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There is a growing risk to aircraft in flight from collisions with debris produced by the breakup of uncontrolled rocket bodies and satellites during atmospheric reentry. On one hand, the aviation industry has grown to almost 39 million flights per year, with a 63 % increase between 2004 and 2019. On the other hand, the number of successful rocket launches more than doubled between 2015 and 2023, from 87 to 212, respectively. During those 212 launches in 2023, 128 rocket bodies were abandoned in orbit, left to reenter uncontrollably. Such uncontrolled space object reentries are hard to predict, making mitigation measures difficult. In November 2022, a reentering Long March 5B rocket caused the closure of airspace over Europe, delaying 645 flights and having a plausible economic impact of millions of Euros. There are international and domestic laws that might enable the recovery of economic losses resulting from uncontrolled reentries, but such losses should not be allowed to occur in the first place. Instead of leaving the location of a reentry to chance, controlled reentries can be achieved with existing technologies and mission designs, directing reentries away from areas of high aircraft traffic. Moving to a controlled reentry regime would create a cost to space operators – but that cost is currently being externalized to the aviation industry. Multilateral solutions to create a controlled reentry regime should be pursued, as recommended in the 2023 Montreal Recommendations on Aviation Safety and Uncontrolled Space Object Reentries, before there is a tragedy caused by an aircraft collision with debris from a rocket body or satellite. • As the number of rocket launches and commercial aircraft flights increase, the probability of a catastrophic collision between an aircraft and reentering space debris is also growing. • Technologies and mission designs exist to enable all rocket bodies to be returned to Earth in a controlled manner, eliminating the casualty risk. • From a broad economic perspective, space companies are externalizing some of their risks and costs and imposing them on the aviation industry. • States are liable for damage caused by reentering space objects and could be liable for the economic costs caused by precautionary airspace closures. • The 2023 Montreal Recommendations offer actionable steps to reduce the risk of collisions between space debris and aircraft. [ABSTRACT FROM AUTHOR]

This article examines the films "Sully" and "Flight" and their portrayal of prevailing ideologies. Released during Barack Obama's presidency, both films focus on skilled pilots rather than passengers. "Sully" presents a white male hero who opposes regulation, while "Flight" features an African American antihero who finds redemption in jail. Both films affirm mainstream ideologies of individualism and redemption, while also highlighting the challenges and contradictions within the United States. The article argues that both films ultimately reinforce American nationalism and fail to address the social and political realities of their time. [Extracted from the article]

This study proposes a probabilistic model to assess the likelihood of passenger survival in fires resulting from aircraft accidents. The model evaluates the risk of passenger death in a fire, considering the type of aircraft and airline. By comparing the time available for passengers to fully evacuate a burning plane with the time required for evacuation using modern means and technologies, onboard rescue equipment, and the qualifications of crew members and rescue personnel, we introduce a comprehensive approach to quantify passenger survival rates. Additionally, the concept of the hazard coefficient is introduced, which accounts for factors such as cabin temperature and toxic components. [ABSTRACT FROM AUTHOR]

This paper investigates the usage of a systemic neutralized taxonomy for understanding human factors to foster a restorative culture when studying adverse events. The available studies supporting accident analysis from a system‐theoretic perspective with human factors‐based methods are grounded on error taxonomies and do not reinforce the non‐judgemental dimension that is encouraged by modern safety science. We propose a methodology to integrate the system‐theoretic accident analysis technique, Causal Analysis based on System Theory, with a neutralized taxonomy of human explanatory factors. The proposed methodology has been applied to an aviation accident involving a military aircraft and a glider. This case revealed various critical interactions among system components, which require dedicated safety recommendations that go beyond the identification of single points of failures and root causes, leading to a deeper understanding of socio‐technical orchestrations. Despite the use case in aviation, the proposed methodology remains suitable for various types of safety occurrences in diverse domains and industrial settings. It also represents the basis for supporting future proactive safety‐related decision‐making processes. [ABSTRACT FROM AUTHOR]

INTRODUCTION: The European Air Transport Command (EAT C) is a seven-nation integrated command. One of its core capabilities is strategic aeromedical evacuation (AE). During the global COVID-19 pandemic and Ukrainian crisis, EAT C proved that acting in concert is a valuable, effective, and reliable option. METHODS: By pooling and sharing aircraft and personnel, EAT C has privileged access to a diverse fleet and pool of experts. Cooperation is based on a common set of rules and regulations, which ensures that EAT C can address any problem with expertise. RESULTS: During the COVID-19 pandemic, 1060 COVID-19-positive patients were transported in 198 missions, with neither death nor disease transmission reported during those strategic AE flights. EAT C transferred 986 military cases, mostly routine priority (91.4%); the other 74 cases were civilians, who were transported in 17 missions, with 81.1% categorized as urgent. During the Ukrainian crisis, 251 patients were transported, 112 military and 139 civilians, including 30 children. Among the recorded injuries were cerebrocranial, abdominal, and chest injuries, as well as fractures (180) and amputations (48) of the extremities. DISCUSSION: EAT C is recognized as a center of expertise within the AE community, where interoperability and harmonization of concepts are key to safety and success. Cross-national missions, where a patient is evacuated by an aircraft and medical crew provided by another nation, offer maximum flexibility. Complex situations, such as the COVID-19 pandemic and the Ukrainian crisis, have shown that multinational cooperation is not only achievable but also provides robust, effective, and reliable solutions for AE in particular. [ABSTRACT FROM AUTHOR]

The case study on Airblue chronicles the events that led to the biggest plane crash in the aviation history of Pakistan. Airblue flight 202 destined from Karachi to Islamabad crashed while attempting to land under adverse weather conditions. The flight carried 146 passengers and 6 crew members; all died in the crash. Later investigations identified gross errors in judgment and decision making by the cockpit crew and unprofessional attitude as the sole cause of the crash. The case study documents the events that unfolded prior to the crash and identifies a number of major factors that are important while communicating and making decisions under critical situations. It touches upon the themes of superior-subordinate communication and relationships, empowerment, sense of responsibility under life-threatening situations, making sense of crises, the role of initiative, self-confidence, and reliance on others. The case is suitable to be taught on topics dealing with communication, decision making, teamwork, and leadership in crises, at the graduate level (MBA) and in executive training courses on team building, leadership and crisis management. It highlights the situations which emerge as crises and where teamwork is paramount for the effective achievement of goals. Furthermore, it focuses on the possible relapses when effective teamwork and communication are not in play. [ABSTRACT FROM AUTHOR]

This article provides an overview of the mental health challenges faced by pilots and air traffic controllers (ATCs), whose stressful professional lives may negatively impact global flight safety and security. The adverse effects of mental health disorders on their flight performance pose a particular safety risk, especially in sudden unexpected startle situations. Therefore, the early detection, prediction and prevention of mental health deterioration in pilots and ATCs, particularly among those at high risk, are crucial to minimize potential air crash incidents caused by human factors. Recent research in artificial intelligence (AI) demonstrates the potential of machine and deep learning, edge and cloud computing, virtual reality and wearable multimodal physiological sensors for monitoring and predicting mental health disorders. Longitudinal monitoring and analysis of pilots' and ATCs physiological, cognitive and behavioral states could help predict individuals at risk of undisclosed or emerging mental health disorders. Utilizing AI tools and methodologies to identify and select these individuals for preventive mental health training and interventions could be a promising and effective approach to preventing potential air crash accidents attributed to human factors and related mental health problems. Based on these insights, the article advocates for the design of a multidisciplinary mental healthcare ecosystem in modern aviation using AI tools and technologies, to foster more efficient and effective mental health management, thereby enhancing flight safety and security standards. This proposed ecosystem requires the collaboration of multidisciplinary experts, including psychologists, neuroscientists, physiologists, psychiatrists, etc. to address these challenges in modern aviation. [ABSTRACT FROM AUTHOR]

Airports can be attractive places for fauna to find food resources, especially for large birds, which can cause severe collisions with aircraft. At many Brazilian airports, the Crested Caracara (Caracara plancus) is considered a problem due to the high rates of collisions and sightings in risk areas. Therefore, strategies to manage the species at airports are needed. We use an airport located in Central Brazil as a model system to evaluate the density and space-time distribution of Crested Caracara at the airport and in nearby regions. We studied the fortnightly temporal distribution and density of Crested Caracara in five different areas throughout one year, including the airport. Using circular statistics, we found that the spatiotemporal distribution was uneven throughout the year in all observed areas, with sightings peaking at different times. The airport's distribution differed from three out of four other areas. The density was higher in the region farthest from the city center. In the airport, the density was one of the lowest. The difference between density and temporal distribution patterns can be explained by the species' foraging dynamics, which shift according to the availability and abundance of resources, which vary randomly over time in the urban landscape. Our research is the first to evaluate the temporal distribution of problematic bird species in airports and their surroundings. The results can contribute to management plans to mitigate the risk imposed by fauna. [ABSTRACT FROM AUTHOR]

Air traffic controllers' mental workload significantly impacts their operational efficiency and safety. Detecting their mental workload rapidly and accurately is crucial for preventing aviation accidents. This study introduces a mental workload detection model for controllers based on power spectrum features related to gamma waves. The model selects the feature with the highest classification accuracy, β + θ + α + γ, and utilizes the mRMR (Max-Relevance and Min-Redundancy) algorithm for channel selection. Furthermore, the channels that were less affected by ICA processing were identified, and the reliability of this result was demonstrated by artifact analysis brought about by EMG, ECG, etc. Finally, a model for rapid mental workload detection for controllers was developed and the detection rate for the 34 subjects reached 1, and the accuracy for the remaining subjects was as low as 0.986. In conclusion, we validated the usability of the mRMR algorithm in channel selection and proposed a rapid method for detecting mental workload in air traffic controllers using only three EEG channels. By reducing the number of EEG channels and shortening the data processing time, this approach simplifies equipment application and maintains detection accuracy, enhancing practical usability. [ABSTRACT FROM AUTHOR]

Clear‐Air Turbulence (CAT) is associated with wind shear in the vicinity of jet streams in upper atmospheric levels. This turbulence occurs in cloudless regions and causes most weather‐related aircraft accidents. Recent studies have shown that in response to climate change, CAT could significantly increase over certain regions as a consequence of strengthening of jet streams. In this study we use several atmospheric reanalyses and coupled model experiments database to evaluate CAT recent and future changes in the Northern Hemisphere. Several CAT diagnostics are computed to assess the sensitivity of the results to different turbulence representations. A significant positive trend in CAT frequency is found in the reanalyses in different Northern Hemisphere regions over the period 1980–2021. The signal‐to‐noise analysis shows that over North Africa, East Asia and Middle East the increase of CAT occurrence in the last decades is likely attributed to the response to anthropogenic forcing. In contrast, over the North Atlantic and North Pacific the response to external forcing is not detectable due to a weak signal to noise ratio related to large internal variability. Future climate projections show that over several Northern Hemisphere regions, CAT is projected to increase with a high model agreement and independently of the CAT diagnostic used. The largest increase in CAT is projected to occur over East Asia. In the North Atlantic, large uncertainty remains due to lack of model agreement and different results between the various CAT diagnostics. Plain Language Summary: Aircrafts in flight can be subject to Clear‐Air Turbulence (CAT), which is defined as all turbulence that occurs in the atmosphere away from a visible convective activity, and which is particularly difficult to detect by pilots and using on‐board radar. CAT can injure passengers and flight attendants, cause structural damage to planes and induce considerable economic loss. In this study we use several atmospheric reanalyses and coupled model experiments database to evaluate CAT recent and future changes in the Northern Hemisphere. We also compute several CAT diagnostics to evaluate the sensitivity of results to different turbulence representations. Our results show that over several regions in the Northern Hemisphere, in particular East Asia, positive CAT trends are found as a consequence of anthropogenic forcing, indicating that the response of CAT to global warming can be already detectable in the recent decades. Positive trends in CAT frequency are projected to increase for different global warming levels over these regions at aircraft cruising altitudes. Nevertheless, over the North Atlantic region there are still many uncertainties in the response of climate models and also in CAT diagnostics used. The changes in CAT described in this study could have important consequences for aviation safety. Key Points: Atmospheric reanalyses show increases in the frequency of Clear‐Air Turbulence (CAT) in recent decades over several regionsThe increases over some of these regions is attributable to external forcingCAT frequency is projected to increase in the future over East Asia, Middle East, North Africa, North Pacific and North America [ABSTRACT FROM AUTHOR]

In the aftermath of the Germanwings crash in 2015, several regulations have been instituted around pilots' mental health issues and flight safety. One of these (CAT.GEN.MPA.215) stipulates that European operators are to implement a Peer Support Program to encourage pilots' self-referral of mental health issues and identify mental wellbeing issues as early as possible. However, knowledge is scarce regarding how effective these programs are on a range of outcomes. This systematic review aimed to identify articles investigating peer support programs and their effectiveness in preventing and detecting mental health issues, in commercial aviation and other high-risk organizations. A systematic search was performed in three databases, following the structure of the PRISMA guidelines. All articles (2.123) were exported to Rayyan Citation, where the screening process was performed. Four articles met the final inclusion criteria. Overall, the search revealed little empirical evidence of the effectiveness of peer support in detecting and preventing mental health. Although there is limited or no evidence in any direction, the peer support programs seem to be without evident harm and were generally appreciated. The insufficient empirical evidence is nonetheless concerning, with these programs being implemented throughout Europe in such a high-risk context as the aviation industry. The results highlight the importance of more research on peer support in aviation. [ABSTRACT FROM AUTHOR]

To conduct the Turkish adaptation of the Flight Anxiety Situations Questionnaire (FAS) and the Flight Anxiety Modality Questionnaire (FAM). The FAS measures the anxiety levels in different flight situations, while FAM assesses the somatic and cognitive symptoms of anxiety or anticipatory anxiety in different flight situations. The FAS and the FAM have been adapted to different cultures and used in different studies. 645 adults from different regions of Turkey participated in this study (Mage = 25.58, SDage = 10.43, 59.2% women). A Socio-demographic Information Form, the Visual Analog Flight Anxiety Scale (VAFAS), the FAS, the FAM and the State-Trait Anxiety Inventory (STAI) were used for data collection. Exploratory factor analysis showed that the Turkish forms of the FAS and the FAM had similar factor structures to the original forms. The FAS consisted of three factors and the FAM consisted of two factors with factor loadings between.56 and.85. High Cronbach's alpha scores (.78–.97) of the FAS, the FAM and their subscales supported internal consistency reliability. Convergent and discriminant validity of the scales were supported with correlation analysis and independent samples t-test. The Turkish forms of the FAS and the FAM provided psychometrically sound self-report measures of flight anxiety. It is thought that these measures will be useful in clinical assessments, interventions and future cross-cultural research about flight anxiety in the Turkish community. [ABSTRACT FROM AUTHOR]

Ice formation on aircraft surfaces poses significant safety risks, and current detection systems often struggle to provide accurate, real-time predictions. This paper presents the development and comprehensive evaluation of a smart ice control system using a suite of machine learning models. The system utilizes various sensors to detect temperature anomalies and signal potential ice formation. We trained and tested supervised learning models (Logistic Regression, Support Vector Machine, and Random Forest), unsupervised learning models (K-Means Clustering), and neural networks (Multilayer Perceptron) to predict and identify ice formation patterns. The experimental results demonstrate that our smart system, driven by machine learning, accurately predicts ice formation in real time, optimizes deicing processes, and enhances safety while reducing power consumption. This solution holds the potential for improving ice detection accuracy in aviation and other critical industries requiring robust predictive maintenance. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Comparative Politics is the property of Journal of Comparative Politics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Atomic Energy Science & Technology is the property of Editorial Board of Atomic Energy Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Hazards threaten railway safety by their potential to trigger railway accidents, resulting in significant costs and impacting the public's willingness to use railways. Whilst many prior works investigate railway hazards, few offer a holistic view of hazards across jurisdictions and time because the large number of primary sources make synthesising such learnings time consuming and potentially incomplete. The conceptual framework HazardMap is developed to overcome this gap, employing open-sourced Natural Language Processing topic modelling for the automated analysis of textual data from Rail Accident Investigation Branch (RAIB), Australian Transport Safety Bureau (ATSB), National Transportation Safety Board (NTSB) and Transportation Safety Board of Canada (TSB) railway accident reports. The topic modelling depicts the relationships between hazards, railway accidents and investigator recommendations and is further extended and integrated with the existing risk theory and epidemiological accident models. The results allow the different aspects of each hazard to be listed along with the potential combinations of hazards that could trigger railway accidents. Better understanding of the aspects of individual hazards and the relationships between hazards and previous accidents can inform more effective hazard mitigation policies including technical or regulatory interventions. A case study of the risk at level crossings is provided to illustrate how HazardMap works with real-world data. This demonstrates a high degree of coverage within the existing risk management system, indicating the capability to better inform policymaking for managing risks. The primary contributions of the framework proposed are to enable a large amount of knowledge accumulated to be summarised for an intuitive policymaking process, and to allow other railway investigators to leverage lessons learnt across jurisdictions and time with limited human intervention. Future research could apply the technique to road, aviation or maritime accidents. • A framework HazardMap is developed for mapping hazards in the railway system. • A case study of the risk at level crossing is implemented. • Opportunities for practitioners in learning across jurisdiction and time. • Enabling knowledge accumulated to be summarised for policymaking process. [ABSTRACT FROM AUTHOR]

To reveal complex causes of aircraft events, this paper aims to mine association rules between the trigger probability and relative strength via a modified Apriori algorithm. Clustering is adopted for data preprocessing and TF–IDF value calculation. Causative item sets of aircraft events are obtained based on the accident causation 2–4 model and are coded to establish code indicators. By avoiding the use of statistical methodologies to resolve not-a-number (NaN) values for altering the interrelations among causes, an enhancement in the Apriori algorithm is proposed by considering frequent items. By extracting frequent patterns, in this paper, all the association rules that satisfy three perspectives (support, confidence and lift) are determined by constantly generating and pruning candidate item sets. A network graph is used to visualize the association rules between different unsafe events and all types of causes. Finally, 9835 representative pieces of data, including general unsafe events, general incidents and serious incidents from the Southwest Air Traffic Management Bureau, are selected for analysis. The results show that improper energy allocation, poor conflict resolution ability, inadequate onsite management duties, adoption of a luck mentality, and occurrence of controller oversight are highly correlated with general unsafe events, and failure to rectify incorrect recitation is notably correlated with general incidents, while inadequate manual promotion, lack of conflict judgement and insufficient safety management are strongly correlated with serious incidents. This study quantitatively reveals the potential patterns and characteristics of mutual interactions among various types of historical aircraft events and highlights directions for controllable prevention and prediction of aircraft events. [ABSTRACT FROM AUTHOR]

Most of the existing literature on crisis communication focuses on the crisis response immediately following a crisis. There is a dearth of research examining postcrisis communication efforts. Postcrisis communication is especially important in the context of tragic crises, which leave stakeholders deeply affected and traumatized. This paper examines the multifaceted nature of memorials and their significance in postcrisis communication. Using the 2015 Germanwings crash as an illustrative case study, the paper highlights how memorials serve as artifacts of grief, remembrance and celebration of life. Postcrisis communication that centres on victim needs is a keystone to better crisis management. Moreover, I argue that postcrisis communication should facilitate healing by serving the needs of victims, which supersede those of organizations. The paper examines the notions of victim‐centred crisis communication and ethics of care by looking at memorials as artefacts of postcrisis communication. [ABSTRACT FROM AUTHOR]

Over 8000 weather-related aviation accidents in the USA from 2000 to 2020 are investigated, in order to find possible connections between atmospheric instability and severe aviation accidents – defined here as events that recorded serious or fatal injuries. We use the bootstrapped median values for multiple meteorological parameters extracted from North America Regional climate reanalysis for each accident cause. To check the possibility of predicting severe accidents, we applied a logistic regression model containing several meteorological variables as predictands. Results show that approximately 67% of the weather-related severe aviation accidents can be explained by meteorological parameters like relative humidity, temperature, visibility or total cloud fraction. The monthly frequency of weather-related accidents shows a 6-months peak, corresponding to the peak of the convective season in North America. Older pilots (> 60 years) are more likely to be involved in a severe accident during adverse weather, while flight experience seems less relevant. Our study aims to better understand which meteorological variables are more significant in the outcome of severe aviation accidents during adverse meteorological conditions, and to investigate the roles of age and experience in pilots' response during extreme weather. [ABSTRACT FROM AUTHOR]

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

Copyright of Journal of Anbar University for Law & Political Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study investigates the impact of wind shear on the flight dynamics of commercial aircraft where C* and C*U control laws are employed during the approach phase. Given the high incidence of flight accidents during takeoff and landing attributed to wind shear, this research aims to enhance aviation safety by analyzing control law behavior under varying wind shear conditions. A nonlinear flight simulation model was developed, utilizing aerodynamic and engine data from a B737, to explore the aircraft's response to different wind shear intensities. The simulation analysis was used to compare the response of the aircraft with C* and C*U controllers, respectively, under different wind shear, and to evaluate the effectiveness of its stability enhancement in wind shear. It was found that in most cases, the controller can achieve a good stabilization effect, but in some cases of wind fields, the aircraft suffered more significant oscillation. [ABSTRACT FROM AUTHOR]

INTRODUCTION: A gricultural aircraft operations are associated with unique challenges. In particular, these include maintaining awareness of obstacles associated with flight at very low altitudes. Wire strikes are a common cause of accidents in these operations. METHODS: Focus groups were completed during the 2022 Ag Aviation Expo hosted by the National Agricultural Aviation Association with pilots who had experienced wire-strike events (N = 22). The researchers coded the transcripts using a human factors framework. RESULTS: Notably, unplanned "trim passes" were a key stage of flight during wire-strike events. Cognitive risk factors that may have affected their performance included situation awareness, decision-making choices, and pressure to perform. Over half of subjects reported being aware of the wire before collision. Possible prevention strategies include not spraying the field due to safety risks, paying better attention to where they were in the field, and avoiding deviation from the planned route. DISCUSSION: Wire-strike events often occur due to momentary lapses in attention, even when the pilot is already aware of the wire. This study shows that targeted approaches to prevent wire strikes in agricultural aviation operations require addressing a number of cognitive risks and human factors, rather than implementing increased preflight surveillance. These results have implications for preventing future wire-strike accidents based directly on pilot perceptions, both within agricultural operations and general aviation more broadly. [ABSTRACT FROM AUTHOR]

Results are presented from the Rum Creek fire during the California Fire Dynamics Experiment (CalFiDE). An instrumented payload aboard the NOAA Twin Otter (TO) aircraft, which included a scanning micro‐pulsed Doppler lidar (DL) and in situ chemistry packages, was used to address the evolution of a buoyant plume jet (BPJ) and transport dynamics over the southwest corner of the fire between 09/01/2022 and 09/02/2022. An approach previously developed to isolate updrafts was modified to account for the Gaussian core structure when addressing the evolution of the updraft, plume‐top entrainment, lateral entrainment, and the role of fire‐atmosphere interactions on the characteristics of the BPJ during four overpasses. A persistent cross‐valley flow leading up to the BPJ was observed for all four overpasses, with flow enhancement during the second overpass that coincided with changes in the BPJ structure and turbulence characteristics surrounding the BPJ. Length scales and entrainment rates were estimated at the lateral edges and the top of the plume. In the case of the latter, an analytical form of the BPJ profile above the vertical velocity maximum of the updraft was derived using a simplified form of the vertical momentum equation following a partial budget analysis that accounted for plume‐top entrainment and the boundary layer (BL) inversion. Velocity core strength and characteristics were analyzed away from the updraft with similar relationships between depth‐to‐widths of velocity cores found in a forthcoming study focused on wildfire plumes. Plain Language Summary: The goal of the California Fire Dynamics Experiment (CalFiDE) during the fall of 2022 was to survey wildfire dynamics and impacts on air quality over areas historically affected by wildfires. The Rum Creek fire, which occurred west of Medford, Oregon, was one of several fires observed using data collected aboard the NOAA Twin Otter (TO) aircraft. In this study, we focused on a smoke plume at the southwest corner of the fire that featured strong upward motion. Multiple flyovers of this plume led to an analysis of how the plume changed with time, and how the conditions surrounding the plume supported its development. The work presented details the internal structure of the plume and the influence of background winds on the evolution of the plume, which has implications for understanding the transport of smoke away from the fire. Key Points: Airborne Doppler lidars are capable of resolving small scale dynamics over short distances spanning the width of the firelineComplex interactions between fire‐induced updrafts and the surrounding atmosphere can lead to non‐ideal representation of the updraft profileTerrain and fire‐modified winds are important for updraft evolution and transport dynamics [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. [ABSTRACT FROM AUTHOR]

Aircraft icing refers to the accumulation of ice on the surface and components of an aircraft when supercooled water droplets collide with the aircraft above freezing levels (at altitudes at which the temperature is below 0 °C), which requires vigilant monitoring to avert aviation accidents attributable to icing. In response to this imperative, the Weather Radar Center (WRC) of the Korea Meteorological Administration (KMA) has developed a real-time icing detection algorithm. We utilized 3D dual-polarimetric radar variables, 3D atmospheric variables, and aircraft icing data and statistically analyzed these variables within the icing areas determined by aircraft icing data from 2018–2022. An algorithm capable of detecting icing potential areas (icing potential) was formulated by applying these characteristics. Employing this detection algorithm enabled the classification of icing potential into three stages: precipitation, icing caution, and icing warning. The algorithm was validated, demonstrating a notable performance with a probability of detection value of 0.88. The algorithm was applied to three distinct icing cases under varying environmental conditions—frontal, stratiform, and cumuliform clouds—thereby offering real-time observable icing potential across the entire Korean Peninsula. [ABSTRACT FROM AUTHOR]

The quantitative assessment of human error risk in computerized aircraft cockpit need a comprehensive understanding of performance shaping factor (PSF) effects on interaction tasks and the dependency between PSFs. This study employed stepwise logistic regression analysis and mediating effect analysis to explore PSF dependencies based on 872 air accident report data. Among the 14 PSFs of the established PSF taxonomy, five PSFs have significant influences on crew error. Further dependency analysis shows that a significant mediating effect exists in 16 PSF combinations, however, only 8 combinations should be considered in the actual human reliability analysis (HRA) process (indirect effect exceeds 20%). The study proposes an empirical method for identifying and assessing PSF dependencies. The results can be used to develop new or modify existing HRA methods according to the civil aviation context, as well as provide guidance to human error risk prevention and mitigation from broader perspectives in addition to interface facet. [ABSTRACT FROM AUTHOR]

Hub airports typically have multiple parallel runways, requiring aircraft to transfer between them. This increases the risk of runway incursions. End-around taxiways (EATs) mitigate such risk by enabling bypassing without runway crossings. This review summarizes 15 EAT layouts worldwide and presents two classification methods: by configuration (N-type, M-type, Large N-type) and by operational relationship with runways (back-around, runway end-around, start-around). The key benefits of EATs were manifold, including the reduction of runway incursions, controller workload, and delays while improving communication safety, capacity, and efficiency. However, drawbacks such as increased land use, construction costs, and potentially longer taxi times and distances should be considered. Therefore, the optimization of the EAT layout is essential. In pursuit of optimal design, considerations should encompass limiting obstacle surfaces, flight procedures, navigation/lighting facilities, jet blast, and visual obstructions from end-around aircraft to departing aircraft. Notably, challenges arise in reducing distances between EATs and thresholds/ends. The given solutions include displacing thresholds, creating "sunken" lowered elevation EATs, and utilizing terrain shielding instead of metallic visual screens. A case study was introduced to demonstrate the successful improvement of the EAT via sunken EATs and terrain shielding at Guiyang Airport. The conclusion encourages further optimization of EAT layouts that balance safety and efficiency. [ABSTRACT FROM AUTHOR]

The aerospace industry prioritises safety protocols to prevent accidents that can result in injuries, fatalities, or aircraft damage. One of the potential hazards that can occur while manoeuvring aircraft in and out of a hangar is collisions with other aircraft or buildings, which can lead to operational disruption and costly repairs. To tackle this issue, we have developed the Smart Hangar project, which aims to alert personnel of increased risks and prevent incidents from happening. The Smart Hangar project uses computer vision, LiDAR, and ultra-wideband sensors to track all objects and individuals within the hangar space. These data inputs are combined to form a real-time 3D Digital Twin (DT) of the hangar environment. The Active Safety system then uses the DT to perform real-time path planning, collision prediction, and safety alerts for tow truck drivers and hangar personnel. This paper provides a detailed overview of the system architecture, including the technologies used, and highlights the system's performance. By implementing this system, we aim to reduce the risk of accidents in the aerospace industry and increase safety for all personnel involved. Additionally, we identify future research directions for the Smart Hangar project. [ABSTRACT FROM AUTHOR]

As the information technology (IT) industry advances, embedded systems are being applied in various industrial sectors. With the expansion of application areas, there is a growing demand for high-precision, high-specification embedded systems, leading to the increased complexity of embedded software. Consequently, software errors can cause system malfunctions, resulting in accidents such as airplane crashes and the sudden acceleration of cars, leading to significant loss of life and property damage. Therefore, measures to ensure the safety and stability of increasing embedded systems malfunctions are necessary. This paper proposes a system that monitors the operation of target embedded systems in real-time and compares the extracted normal operation current/voltage patterns with the current/voltage data of a target embedded system (TES). It compares the operation data of the TES with automatically generated normal operation patterns by forcibly exposing them. It suggests algorithms for immediately detecting and efficiently recovering from the TES malfunctions. The proposed system applies two algorithms. (a) Monitoring TES current: When a malfunction is detected, a monitoring embedded systme (MES) resets the TES to restore normal operation. If malfunctions persist, it controls TES by using an algorithm to shut it down. Additionally, a proportional integral derivation (PID) control is applied to stabilize the current state. (b) Monitoring TES voltage: If a voltage drop occurs, the MES immediately stops the TES operation to minimize damage. The proposed algorithms were validated through experiments. For a normal TES consuming up to 95 mA, an error detection rate of 20% was applied. The TES was reset if it consumed over 114 mA. It was confirmed that the TES was stopped upon detecting the third malfunction. Regarding voltage, when the normal operating voltage of the system was around 5 V, if the TES operating voltage dropped below 4.3 V, it was detected as a malfunction, and the algorithm to stop the TES operation was validated. [ABSTRACT FROM AUTHOR]

This study investigates the relationship between pilot candidates' self-control, self-efficacy, and training performance in terms of safety climate. Self-efficacy and safety climate are essential for the flight performance of pilots. However, the effect of self-control on flight performance has yet to be studied. In addition, high self-efficacy is always determined as an essential risk for aviation, but this reality has yet to be researched regarding the safety climate. This study employs qualitative and quantitative research techniques. Data are obtained from 244 pilot candidates training in flight schools in Turkey and then analyzed. There is a significant relationship between self-perceptions and flight performance of pilot candidates. Safety climate has a moderator role in the relationship between self-efficacy, self-control, and flight performance. In the second research model, it is determined that there is a significant relationship between safety climate and flight performance. Self-control and self-efficacy of pilot candidates moderate this relationship. Flight schools and airline companies should exert more effort to establish a safety culture within their institutions, particularly for individuals with excessive levels of self-efficacy. Excessive self-efficacy poses a significant potential risk for those who need to perceive safety culture more in their flight school. In addition, the pilot candidates' self-control level should be considered necessary when recruiting them. [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]

The purpose of the research was to create and validate a safety performance decision-making tool to transform a reactive safety model into a predictive, decision-making tool, specific to large, collegiate Title 14 of the Code of Federal Regulations (CFR) Part 141 flight training organizations, to increase safety and aid in operational decision-making. Using Monte Carlo simulation, the study conducted simulation runs based on true operational ranges to simulate the operating conditions possible within large, collegiate CFR Part 141 flight training organizations with varying levels of controllable resources in terms of personnel (Aviation Maintenance Technicians and Instructor Pilots) and expenditures (active flight students and available aircraft). The study compared the output from three different Verification Scenarios. ANOVA testing indicated no significant differences appeared among the three different groups. Four What-if Scenarios were conducted by manipulating the controllable inputs. Changes to the controllable inputs are reflected by variations to the outputs demonstrating the utility and potential for the safety performance decision-making tool. The outputs could be utilized by safety personnel and administrators to make more informed safety-related decisions without expending unnecessary resources. [ABSTRACT FROM AUTHOR]

Purpose: About 70% of all aircraft accidents are caused by human–machine interaction, thus identifying and quantifying performance shaping factors is a significant challenge in the study of human reliability. An information flow field model of human–machine interaction is put forward to help better pinpoint the factors influencing performance and to make up for the lack of a model of information flow and feedback processes in the aircraft cockpit. To enhance the efficacy of the human–machine interaction, this paper aims to examine the important coupling factors in the system using the findings of the simulation. Design/methodology/approach: The performance-shaping factors were retrieved from the model, which was created to thoroughly describe the information flow. The coupling degree between the performance shaping factors was calculated, and simulation and sensitivity analysis are based on system dynamics. Findings: The results show that the efficacy of human–computer interaction is significantly influenced by individual important factors and coupling factors. To decrease the frequency of accidents after seven hours, attention should be paid to these factors. Originality/value: The novelty of this work lies in proposing a theoretical model of cockpit information flow and using system dynamics to analyse the effect of the factors in the human–machine loop on human–machine efficacy. [ABSTRACT FROM AUTHOR]

In the context of improving aircraft safety, this work focuses on creating and testing a graphene-based ice detection system in an environmental chamber. This research is driven by the need for more accurate and efficient ice detection methods, which are crucial in mitigating in-flight icing hazards. The methodology employed involves testing flat graphene-based sensors in a controlled environment, simulating a variety of climatic conditions that could be experienced in an aircraft during its entire flight. The environmental chamber enabled precise manipulation of temperature and humidity levels, thereby providing a realistic and comprehensive test bed for sensor performance evaluation. The results were significant, revealing the graphene sensors' heightened sensitivity and rapid response to the subtle changes in environmental conditions, especially the critical phase transition from water to ice. This sensitivity is the key to detecting ice formation at its onset, a critical requirement for aviation safety. The study concludes that graphene-based sensors tested under varied and controlled atmospheric conditions exhibit a remarkable potential to enhance ice detection systems for aircraft. Their lightweight, efficient, and highly responsive nature makes them a superior alternative to traditional ice detection technologies, paving the way for more advanced and reliable aircraft safety solutions. [ABSTRACT FROM AUTHOR]

Aircraft icing has historically been a critical cause of airplane crashes. The electro-impulse de-icing system has a wide range of applications in aircraft de-icing due to its lightweight design, low energy consumption, high efficiency, and other advantages. However, there has been little study into accurate wing electric-impulse de-icing simulation methods and the parameters impacting de-icing efficacy. Based on the damage mechanics principle and considering the influence mechanisms of interface debonding and ice fracture on ice shedding, this paper establishes a more accurate numerical model of wing electric-impulse de-icing using the Cohesive Zone Model (CZM). It simulates the process of electric-impulse de-icing at the leading edge of the NACA 0012 wing. The numerical results are compared to the experimental results, revealing that the constructed wing electro-impulse de-icing numerical model is superior. Lastly, the effects of varying ice–skin interface shear adhesion strengths, doubler loading positions, and impulse sequences on de-icing effectiveness were studied. The de-icing rate is a quantitative description of the electro-impulse's de-icing action, defined in the numerical model as the ratio of cohesive element deletions to the total elements at the ice–skin interface. The findings reveal that varying shear adhesion strengths at the ice–skin interface significantly impact the de-icing effect. The de-icing rate steadily falls with increasing shear adhesion strength, from 66% to 56%. When two, four, and seven impulses were applied to doubler two, the de-icing rates were 59%, 71%, and 71%, respectively, significantly increasing the de-icing efficiency compared to when impulses were applied to doubler one. Doubler one and two impulse responses are overlaid differently depending on the impulse sequences, resulting in varying de-icing rates. When the impulse sequence is 20 ms, the superposition results are optimal, and the de-icing rate reaches 100%. These studies can guide the development and implementation of a wing electric-impulse de-icing system. [ABSTRACT FROM AUTHOR]

The paper explores the potential to enhance aviation safety, particularly in militarized regions, by outfitting aircraft with Side Looking Airborne Radar (SLAR) and employing space-time adaptive processing (STAP) algorithms. The research objective revolves around implementing a model of side-looking airborne radar and the corresponding STAP algorithms. This technology enables the detection of slow-moving targets amidst strong interference, encompassing both passive (clutter) and active (jammer) elements. Slow-moving targets relative to the aircraft's speed include tanks, combat vehicles, command vehicles, artillery, and logistical assets of enemy forces. The theoretical framework of space-time adaptive processing is presented, elucidating the sequential steps of the classical Sample Matrix Inversion Space-Time Adaptive Processing (SMI STAP) algorithm. The paper underscores the significance of characteristic parameters delineating a linear STAP processor. The proposed solution facilitates the detection of enemy combat measures and enhances aviation safety. It outlines a radar model installed beneath the aircraft's fuselage and elucidates algorithms for space-time adaptive processing of radar signals. The simulations conducted within the article were executed using the MATLAB environment. The simulation results indeed suggest that the proposed solution holds promise for deployment in equipping aircraft of one's own military and those engaged in operations within conflict zones. This paper stands as one of the few contributions in the literature addressing the augmentation of aircraft safety through radar and space-time adaptive processing. [ABSTRACT FROM AUTHOR]