels of mental workload during simulated flight tasks. Background: Neck pain (NP) is highly prevalent among military aviators. Given the complex nature within the flight environment, mental workload may be a risk factor for NP. This may induce higher levels of neck muscle coactivity, which over time may accelerate fatigue, increase neck discomfort, and affect flight task performance. Method: Three counterbalanced mental workload conditions represented by simulated flight tasks modulated by interstimulus frequency and complexity were investigated using the Modifiable Multitasking Environment (ModME). The primary measure was a neck coactivation index to describe the neuromuscular effort of the neck muscles as a system. Additional measures included perceived workload (NASA TLX), subjective discomfort, and task performance. Participants (n = 60; 30M, 30F) performed three test conditions over 1 hr each while seated in a simulated seating environment. Results: Neck coactivation indices (CoA) and subjective neck discomfort corresponded with increasing level of mental workload. Average CoAs for low, medium, and high workloads were:.0278(SD =.0232),.0286(SD =.0231), and.0295(SD =.0228), respectively. NASA TLX mental, temporal, effort, and overall scores also increased with the level of mental workload assigned. For ModME task performance, the overall performance score, monitoring accuracy, and resource management accuracy decreased while reaction times increased with the increasing level of mental workload. Communication accuracy was lowest with the low mental workload but had higher reaction times relative to increasing workload. Conclusion: Mental workload affects neck muscle coactivation during combinations of simulated flight tasks within a simulated helicopter seating environment. Application: The results of this study provide insights into the physical response to mental workload. With increasing multisensory modalities within the work environment, these insights may assist the consideration of physical effects from cognitive factors. [ABSTRACT FROM AUTHOR]

Because of its distinct function and geographic conditions, the impact of climate change on the operation, safety, and income of airports in coastal areas is becoming increasingly significant. The measurement of climate resilience can help identify priority needs and measures to adapt to climate change, which is a crucial step in developing an aviation adaptation plan. At present, the concept of climate resilience is relatively complex and lacks a clear uniformity of composition, which has made it challenging to effectively support the development of adaptation strategies. Based on the definition of climate resilience, our first step was to construct an evaluation system for coastal airports to visually represent the level of climate resilience. Next, in this study, we introduced a coupling coordination and obstacle degree model to analyze the coordinated development and key drivers of climate resilience, which could be used to develop a targeted improvement strategy based on the calculation results. In the future, additional measures can be combined from the natural environment, socioeconomics, governance capacity, and climate change risk to enhance the capacity development of the aviation industry to address climate change and foster the establishment of a sustainable development model between the industry and the environment. [ABSTRACT FROM AUTHOR]

Diversity, equity, and inclusion (DEI) stands as an integral component of any successful organization. Historically, society has overlooked and underplayed DEI matters, resulting in the underrepresentation of minority groups, including women and people of color. In the past decade, underrepresentation of women and other minority groups in aviation workforce has received attention and raised concerns among industry stakeholders. To gain insight into the status of women in aviation, the authors analyzed the participation of females in aviation professions between 2016 and 2021. Data used in this study were retrieved from the 2023 U.S. Civil Airmen Statistics published by the Federal Aviation Administration (FAA). Descriptive and inferential statistical methods, including one-way analysis of variance (ANOVA), are used to analyze the trends and features of pilots and instructors holding different types of airmen certificates. The analysis delves into temporal, geographic, and age distributions. The temporal distributions reveal that the number and percentage of women in aviation professions have not significantly changed. From 2007 to 2021, female airline transport pilots (ATPs) marginally increased from 3.7% to 4.7%. Notably, there are statistically significant differences across the eight FAA regions, with the Alaskan region having the highest percentage of female pilots, instructors, and remote pilots, while the Central and Southwest regions exhibit the lowest percentages. In addition, a significant age-related disparity exists among female pilots, with a decline in female representation as the certification level advances. Given that the underrepresentation of women in aviation professions resulted from a mix of social, educational, organizational, and financial factors, recognition, understanding, embracement, and advocating for DEI issues could ultimately lead to increased equality, and a positive impact on the ongoing workforce shortage in the aviation sector and the long-term sustainability of the aviation industry. [ABSTRACT FROM AUTHOR]

The article focuses on emission analysis of non-CO2 pollutions from aircraft engines on different flight levels: FL240, FL300 and FL350. The calculation was made based on the A320 flight from Berlin to Lisbon at flight level 350, which was the reference flight level in the analysis. Four sustainable aviation fuels have been taken into consideration: biofuel from jatropha and biofuel from camelina, which are used in different percentages of fuel: 20% of CSPK and JSPK and 40% of CSPK and JSPK. The results showed that the lowest emission of carbon monoxide is on the lowest tested flight level for flight on biofuel, and the lowest emission of nitrogen oxides is for Jet A-1 on the lowest tested flight level. Emission of every toxic gas compound has been compared to conventional jet fuel on flight level 350 to show the differences between flight levels. [ABSTRACT FROM AUTHOR]

In order to design aircraft for minimum impact on climate, appropriate evaluation tools must be integrated early in the aircraft design loop and account for both CO2 and non‑CO2 effects. This paper evaluates the impact of CO2, NOx emissions, and contrail formation from turboprops (D328 and D328eco) compared to jets (A320, ERJ135) using simplified evaluation tools, namely the climate response models AirClim and LEEA. Operational parameters such as distance and altitude are varied, and we propose two one-dimensional correction methods to adjust the climate impact of contrails for aircraft size. Compared to turboprops, jets have higher fuel burn and fly on average at higher altitudes, where the impact from contrails is higher. Based on our assumptions, we show that turboprop aircraft have the capability to compete with larger aircraft and outperform regional jets in terms of climate impact per passenger-kilometre.

In recent years, the rapid growth of air traffic has intensified pressure on the air transport system, leading to congestion problems in airports and airspace. The projected increase in demand exacerbates these issues, necessitating immediate attention. Additionally, there is a growing concern regarding the environmental impact of the aviation sector. To tackle these challenges, the adoption of advanced methods and technologies shows promise in expanding current airspace capacity and improving its management. This paper presents an overview of sustainable aviation, drawing on publications from academia and industry. The emphasis is on optimizing both flight and ground operations. Specifically, the review delves into recent advancements in airline operations, airport operations, flight operations, and disruption management, analyzing their respective research objectives, problem formulations, methodologies, and computational experiments. Furthermore, the review identifies emerging trends, prevailing obstacles, and potential directions for future research.

As the aviation industry strives to minimise its environmental footprint, understanding the full life cycle impacts, including maintenance, becomes essential for sustainable development. This paper addresses the critical research gap in the environmental assessment of aircraft maintenance by conducting a comprehensive life cycle assessment based on an Airbus A320 aircraft. By combining a top-down check-level analysis and a detailed examination of the aircraft manufacturer's maintenance planning document, this study provides significant insights into the environmental implications of maintenance activities. The check-level analysis provides a general overview, while the analysis of the maintenance planning document delves into individual tasks, enabling the identification of components with the highest ecological impacts. This research emphasises the importance of including aircraft maintenance activities in life cycle assessment studies and provides valuable guidance for researchers, industry practitioners, and policy makers in prioritising sustainability measures and enhancing the environmental performance of aircraft throughout their life cycle. [ABSTRACT FROM AUTHOR]

Data management is a crucial requirement due to the autonomous and constrained nature of Unmanned Aerial Vehicles (UAVs), Internet of Things (IoTs), and the aviation domain. The autonomous and restricted nature of these sectors increases the need for a shared, distributed database, strong access control management, consensus in autonomous decision‐making, and effective communication across diverse protocols and devices. This research presents a comprehensive approach and offers a new viewpoint to the field of blockchain while establishing a fundamental baseline for future improvements in data management systems and addressing the shortcomings of previously proposed existing frameworks in order to fulfill the complex needs of secure data management. This study contributes to the advancement of secure and efficient data management systems by implementing robust data monitoring for error detection, ensuring data integrity, and enabling encrypted or anonymous data sharing based on sensitivity levels. Additionally, the integration of diverse devices, enforcement of immutable regulations compliance, and development of permissioned blockchain systems for identity management further enhance the system's capabilities, offering comprehensive solutions for modern data management challenges. In the tests, the proposed framework showed increased successful transactions in all rate controllers. Besides, effect of the validator number on throughput and latency is tested and analyzed thoroughly. [ABSTRACT FROM AUTHOR]

Artificial intelligence is developing at a rapid pace, with examples of machine learning already being used in aviation to improve efficiency. In the coming decade, it is likely that intelligent assistants (IAs) will be deployed to assist aviation personnel in the cockpit, the air traffic control center, and in airports. This will be a game-changer and may herald the way forward for single-pilot operations and AI-based air traffic management. Yet in aviation there is a core underlying tenet that 'people create safety' and keep the skies and passengers safe, based on a robust industry-wide safety culture. Introducing IAs into aviation might therefore undermine aviation's hard-won track record in this area. Three experts in safety culture and human-AI teaming used a validated safety culture tool to explore the potential impacts of introducing IAs into aviation. The results suggest that there are indeed potential negative outcomes, but also possible safety affordances wherein AI could strengthen safety culture. Safeguards and mitigations are suggested for the key risk owners in aviation organizations, from CEOs to middle managers, to safety departments and frontline staff. Such safeguards will help ensure safety remains a priority across the industry. [ABSTRACT FROM AUTHOR]

This study offers a comprehensive examination, both theoretically and experimentally, of the potential of methanol (M) as a sustainable aviation fuel (SAF) assessed in combination with kerosene (Ke—Jet-A aviation fuel + 5% Aeroshell oil). Different blends of methanol and kerosene (10%, 20%, and 30% vol. of (M) was added to Ke) were tested in an aviation micro turbo-engine under various operating regimes, such as idle, cruise, and maximum. Key engine parameters, including combustion temperature, fuel consumption, and thrust, were closely monitored during these trials. Essential performance indicators such as combustion efficiency, thermal efficiency, and specific consumption for all fuel blends under maximum operating conditions are also presented. Physical and chemical characteristics, such as viscosity, density, calorific value and flash point, were determined for each blend. Moreover, elemental analysis and FTIR spectroscopy were utilized to evaluate the chemical composition of the fuels. This study further investigated the air requirements for stoichiometric combustion and computed the resulting CO2 and H2O emissions. Experimental tests were conducted on the Jet Cat P80® micro turbo-engine, covering assessments of starting procedures, acceleration, deceleration, and pollutant emissions (CO and SO2) during various engine operating conditions. The results suggest that the examined fuel blends demonstrate stable engine performance at concentrations of 10% and 20% methanol. However, observations indicate that with an increase in methanol concentration, particularly at 30%, the stability of the engine at idle and, notably, at maximum speed decreases significantly. Specifically, at a 30% methanol concentration, the engine no longer operates stably, exhibiting significant rpm fluctuations, leading to the decision not to explore higher concentrations. [ABSTRACT FROM AUTHOR]

The aim of the study was to examine air traffic controllers’ perspectives on competency, performance, and training. Analysing data from 182 participants, the results revealed a strong focus on competency with the controllers actively evaluating their skills. Notably, the experienced controllers (19+ years) displayed a heightened commitment to continuous learning, reflected in their higher participation in individual training and perception of its value for their career goals and adaptation to the evolving aviation industry. Competency-based training programs also received positive feedback across experience levels, highlighting their potential effectiveness. Moreover, training was universally perceived as key to performance throughout careers. These results highlighted the importance of fostering a culture of continuous learning within air traffic control (ATC) communities. Aviation authorities can support this by providing diverse training opportunities, including individual and competency-based programs. Future research should continue investigating the impact of technological advancements and AI/machine learning on ATC competencies, the effectiveness of competency-based training programs, and the role of individual training in competency development, ultimately ensuring the vital role of air traffic controllers in aviation safety. [ABSTRACT FROM AUTHOR]

The European Union Aviation Safety Agency (EASA) continues to promulgate Safety Management Systems (SMS) across aviation organizations when it recently issued SMS requirements for EASA certificated Part 145 maintenance, repair and overhaul (MRO) organizations and Part 21 Design & Manufacturing (D&M) organizations. Currently, the FAA has no such rule in place for these U.S. based organizations, which may challenge those doing business in countries where EASA policies apply. Given that most of the United States' D&M and MRO population is made up of smaller organizations, it is likely a U.S. SMS regulation will require justification of the associated costs and benefits. This study explored the potential benefits SMS may provide these organizations by exploring the overall scope and nature of safety controls implemented through Airworthiness Directives (AD), which may help safety practitioners better understand how SMS in D&M organizations may reduce the number of AD related corrective actions. Researchers analyzed a sample of 189 ADs issued over a ten-year period and found that approximately 55% of the sampled ADs were the result of a new risk control, and approximately 45% were the result of a revised risk control. In these cases, the risk controls were not sufficient, and the AD action was necessary to ensure an acceptable level of safety. More effective risk controls have the potential to significantly reduce the number of ADs the industry must address. Every AD involves unplanned costs, often at multiple levels, and other variables that must be managed and implemented as part of the aircraft maintenance and manufacturing process. SMS may further improve the industry's safety performance by reducing the number of corrective actions and their associated costs. [ABSTRACT FROM AUTHOR]

Aviation is undergoing significant sustainability issues, making energy efficiency and emissions concerns crucial. This paper examines the energy efficiency patterns of flights departing from 20 airports in Saudi Arabia from 2017 to 2021, considering the influence of the COVID-19 outbreak and the efficiency of the aviation industry. The study assesses energy efficiency by analyzing historical patterns, the hypothetical situation of what could happen in the absence of the COVID-19 pandemic, and the actual situation materialized within the Saudi aviation sector. The findings suggest that despite disruptive events, such as the pandemic and its management practice, aviation has improved its energy efficiency, with flights at some airports experiencing significant improvements due to effective management practices derived from changing previous conditions. This research contributes to the ongoing discourse concerning energy efficiency in aviation and supports the development of policies and measures to address energy and environmental-related challenges in the short and medium term.

The aviation industry faces an urgent need to adopt sustainable aviation fuels for significant decarbonization. Power-to-Liquid (PtL) fuel is considered a potential game changer, but questions remain about the wider economic impacts of introducing PtL fuel in the aviation sector. This paper examines the economic impacts of introducing PtL fuel blending quotas along with a price policy consisting of a kerosene tax and PtL fuel subsidies for the case of Germany. Based on a detailed supply chain analysis, we apply a social accounting matrix and a computable general equilibrium model to take into account both, the production and utilization perspectives of PtL jet fuel. Our results show that the influence of low blending quotas is mainly limited to the aviation sector, with a 10 % blending quota increasing consumer prices by 7.9 % and reducing aviation industry output by 3.1 %. When quota levels increase, however, the effects go beyond the air transport system. On inter-sectoral level, we identify three main patterns: First, industries that substantially contribute to the PtL fuel supply chain, such as metal products and electrical equipment, see increasing levels in both, domestic production, and imports. Second, aviation upstream industries like transport infrastructure and aircraft production see reduced domestic production and imports. Third, aviation downstream industries, such as delivery services and travel agencies, see substitution effects, where imports partly replace domestic output. Macroeconomic indicators are affected negatively by the quota scenarios, but the relative impact is low as the maximum decrease in the gross domestic product (GDP) does not exceed 0.35 %. PtL fuel production subsidies can largely mitigate the decrease in aviation demand but come at the cost of a stronger reduction in the GDP and government income. Moreover, the sensitivity analysis emphasizes that various assumptions and parameters, such as the cost projections of PtL fuel, import options, and elasticities of demand, affect the intensity of economic consequences. Our analysis implies the trade-offs of policymaking between sectoral and macroeconomic interests in the context of sustainable fuels. The main contribution of this study is the investigation of the broader economic effects resulting from the adoption of PtL fuels in aviation. In particular, the production as well as the utilization perspective are considered simultaneously in this study.

Air travel market has changed significantly by the emergence of a lowcost carrier (LCC). The LCCs offer lower fares and fewer frills than the traditional full service carriers (FSCs). The key competitive advantage of the LCCs is their ability to offer significantly lower fares, or at least to create the image of offering lower fares, while being able to generate profits by having low unit costs. LCCs have reshaped the competitive environment within air travel markets and have made significant impacts in the domestic passenger markets, which had previously been largely controlled by FSCs. The new demand for air travel experience through the low fares of low-cost airlines increases the likelihood of choosing not only low-cost airlines but also existing large airlines when choosing air travel. This generally equates to the intention of customers to move to more advanced products as their experience with new products increases. Therefore, the purpose of this study is to theoretically discuss the operating characteristics and market ripple effects of low-cost airlines, and to explore the theoretical implications of existing papers.

This study was motivated by the observed growth and increased significance of situation awareness (SA) in recent years. Despite its acknowledged importance, a notable gap exists in the literature regarding comprehensive systematic reviews of SA within the aviation sector. This gap spurred a meticulous analysis of 754 articles from the Web of Science (WoS) core database for bibliometric knowledge mapping. The primary aim was to fill this gap and acquire a holistic understanding of SA in aviation. This analysis highlighted the USA as the primary contributor to publications, with NASA leading among the institutions in paper contributions. Human Factors and the International Journal of Aerospace Psychology were the leading journals in this domain. This bibliometric study underscored the key focus on healthcare, aviation, performance, workload, and safety through co-occurrence and co-citation analyses. A chronological examination of keywords revealed a central research trajectory centered on patient and crew safety and the impact of automation on human performance in dynamic flight scenarios. Burst keyword analysis pinpointed leading-edge research in SA within healthcare, model, and system design, and the implications of human factors. This study explored the research landscape of SA in aviation using a bibliometric approach. The outcomes shed light on the present research landscape and expedite scholars’ comprehension of advancements in this pivotal field. Finally, we derived a conceptual framework using the main components found in the literature. This framework will help researchers identify the main dimensions of SA.

This paper analyzes the different climate policies that are used by the EU in the aviation sector. Using a simple model, we study their effects on welfare as well as on their acceptability. The efficiency and acceptability depend on the strength of the international agreements (Paris, 2015; CORSIA, 2020) and on the implementation of the policy within the EU. Four different policies are discussed: carbon taxes, tradeable emission permits, Sustainable Aviation Fuels (SAF) blending mandates and fuel efficiency standards for new aircrafts. The Paris and the CORSIA agreements are both weak agreements where, in the absence of sanctions, the implementation depends on the will of the political majority of the moment. In terms of implementation, it is shown that for intra EU aviation, the insertion of aviation in the EU-ETS with partially auctioned emission permits is probably the most robust and efficient implementation of the Paris agreement as it can result in net zero emissions in 2040–2050. Subsidies for R&D in fuel efficiency and new fuels would be good complements to the ETS system as they also have a positive spillover for the non-EU aviation via better aircrafts and better fuels. SAF mandates are likely to be inefficient implementations of climate policies, they exist because they are more acceptable for the airlines and intensive air transport users. • The efficiency and acceptability of climate policy depend on the strength of the international agreements. • For intra EU aviation, the EU-ETS with partially auctioned emission permits is the most robust and efficient implementation of the Paris agreement. • Subsidies for R&D in fuel efficiency and new fuels would be good complements to the ETS system as they also have a positive spillover for the non-EU aviation. • SAF mandates are inefficient implementations of climate policies, but they are more acceptable for the airlines and intensive air transport users. [ABSTRACT FROM AUTHOR]

The objective of this work is to develop a new modelling tool to quantify non-CO2 emissions from aircraft during the landing and take-off (LTO cycle) considering the following criteria: (i) utilising freely available activity data; (ii) using widely recommended emission factors; (iii) providing emissions with the spatial and temporal resolution required for local air quality assessment. Freely available flight tracking data obtained from Flightradar24 and emission factors from the European Environment Agency (EEA/EMEP) are considered for the algorithm implementation and tested for Lisbon airport. The analyses of aircraft emissions during various flight stages reveal that HC and CO are mostly emitted during taxiing (93%), while NOX and PM are mostly produced during climb-out (48% and 35%, respectively). Sensitivity analysis, by using simplified activity data from publicly available databases against detailed engine models and emission factors, showed variations in the daily emissions of less than 13% in the case of CO and NOX, but up to 34% for HC and PM. The modelling approach based on freely available activity data developed in this work may offer valuable insights for quantifying airport emissions, providing crucial inputs for air quality assessment, and supporting the definition of mitigation strategies aimed at enhancing sustainability in aviation practices. [ABSTRACT FROM AUTHOR]

The production of thin-walled elements, especially those with large overall dimensions, poses numerous technological and operational problems. One of these problems relates to the machining-induced strain of such elements resulting from residual stress generated during the machining process. This study investigates the effect of the technological parameters of milling on residual stress in the surface layer of thin-walled plates made of aluminum alloy EN AW-2024 T351 for aerospace applications. The results have shown that residual stress increases with the cutting speed only to a certain point, reaching the maximum value at vc = 750 m/min. At a cutting speed vc = 900 m/min, residual stress significantly decreases, which probably results from the fact that the milling process has entered the High-Speed Cutting range, and this inference agrees with the results obtained for the cutting force component. Residual stress increases with the feed per tooth, while the relationship between residual stress and milling width is the same as that established for residual stress and variable cutting speed. Positive tensile stress is obtained in every tested case of the milling process. The results have also shown that the induced residual stress affects the strain of machined thin-walled parts, as proved by the strain results obtained for milled thin walls. [ABSTRACT FROM AUTHOR]