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Control forgetting accounts for most of the current unsafe incidents. In the research field of radar surveillance control, how to avoid control forgetting to ensure the safety of flights is becoming a hot issue which attracts more and more attention. Meanwhile, aviation safety is substantially influenced by the way of eye movement. The exact relation of control forgetting with eye movement, however, still remains puzzling. Motivated by this, a control forgetting prediction method is proposed based on the combination of Convolutional Neural Networks and Long-Short Term Memory (CNN-LSTM). In this model, the eye movement characteristics are classified in terms of whether they are time-related, and then regulatory forgetting can be predicted by virtue of CNN-LSTM. The effectiveness of the method is verified by carrying out simulation experiments of eye movement during flight control. Results show that the prediction accuracy of this method is up to 79.2%, which is substantially higher than that of Binary Logistic Regression, CNN and LSTM (71.3%, 74.6%, and 75.1% respectively). This work tries to explore an innovative way to associate control forgetting with eye movement, so as to guarantee the safety of civil aviation., (© 2023. The Author(s).)

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]

This paper studies the performance of machine learning predictions for the counterfactual analysis of air transport. It is motivated by the dynamic and universally regulated international air transport market, where ex post policy evaluations usually lack counterfactual control scenarios. As an empirical example, this paper studies the impact of the COVID-19 pandemic on airfares in 2020 as the difference between predicted and actual airfares. Airfares are important from a policy makers' perspective, as air transport is crucial for mobility. From a methodological point of view, airfares are also of particular interest given their dynamic character, which makes them challenging for prediction. This paper adopts a novel multi-step prediction technique with walk-forward validation to increase the transparency of the model's predictive quality. For the analysis, the universe of worldwide airline bookings is combined with detailed airline information. The results show that machine learning with walk-forward validation is powerful for the counterfactual analysis of airfares. [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.)

Carbon peaking and carbon neutrality are gaining global consensus, and carbon reduction in aviation is necessary and urgent. The main objective of this research paper is to map and analyze the knowledge graph of aviation carbon emissions research from a bibliometric perspective. Publications related to aviation carbon emissions indexed by Scopus for the period 1992 to 2021 were analyzed primarily using CiteSpace software. This paper presents a bibliometric analysis of current research progress from four perspectives: (1) descriptive analysis of publications, involving annual distribution, authors, and journals; (2) analysis of co-cited authors and their countries; (3) co-citation analysis of cited references; and (4) co-occurrence analysis of keywords. A series of domain knowledge maps were constructed to visualize the core of aviation carbon emissions research and to distill the research perspectives on aviation carbon emissions in the past 20 years. The latest and most important research results in the field obtained through the combing provide certain references for the research and development of aviation carbon emissions. [ABSTRACT FROM AUTHOR]

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.)

Spatial ability has long been considered an important attribute when identifying military aviators. This paper examines the Direction Orientation Task (DOT), which is currently used by the US military to assess spatial ability in aviation applicants. Several limitations of the test, such as a limited number of trials and the availability of practice trials online, make it subject to potential ceiling effects. The paper presents historical data of all Naval Aviator applicants over a six-year time period and revealed that 22% of applicants answered 90% or more of the questions correctly. Furthermore, test performance has significantly increased in the years since the test was first administered and there is evidence that DOT is no longer contributing incremental validity. A follow-up empirical study looked at DOT performance and strategy in a group of military student aviators and student air traffic controllers. The results of the empirical investigation reveal that the use of an analytic strategy was associated with higher performance on the DOT, whereas the use of a spatial strategy was not associated with performance. Taken together, the improved performance data over time and the data on strategy use suggest the test's ability to measure spatial ability may be diminishing, ultimately reducing its construct and incremental validity. This is problematic and should be addressed, since the DOT is the only measure of spatial ability used by the Navy to assess aviation applicants. [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]

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]

Over the years, aircraft and spacecraft designs incorporated highly integrated and/or complex systems that can manage complex scenarios during its operation. In addition to the inherent complexity and/or high level of integration of those systems, the development process applied to aerospace programs is also challenged by other factors: program schedule, budget, multidisciplinary teams, new industry emerging technologies, large number of different processes and procedures that guide the activities along the development life cycle, and others. Given the fact many tasks executed during the development of such systems require human interaction, that yields the introduction of design errors that can contribute to the occurrence of non-desired system behaviors during operation phase. It is already recognized by the civil aviation industry that it is unfeasible to have a deterministic test set to demonstrate that such systems are completely free of such design errors. In that context, a huge effort is applied by the industry, by using qualitative methods to mitigate the occurrence of design errors during the development phases. This paper discusses how MBSE methodology applied together with a design assurance process could prevent such design errors, and presents an analysis showing how some events in aerospace industry where a design error was one of the contributing factors could be avoided.

Operating an aircraft requires pilots to handle a significant amount of multi-modal information, which creates a high working memory load. Detecting auditory alarms in this high-load scenario is crucial for aviation safety. According to cognitive control load theory, an increase in working memory load may enhance distractor interference, resulting in improved detection sensitivity for task-irrelevant stimuli. Therefore, understanding the effect of working memory load on auditory alarm detection is of particular interest in aviation safety research. The studies were designed to investigate the effect of storage load and executive function load of working memory on auditory alarm detection during aeronautical decision-making through three experiments. In Experiment 1 and 2, participants performed an aeronautical decision-making task while also detecting an auditory alarm during the retention interval of a working memory task (visual-spatial, visual-verbal and auditory-verbal). In Experiment 3, participants were required to detect an auditory alarm while performing the 2-back and 3-back aeronautical decision-making tasks. Experiment 1 found that the auditory alarm sensitivity was higher in conditions of low visual-spatial working memory storage load compare to high load conditions. Experiment 2 found that a high storage load of visual-verbal working memory reduced auditory alarm sensitivity but auditory-verbal working memory load did not. Experiment 3 found that, unlike storage load, auditory alarm sensitivity was stronger under high executive function load relative to low executive function load. These findings show that working memory storage load and executive function load have different effects on auditory alarm sensitivity. The relationship between executive function and auditory alarm sensitivity supports cognitive control load theory, while the impact of the storage function on auditory alarm sensitivity does not adhere to this theory., 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 Elsevier Ltd. All rights reserved.)

Loss of control in flight is the primary category of fatal accidents within all sectors of aviation and failure to maintain adequate airspeed - leading to a stall - is often cited as a causal factor. Stalls occur when the critical angle of the aircraft is exceeded for a given airspeed. Using airspeed as an indicator of the potential to stall is an unreliable proxy. Systems that measure the angle of attack have been routinely used by military aircraft for over 50 years however rigorous academic research with respect to their effectiveness has been limited. Using a fixed-base flight simulator fitted with a simulated, commercially available angle of attack system, 20 pilots performed normal and emergency procedures during the circuit/pattern in a light aircraft. Experimental results have shown that pilot performance was improved when angle of attack was displayed in the cockpit for normal and emergency procedures during the approach phase of flight in the pattern/circuit. In relation to pilot workload, results indicated that during the approach phase of flight, there was a moderate but tolerable increase in pilot workload. The use of such a display may assist pilots to maintain the aircraft within the optimum range and hence reduce occurrences of unstable approaches. Overall, fewer stall events were observed when angle of attack was displayed and appropriate pilot decisions made during emergencies. These results provide a new perspective on pilot workload and aviation safety., 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.)

The black hole illusion (BHI) is a subtype of spatial disorientation that can result in fatal consequences in aviation. Research on the BHI has generally focused on altitude deviation, and few studies have examined the effect across different flight phases. In a simulation-based experiment, 18 participants performed 12 simulated approach and landing tasks in normal and BHI environments. Flight performance was analyzed with 14 flight parameters and was compared across five points and three phases, which were referenced from a National Transportation Safety Board report and other previous studies. Results showed that multiple flight parameters were significantly impaired and that their influences varied from the initial approach to the final touchdown. In the BHI environment, participants tended to descend aggressively during the approach phase and flew a lower but similar glidepath during the last approach phase. They might have realized the abnormal situation induced by the BHI but usually were unable to recover from the dangerous maneuver in time. Additionally, the result of glide path error, one of the most commonly used variables in previous BHI research, was only significant during the last approach phase. Flight stability was also impaired in the BHI environment. This is the first study to systematically analyze the BHI effects on multiple flight parameters at different flight phases. The use of this experimental paradigm could facilitate future research to evaluate and prevent the BHI in a more comprehensive way., Competing Interests: Declaration of competing interests 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 Elsevier Ltd. All rights reserved.)

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]

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]

Due to the continuous growth of air traffic and the development of aviation systems, the current safety management methodologies should be improved and upgraded. Safety management systems help aviation organizations to manage, maintain and increase safety efficiently. The focus of the research is on the development of the predictive safety management methodology to upgrade current reactive and proactive safety management methodologies and to improve the overall safety level in aviation organizations. Predictive methods are used in various aviation sectors (air navigation services, airport operations, airline operations) for planning purposes but not in the segment of safety management. Available examples of predictive methods were tested and analyzed. Time series decomposition methods were selected as most suited for implementation in aviation safety management. The paper explicitly emphasizes correlations between safety management methodologies in the sample aviation organization. The paper also shows how causal links among organizational and safety performance indicators can be detected, by developing causal models of mutual influences using causal modeling methods, on the sample organization. This research defined steps and tools of the conceptual model of predictive safety management methodology, which enables an organization to identify and mitigate future adverse events. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the paper is to investigate the role of civil aviation in the case of Montenegro, one of the smallest countries in Europe and one whose economy heavily relies on tourism. Methods: For this research, a dynamic panel data approach is used, where five models are proposed for modelling tourism demand. Available seats per kilometer, the Herfindahl-Hirschman index, jet fuel prices, exchange rates, and seasonality are used as the models' explanatory variables, in line with the available litetrature. Results: The econometric results show that all suggested models are valid, the explanatory variables are statistically significant, and their coefficients have the expected sign, suggesting a strong relationship between tourism demand and civil aviation. Implications: Apart from being one of the first attempts to highlight the civil aviation and tourism nexus in the context of Montenegro, this paper contributes to the literature by suggesting a way forward for destination managers and policymakers in small countries with great tourism potential. [ABSTRACT FROM AUTHOR]

Prognostic and health management (PHM) plays a vital role in ensuring the safety and reliability of aircraft systems. The process entails the proactive surveillance and evaluation of the state and functional effectiveness of crucial subsystems. The principal aim of PHM is to predict the remaining useful life (RUL) of subsystems and proactively mitigate future breakdowns in order to minimize consequences. The achievement of this objective is helped by employing predictive modeling techniques and doing real-time data analysis. The incorporation of prognostic methodologies is of utmost importance in the execution of condition-based maintenance (CBM), a strategic approach that emphasizes the prioritization of repairing components that have experienced quantifiable damage. Multiple methodologies are employed to support the advancement of prognostics for aviation systems, encompassing physics-based modeling, data-driven techniques, and hybrid prognosis. These methodologies enable the prediction and mitigation of failures by identifying relevant health indicators. Despite the promising outcomes in the aviation sector pertaining to the implementation of PHM, there exists a deficiency in the research concerning the efficient integration of hybrid PHM applications. The primary aim of this paper is to provide a thorough analysis of the current state of research advancements in prognostics for aircraft systems, with a specific focus on prominent algorithms and their practical applications and challenges. The paper concludes by providing a detailed analysis of prospective directions for future research within the field.

This paper provides an overview of cognitive radio technology and its applications in the field of civil aviation. Cognitive radio technology is a relatively new and emerging field that allows for dynamic spectrum access and efficient use of spectrum resources. In the context of civil aviation, cognitive radio technology has the potential to enable more efficient use of the limited radio spectrum available for communication and navigation purposes. This paper examines the current state of cognitive radio technology, including ongoing research and development efforts, regulatory issues, and potential challenges to widespread adoption. The potential applications of cognitive radio technology in civil aviation are also explored, including improved spectrum utilization, increased safety and security, and enhanced situational awareness. Finally, the paper concludes with a discussion of future research directions and the potential impact of cognitive radio technology on the future of civil aviation. It is hoped that this paper will serve as a useful resource for researchers, engineers, and policy makers interested in the emerging field of cognitive radio technology and its potential applications in the field of civil aviation.

Global Navigation Satellite System (GNSS) interference poses an increasing threat for civil aviation, and the detection and mitigation of interferences can help to make the sector more robust. This paper focuses on the detection and mitigation capabilities of a software-based Controlled Reception Pattern Antenna (CRPA) as part of a wider study in which different detection and mitigation methods are tested and compared. The proposed CRPA uses eigenvalue decomposition to determine the weight vector and is combined with MUltiple SIgnal Classification (MUSIC) for detection purposes. Simulations are used to test the software CRPA for its robustness against different types of interference in static and dynamic scenarios. The test method and processing pipeline are described. Initial results show the CRPA algorithm under test is capable of detecting and mitigating different types of interferences, and mitigation can help a receiver to maintain a position velocity time (PVT) solution for higher levels of interference power. [ABSTRACT FROM AUTHOR]

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This paper systematically introduces the application status of coating-preparation technology on light alloys in the field of aviation parts repair. Included are the advantages and disadvantages of thermal spraying technology and laser cladding technology in the application process, as well as the research status and application prospects of the emerging cold spray (CS) technology and supersonic laser deposition (SLD) technology. Compared with traditional thermal-spraying technology, CS has many advantages, such as low spraying temperature, low oxygen content of the coating, and low porosity, which can effectively avoid oxidation, burning loss, phase change, and grain length during thermal spraying. CS can prepare oxygen-sensitive, heat-sensitive, amorphous, and nanomaterial coatings that are difficult to prepare by traditional thermal-spraying technology. However, in the preparation of high-strength super-hard alloys, CS has shortcomings such as low deposition efficiency and bonding strength. SLD overcomes the shortcomings of CS while inheriting the advantages of CS. In the future, both technologies will be widely used in repairing and remanufacturing in the field of aviation. Based on the principles of CS and SLD, this paper introduces, in detail, the deposition mechanism of the coating, and the specific application examples of CS in the aviation field at the present stage are described. The research and application status of the two technologies in the fields of anti-corrosion coating, wear-resistant coating, functional coating, repair, and remanufacturing in recent years are reviewed. Finally, the application and development prospects of CS and SLD are discussed. [ABSTRACT FROM AUTHOR]

Dangerous goods (DGs) not declared for transport as required by the regulations can give rise to risks, as they can endanger public safety or the environment. This study explains the risks posed by undeclared shipments by providing information about the most common undeclared DGs aboard aircraft and maritime ships, legal frameworks regulating the proper transportation of DGs, and key mechanisms for preventing the occurrence of undeclared DG shipments. This paper identifies the responsibilities of each stakeholder involved in the process of DG transportation. The main objective of this paper is to reveal human errors and dishonest techniques within the supply chain when DGs are transported by air and sea. [ABSTRACT FROM AUTHOR]

To mitigate aviation's carbon emissions of the aviation industry, the following steps are vital: accurately quantifying the carbon emission path by considering uncertainty factors, including transportation demand in the post-COVID-19 pandemic period; identifying gaps between this path and emission reduction targets; and providing mitigation measures. Some mitigation measures that can be employed by China's civil aviation industry include the gradual realization of large-scale production of sustainable aviation fuels and transition to 100% sustainable and low-carbon sources of energy. This study identified the key driving factors of carbon emissions by using the Delphi Method and set scenarios that consider uncertainty, such as aviation development and emission reduction policies. A backpropagation neural network and Monte Carlo simulation were used to quantify the carbon emission path. The study results show that China's civil aviation industry can effectively help the country achieve its carbon peak and carbon neutrality goals. However, to achieve the net-zero carbon emissions goal of global aviation, China needs to reduce its emissions by approximately 82%-91% based on the optimal emission scenario. Thus, under the international net-zero target, China's civil aviation industry will face significant pressure to reduce its emissions. The use of sustainable aviation fuels is the best way to reduce aviation emissions by 2050. Moreover, in addition to the application of sustainable aviation fuel, it will be necessary to develop a new generation of aircraft introducing new materials and upgrading technology, implement additional carbon absorption measures, and make use of carbon trading markets to facilitate China's civil aviation industry's contribution to reduce climate change., 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 Elsevier Ltd. All rights reserved.)

The environmental concerns are behind urban and regional mobility plans, with one of the goals being to manage surface traffic to reduce emissions. Yet, in sensitive areas such as those around airports, the contribution to the emissions generated by air traffic are commonly not considered. The research goal of this paper is to quantify and compare the magnitude of the emissions generated by both air and surface traffic, taking the second airport in Rome as an example, in the awareness that a proper knowledge of the emission phenomena might help steer local transport policies towards more appropriate and sustainable solutions. The paper describes the case study's regulatory and land use frameworks both affecting the current traffic patterns around the airport and the emission generation, along with the methodology adopted to quantify the emission magnitude of both air and surface modes; as a result, air traffic emissions are not even comparable in magnitude to those from surface modes. In light of that, implications for surface transport policies are presented, leading to a revision of current mobility plans, and solutions to minimize emissions during land and take-off operations suggested, although problems for their implementations are acknowledged in the conclusions. All within the additional goal to advance the research further afield. [ABSTRACT FROM AUTHOR]

The aviation industry has committed to decarbonize its CO2 emissions. However, there has been much less industry focus on its non-CO2 emissions, despite recent studies showing that these account for up to two-thirds of aviation's climate impact. Parts of the industry have begun to explore the feasibility of potential non-CO2 mitigation options, building on the scientific research undertaken in recent years, by establishing demonstrations and operational trials to test parameters of interest. This paper sets out the design principles for a large trial in the North Atlantic. Considerations include the type of stakeholders, location, when to intervene, what flights to target, validation, and other challenges. Four options for safely facilitating a trial are outlined based on existing air-traffic-management processes, with three of these readily deployable. Several issues remain to be refined and resolved as part of any future trial, including those regarding meteorological and contrail forecasting, the decision-making process for stakeholders, and safely integrating these flights into conventional airspace. While this paper is not a formal concept of operations, it provides a stepping stone for policymakers, industry leaders, and other stakeholders with an interest in reducing aviation's total climate impact, to understand how a large-scale warming-contrail-minimizing trial could work. [ABSTRACT FROM AUTHOR]

Contrails are responsible for a significant proportion of aviation's climate impact. This paper uses data from the European Centre for Medium-Range Weather Forecasts to identify the altitudes and latitudes where formed contrails will not persist. This reveals that long-lived contrails may be prevented by flying lower in equatorial regions and higher in non-equatorial regions. Subsequently, it is found that the lighter fuel and reduced seating capacity of hydrogen-powered aircraft lead to a reduced aircraft weight, which increases the optimal operating altitude by about 2 km. In non-equatorial regions, this would lift the aircraft's cruise point into the region where long-lived contrails do not persist, unlocking hydrogen-powered, low-contrails operation. The baseline aircraft considered is an A320 retrofitted with in-fuselage hydrogen tanks. The impacts of the higher-altitude cruise on fuel burn and the benefits unlocked by optimizing the wing geometry for this altitude are estimated using a drag model based on theory proposed by Cavcar, Lock, and Mason, and verified against existing aircraft. The weight penalty associated with optimizing wing geometry for this altitude is estimated using Torenbeek's correlation. It is found that thinner wings with higher aspect ratios are particularly suited to this high-altitude operation and are enabled by the relaxation of the requirement to store fuel in the wings. An example aircraft design for the non-equatorial region is provided, which cruises at a 14 km altitude at Mach 0.75 with a less than 1% average probability of generating long-lived contrails when operating at latitudes more than 35° from the equator. Compared to the A320, this concept design is estimated to have a 20% greater cruise lift–drag ratio, due to the 33% thinner wings with a 50% larger aspect ratio, enabling just 5% more energy use per passenger-km, despite fitting 40% fewer seats. [ABSTRACT FROM AUTHOR]

In this paper, we report on a wind observation method based on the movement of hot‐air balloons (HABs). A quality assessment was carried out by comparing against wind observations at the meteorological tower of Cabauw in the Netherlands during May–September 2018, and the obtained standard deviations in error were σu=0.65ms−1$$ {\sigma}_u=0.65\;{\mathrm{ms}}^{-1} $$ and σv=0.69ms−1$$ {\sigma}_v=0.69\;{\mathrm{ms}}^{-1} $$ for the measured zonal and meridional wind components, respectively. Subsequent comparison against short‐term forecasts of the HARMONIE‐AROME model showed a standard deviation of 2.5 ms−1 for the wind vector difference. From the HAB observation set, a case was selected with a rapidly changing wind field belonging to a small intensifying depression. The HAB wind observation was applied in data assimilation as a proof of principle for a single‐observation experiment. It is shown that in a complex baroclinic situation, the model state is slightly improved. [ABSTRACT FROM AUTHOR]

With the continuous increase in flight flows, the flight conflict risk in the airspace has increased. Aiming at the problem of conflict resolution in actual operation, this paper proposes a tactical conflict resolution strategy based on Deep Reinforcement Learning. The process of the controllers resolving conflicts is modelled as the Markov Decision Process. The Deep Q Network algorithm trains the agent and obtains the resolution strategy. The agent uses the command of altitude adjustment, speed adjustment, or heading adjustment to resolve a conflict, and the design of the reward function fully considers the air traffic control regulations. Finally, simulation experiments were performed to verify the feasibility of the strategy given by the conflict resolution model, and the experimental results were statistically analyzed. The results show that the conflict resolution strategy based on Deep Reinforcement Learning closely reflected actual operations regarding flight safety and conflict resolution rules. [ABSTRACT FROM AUTHOR]

As the COVID-19 pandemic fades, the aviation industry is entering a fast recovery period. To analyze airport networks' post-pandemic resilience during the recovery process, this paper proposes a Comprehensive Resilience Assessment (CRA) model approach using the airport networks of China, Europe, and the U.S.A as case studies. The impact of COVID-19 on the networks is analyzed after populating the models of these networks with real air traffic data. The results suggest that the pandemic has caused damage to all three networks, although the damages to the network structures of Europe and the U.S.A are more severe than the damage in China. The analysis suggests that China, as the airport network with less network performance change, has a more stable level of resilience. The analysis also shows that the different levels of stringency policy in prevention and control measures during the epidemic directly affected the recovery rate of the network. This paper provides new insights into the impact of the pandemic on airport network resilience., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Guo 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.)

It has been a main concern for governments to reduce the carbon emission of the aviation industry. The paper proposes a multiobjective gate assignment model that considers the carbon emission at the airport surface to facilitate environmental-friendly airport construction. Three objectives are considered in the model to reduce carbon emissions, including the proportion of flights assigned to the contact gate, aircraft taxiing fuel consumption, and gate assignment robustness. In order to achieve better performance on all objectives, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is used to obtain the optimal results. The operation data from a domestic airport is deployed to validate the model. The optimal results of the gate assignment model are compared with the original scheme. It indicates that the proposed model can effectively reduce carbon emissions. The study can provide a strategy for gate assignment to reduce carbon emissions and improve the management of the airport.