Aircraft Incidents Research Articles

Aircraft Electrothermal Pulse Deicing

Abstract Ice formation and accumulation on aircraft is a major problem in aviation. Icing is directly responsible for aircraft incidents, limiting the safety of air travel and requiring expensive, and sometimes ineffective deicing strategies. Furthermore, electrification of aircraft platforms leads to difficulties with integration of legacy deicing methods such as pneumatic boots. In this work, we study electrothermal pulse deicing capable of efficient and rapid removal of ice from aircraft wings. The pulse approach enables the efficient melting of a thin (<100 μm) ice layer on the wing surface to limit parasitic heat losses. Only the interface is melted, with the rest of the ice sliding on the melt lubrication layer due to aerodynamic forces. To study pulse deicing, we developed a transient thermal-hydrodynamic numerical model that accounts for multiple phases and materials, specific and latent heating effects, melt layer hydrodynamics, as well as boundary layer effects. To identify optimal deicing strategies, we use our model to study the effects of heater thickness (50 μm < th < 1 mm), substrate electrical insulation thickness (10 μm < ti < 1 mm), pulse duration (0.4 s < Δtpulse < 4.5 s), and pulse energy. Optimum operating points are identified for large (Boeing-747), midsize (Embraer-E175), and small (Cessna-172) aircraft. The scale-dependent thermal-hydraulic model results are used to estimate input conditions required for deicing and integrated into an electrical model considering energy storage, power electronics, integration, and layout, to achieve overall volumetric and gravimetric power density optimization.

Relationship between dependability and flight safety

This paper presents methods of dependability assessment and safety of aeronautical engineering selected from scientific achievements of the Air Force Institute of Technology. Studying dependability and safety was preceded by the implementation of the computer system used for the support of the operational process and consisting of the following modules: recording, database and module for processing of operational information. The processing system was provided with the developed models and assessment algorithms. The dependability and safety of military aircraft are assessed by registering defects appropriately classified into causes and effects that determine certain factors and their correlation with aircraft incidents and accidents. A significant assessment factor is a failure flux parameter, damageability, and probability of performing an aircraft operation with or without failure to the aircraft. Favourable flight conditions and the occurring disruptions are taken into consideration. Correlation assessment between failure frequency and the probability of favourable operations enables us to evaluate the relationship between dependability and flight safety.

AKAASH: A realizable authentication, key agreement, and secure handover approach for controller-pilot data link communications

Controller-Pilot Data Link Communications (CPDLC) are rapidly replacing voice-based Air Traffic Control (ATC) communications worldwide. Being digital, CPDLC is highly resilient and bandwidth efficient, which makes it the best choice for traffic-congested airports. Although CPDLC initially seems to be a perfect solution for modern-day ATC operations, it suffers from serious security issues. For instance, eavesdropping, spoofing, man-in-the-middle, message replay, impersonation attacks, etc. Cyber attacks on the aviation communication network could be hazardous, leading to fatal aircraft incidents and causing damage to individuals, service providers, and the aviation industry. Therefore, we propose a new security model called AKAASH, enabling several paramount security services, such as efficient and robust mutual authentication, key establishment, and a secure handover approach for the CPDLC-enabled aviation communication network. We implement the approach on hardware to examine the practicality of the proposed approach and verify its computational and communication efficiency and efficacy. We investigate the robustness of AKAASH through formal (proverif) and informal security analysis. The analysis reveals that the AKAASH adheres to the CPDLC standards and can easily integrate into the CPDLC framework.

Analyzing Emerging Challenges for Data-Driven Predictive Aircraft Maintenance Using Agent-Based Modeling and Hazard Identification

The increasing use of on-board sensor monitoring and data-driven algorithms has stimulated the recent shift to data-driven predictive maintenance for aircraft. This paper discusses emerging challenges for data-driven predictive aircraft maintenance. We identify new hazards associated with the introduction of data-driven technologies into aircraft maintenance using a structured brainstorming conducted with a panel of maintenance experts. This brainstorming is facilitated by a prior modeling of the aircraft maintenance process as an agent-based model. As a result, we identify 20 hazards associated with data-driven predictive aircraft maintenance. We validate these hazards in the context of maintenance-related aircraft incidents that occurred between 2008 and 2013. Based on our findings, the main challenges identified for data-driven predictive maintenance are: (i) improving the reliability of the condition monitoring systems and diagnostics/prognostics algorithms, (ii) ensuring timely and accurate communication between the agents, and (iii) building the stakeholders’ trust in the new data-driven technologies.

Methodological approach to the quantitative assessment of risk caused by a collision between birds and aircraft

Since 2011 worldwide, and since 2014 in Russia, a trend has revealed a steady increase in the number of aviation events caused by a collision between birds and civil aircraft. The article presents the results of the bird aircraft strike hazard (BASH) analysis in commercial aviation in Russia and proposes a methodological approach to the quantitative risk assessment caused by bird strikes. The process of the quantitative assessment of the risk level resulted from bird strikes, implemented within the framework of the UTair Aviation Safety Management System on the results of 2021, is described. The estimation of the probability is provided for aviation events of all the possible severity levels: an aircraft incident, serious accident, major accident, fatal accident. In the empirically obtained formulas for the indirect probability estimation of aircraft occurrences, the conditional probability of aviation events of greater severity was used, if events of lower severity took place, in accordance with the ratios in the previously obtained “risk pyramid” of commercial aviation in Russia. Solving the problem of quantifying the risk level contributes to increasing the assessment reliability due to the transition from a three-level risk ranking (“acceptable”, “tolerable”, “unacceptable”) to a twenty-five-level ranking and makes it possible to evaluate the effectiveness of corrective actions aimed at reducing risk by comparing the quantitively assessed level of residual risk with the original one; to optimize risk management according to the effectiveness criterion of corrective actions according to the criterion “increment in the risk level/cost”, to identify high-risk aerodromes in advance and plan unscheduled checks of ornithological aerodrome support; to develop and implement preventive corrective measures to improve ornithological support at high-risk aerodromes; to update periodically the recommendations to flight personnel in the event of a bird strike and a threat of collision (especially during takeoff and landing). The proposed methodological approach ensures the functioning of the risk management loop in the flight safety management system of any aircraft operator when performing a monthly risk analysis associated with seasonal and regional BASH in Russia.

Effects of the Federal Aviation Administration's Compliance Program on aircraft incidents and accidents

• Restorative justice-based policies in aviation may be unsafe. • The FAA’s Compliance Program may reduce aviation safety. • Population-level data was evaluated using GLARMA modeling. • An increase in aircraft incidents and accidents resulted from the FAA’s Compliance Program. • A decrease in punishment may affect human behavioral responses. A novel enforcement policy based on restorative justice principles was implemented by the United States Federal Aviation Administration (FAA) in 2015. In this study, interrupted time series regression analyses using generalized linear autoregressive moving average (GLARMA) models were used to analyze FAA investigated incident and accident counts, runway incursion caused by pilot deviation, and National Transport Safety Board (NTSB) accident count data from June 2010 to September 2020. An association was observed between the change in FAA’s enforcement policy and the increase in aircraft incidents, accidents, and runway incursions post-intervention (2015–2020). These adverse safety outcomes appear to be directly related to this policy change. Results highlight the risk of moving away from punishment as a means of reinforcing safe behavior and the need for careful theory-based implementation of alternative approaches.

Skill set issues in aircraft maintenance from industrial revolution 4.0 context: A document analytics survey

BACKGROUND: Aircraft maintenance and repair are critical tasks in the aviation industry for improved aircraft service and safety. Many articles and reports describe personnel factor and skill issues contribute to many aircraft incidents. Aircraft maintenance personnel needs to level up their skill set to match with task requirements in the setting of Industry Revolution 4.0. OBJECTIVE: The aim of this paper is to investigate document set that describe human errors and skill mismatch as a human factor in aircraft incidents and problems. It also discusses on the findings and management of the aircraft maintenance skill issues. METHODS: The study uses a document analytics tool to assess a set of online articles that discuss aircraft maintenance incidents and skill mismatch issues. The experiment is divided into four (4) modules: (i) collection of online articles and reports, (ii) document pre-processing, (iii) text analytics, and (iv) visualisation. RESULTS: The experiment’s results show that the majority of documents discuss aircraft maintenance, skill mismatch, and training gaps. CONCLUSION: We can conclude that the document dataset primarily discusses aircraft maintenance and skill set issues using the document analytics. Consequently, the management of aircraft maintenance workforce skill set issues by having initiatives for upskilling and reskilling. Furthermore, firms should foster a culture of continuous learning and develop a mindset among their employees that allows them to adapt to new technologies and information in aircraft maintenance.

Setting up new standards in aviation industry with the help of artificial intelligent – machine learning application

In these times, dominated by innovation, technology is an important asset in optimizing maintenance, aircraft operations and even the investigation process of aviation accidents, with unprecedented results so far. All the information related to an aircraft, generated over time, can be included in a database, in order to be analyzed for better technical insights. The same approach can be applied in analyzing evidence and reports generated after an aircraft accident occurred. Aircraft investigation involves tones of hard-working hours and evidence analysis. This research aims to identify a new tool to improve the investigation process of aircraft incidents caused by human factors errors. Using artificial intelligence to process the resulted evidence during the aircraft accidents investigation, will shed light on the root cause of the incident much faster. Accelerating an investigation means huge benefits for all parties involved. In this sense, a proof-of-concept software has been developed to emphasize the power of artificial intelligent in the aircraft accidents investigation. Using machine learning algorithms, a program was trained with data, to develop an application capable of automatically determining the root cause of an accident based on witness statements. All data was derived from the Aviation Safety Reporting System database from the U.S, which was queried for incidents, occurred between 2000 and 2020. This application is not only about automating a stage in an aircraft accident investigation, is rather about setting up new standards in aviation industry with the help of artificial intelligence.

Systemic approach to an airport incident investigation

The paper describes the practical use of the system approach to the incident investigation at the international airport and why the airport focuses on new methods in safety engineering. The approach is shown on the test investigation of aircraft incident using the CAST methodology based on the STAMP model describing investigation steps and overall context. The outcome is compared with the traditional approach to investigation, and causal factors and safety recommendations are determined. A systemic approach significantly influences these recommendations positively. Traditional methods are proven over the years, but it is beneficial to complement them with a new approach to get the best possible lessons learned and the most effective recommendations and safety actions.

Investigating air travellers’ travel motivation during a pandemic crisis

The growth of the air transport industry has been accompanied by various crises including aircraft incidents and accidents, terrorist attacks, and pandemics such as COVID-19. These crises to a great extent affect air travelers' motivation, which in turn affects the air travel demand that justifies airlines' legitimate existence and sustainability. However, there has been relatively little research into understanding air travelers' motivation during and after such crises, despite some studies having been conducted in the tourism domain to understand the motivation of tourists to travel to specific destinations. An enhanced knowledge in this field is important and would benefit the airline industry, which is facing increasing competition from other transportation modes as well online conferencing technologies. By applying the Push and Pull Factor model, this study has sought to identify the travel motivation and further determine whether Push factors have any positive influence on Pull factors. To this end, 760 questionnaires were collected from Taiwan. Both descriptive and inferential statistical analyses were conducted to test the hypotheses. Our findings reveal that the Destination image remains the most influential Pull factor, while Aviation-specific products and services is the least attractive Pull factor. Self-realization/achievement topped the rankings for the Push factors, while Flying experience was a selling point in its own right among the Push factors, although it was not as appealing as anticipated. The millennium generation, fewer frequent flyers and low-income consumers are more likely to take advantage of flying deals. This paper suggests that a more collaborative approach between airlines, airports and destination organizations could be adopted to design and promote tailor-made aviation and travel products to stimulate segmented consumers’ demand for air travel during crises. Effective marketing strategies need to be in place to promote the specially-designed travel products.

Examining pragmatic failure and other language-related risks in global aviation

PurposeThe purpose of this research is to investigate the pragmatic failure and other language-related risks between pilots and air traffic controllers in intercultural aviation communication. The paper attempts to provide recommendations for the minimization of these risks, thereby improving aviation safety by reducing the rate of aviation incidents and accidents. Pragmatic failure refers to the miscomprehension of intended pragmatic meaning. As opposed to semantic meaning, it depends on the context and is highly influenced by culture.Design/methodology/approachThe risk of pragmatic failure in aviation is presented hypothetically, and examples of language-related communication failure in air-to-ground communication between pilots and air traffic controllers (ATCOs) involving language are examined, including an example involving pragmatic failure. A questionnaire has been developed to survey pilots and ATCOs who communicate over radiotelephony. Results from 212 respondents are presented and conclusions are drawn.FindingsThe authors propose, based on linguistic theory and the results of this survey, that native English-speaking aviation operators gain more familiarity with the inner workings of the English language, in particular regarding the difference between semantic and pragmatic meaning. They benefit from this awareness whenever communicating with people of other cultures to develop the valuable skill of focusing on semantic meaning while avoiding adding pragmatic meaning. This minimizes the potential of misunderstanding when an emergency arises that cannot be dealt with through the International Civil Aviation Organization standard phraseology and when the listener of this message is someone from a different culture.Practical implicationsLanguage and communication are the main tools that play a vital role in reducing the rate of aircraft incidents and accidents. In aviation, pilots and ATCOs are neither in face-to-face contact nor have a video speech interface between them while communicating with each other. Their communications are conducted entirely through radio messages using a specialized language designed to make communication as accurate and efficient as possible. This study, therefore, is important in terms of investigating the risks of pragmatic failure and of language errors in general between pilots and air traffic controllers. This research will be a useful guide for designing training for operators (pilots and ATCOs) as well.Originality/valueThe main focus of the study is to investigate reasons for pragmatic failure and other language-related causes of misunderstanding between pilots and air traffic controllers over air-to-ground communication. To illustrate these roles, a questionnaire has been developed for pilots and ATCOs who communicate over aeronautical radiotelephony and examples of aircraft accidents were given.

Towards building a speciesspecific risk model for mammal-aircraft strikes

Wildlife strikes are a significant issue in the aviation industry, especially strikes with medium- to large-sized mammals, which pose a high risk of damage to aircraft and human safety. Despite the identified threat that mammals can pose to aircraft, few works have been published on ways to rank and predict the risk of mammalian species to aircraft. This study used remote camera trap data collected from an array of wildlife camera traps at the Prince George International Airport (YXS), Prince George, British Columbia, Canada, to calculate strike risk for various species of mammals involved in runway incidents between January 2012 and December 2018. Carnivores such as red foxes and coyotes were found to be the highest risk mammal species at YXS, but foxes were found airside infrequently compared to coyotes. Binary logistic regression modelling was used in an attempt to predict variables leading to runway incidents with coyotes at YXS. The highest supported logistic regression model predicting coyote incidents included the variables ‘weekday’, ‘month’ and ‘season’. Although data from camera traps did not help to predict incidents, trend data collected from camera traps mirrored coyote incident data, suggesting that camera traps are useful for capturing times of the day and seasons of the year in which coyotes are active at the airport. Suggestions are provided as to how cameras might be used to track the movement of animals more accurately and what other data could be useful in helping to build risk assessments and models to predict aircraft incidents with mammals of interest.

Development and Implementation of a Framework for Aerospace Vehicle Reasoning (FAVER)

This paper discusses the development and implementation of the architecture of a Framework for Aerospace Vehicle Reasoning, `FAVER'. Integrated Vehicle Health Management systems require a holistic view of the aircraft to isolate faults cascading between aircraft systems. FAVER is a system-agnostic framework developed to isolate such propagating faults by incorporating Digital Twins (DTs) and reasoning techniques. The flexibility of FAVER to work with different types and scales of DTs and diagnostics, and its ability to adapt and expand for previously unknown faults and new systems are demonstrated in this paper. The paper also shows the novel combination of relationship matrix and fault attributes database used to structure the knowledge of FAVER's expert system. The paper provides the working mechanism of FAVER's reasoning and its ability to isolate faults at the system level, identify their root causes, and predict the cascading effects at the vehicle level. Four aircraft systems are used for demonstration purposes: i) the Electrical Power System, ii) the Fuel System, iii) the Engine, and iv) the Environmental Control System, and the use case scenarios are adapted from real aircraft incidents. The paper also discusses the pros and cons of FAVER's reasoning via demonstrations and evaluates the performance of FAVER's reasoning through a comparative study with a supervised neural network model.

Failing And Not Falling (F&!F): Data-Enabled Classification Learning of Aircraft Accidents and Incidents

Journey by aircraft is the only option for long-distance transportation and also one of the frequently used modes of transportation of passengers. As a result, safety of passengers and efficiency of the aircraft depend on maintaining efficient running conditions. Although many safety standards are followed in the design of the aircraft, and thus there are fewer accidents, it is necessary to perform a thorough analysis to avoid risks that may occur during flight time. In the present work, we propose a maintenance strategy, Failing And Not Falling (F&!F), based on the Federal Aviation Administration (FAA) data in the USA. We work with the dataset of Boeing 737. The data consists of 72 features with 137,236 records which describe an aircraft accident or incident. These features are used to predict whether an incident will be identified during aircraft maintenance or during aircraft operation and what specific type of incident will occur. The prediction method is based on the integration of a decision tree and a unique neural network at each node of the decision tree. The results obtained using different architectures show how deep the neural networks should be, how to identify the relevant features, and the success of combining decision trees and neural networks. Moreover, the neural networks and the decision tree approach also successfully identified the important features of maintenance. This method can be used for the maintenance of any data in multiple domains.

The Fractographic Investigation of an Aeroengine Accessory Gearbox Quill Shaft

Abstract This paper analyzes the fracture of the quill shaft. An investigation of a twin-engine trainer aircraft incident has been reported. The incident occurred due to the right electric generator out and low oil pressure. The main failure based on the warnings and the subsequent incident was identified. The failure involved the fatigue fracture of the quill shaft on the J85 turbojet engine's accessory drive gearbox (ADG) and Input Drive Assembly (IDA). It was determined that the fracture had been originated by the torsional loads impacting the quill shaft that connects the ADG and IDA. The quill shaft was broken as the loads excessed the limit values designed by the manufacturer as a system protection part. Although the main failure was successfully identified, further analysis regarding the reaching to the triggering cause of the fracture was performed. Through the detailed fractographic and metallographic studies, the root-cause of the fracture was determined as the misalignment of the quill shaft between ADG as the driving unit and IDA as the driver unit.

Accident of a civil passenger aircraft at a military airfield: The Casevac experience

Introduction: There are many civil airports in India wherein the airfield and flying operations are controlled by the military whereas, the Airports Authority of India (AAI) controls the civil terminal. Accident of a civil aircraft on such a base poses unique challenges. This paper discusses the medical contingency plan of a Naval Air Station to deal with civil aircraft crashes based on a civil aircraft incident. Case Details: In the early morning of late Dec in 2016, a Mumbai bound civil flight (Boeing 737) took off from an Indian Navy controlled airfield. While initiating the take-off roll from RW, it veered off the runway towards right and came to halt along the perimeter road 230 m north of the runway edge, on hard rocky ground. There were 154 passengers and 7 crew members who were evacuated from the aircraft, through emergency chutes. Few passengers escaped through the over wing hatches. Twenty passengers sustained injuries, mostly involving the lower limbs. This was primarily due to jumping on hard rocky ground and falling and tripping on rocks while moving away from the aircraft. An analysis was done to understand the limitations on the existing medical contingency plan. Discussion: The ICAO Airport Services Manual Part 7 on Airport Emergency Planning (Doc 9137-AN/898 Part 7) is the guiding reference for all airports on Airport Disaster and Planning. The Medical Services portion delineates clearly the role of the Medical Aid Providers. In the instant case, the medical department had successfully handled the casualty evacuation and their medical management. SOP and the existing medical contingencies were effectively used. A post-accident analysis in the instant case revealed that 17 out of 25 checklist points were satisfied. The lessons learned from the incident have been discussed in the paper.

Adhesion behavior of calcia–magnesia–alumino–silicates on gadolinia-yttria-stabilized zirconia composite thermal barrier coatings

Abstract

Persistent and emerging hazards contributing to work-related fatalities in Alaska.

Workers in Alaska have an elevated risk of dying on the job compared to workers in the rest of the United States. The purpose of this study was to measure and describe the trend in fatalities during the 15-year period 2004 to 2018, and to identify lingering and emerging hazards that result in fatalities. Data on fatal work-related injuries in Alaska during 2004 to 2018 were obtained from the Alaska Occupational Injury Surveillance System. Descriptive statistics were calculated to identify fatality characteristics. Fatality rates were expressed as the number of deaths per 100 000 workers, and Poisson regression was used to measure the trend during the study period. During 2004 to 2018, there were 517 work-related fatalities in Alaska. The average annual risk of fatalities during the 15-year period was 9.6 per 100 000 workers, with no significant trend. The leading events or exposures resulting in fatal injuries to workers in Alaska during 2004 to 2018 were water vehicle incidents (145, 28.0%), aircraft incidents (105, 20.3%), and suicides (46, 8.9%). The number of suicides and homicides at work increased substantially during the 15-year period. While deaths due to water vehicle incidents have substantially decreased, they still represent a major component of Alaska's work-related fatality profile. Aviation safety continues to be an area of concern in Alaska. Unintentional drug overdoses at work, as well as workplace violence in the form of suicides and homicides, represent emerging issues that need the attention of Alaskan occupational safety stakeholders. These findings can inform and direct fatality prevention research and practice.

Upaya Pengelolaan Fatigue Pada Penerbang Dengan Aktivitas Fisik, Latihan Fisik Dan Waktu Tidur

Fatigue adalah kondisi fisiologis yang ditandai dengan penurunan kapabilitas performa fisik dan mental akibat kehilangan tidur atau terjaga berkepanjangan, perubahan irama sirkadian dan beban kerja yang dapat mengganggu kewaspadaan dan kemampuan personil penerbangan dalam mengoperasikan pesawat atau tugas penerbangan dengan selamat. Insiden atau kecelakaan penerbangan dapat timbul akibat kesalahan di tingkat individu (penerbang atau awak pesawat lainnya), dimana fatigue menjadi salah satu faktor penyebab utama.International Civil Aviation Organization (ICAO) telah merekomendasikan Fatigue Risk Management System (FRMS) kepada negara-negara anggotanya, termasuk Indonesia. FRMS ini merupakan suatu sistem adalah suatu sistim pengawasan dan pengelolaan faktor-faktor risiko terkait kelelahan berbasis bukti, yang dilakukan secara berkesinambungan. Di Indonesia saat ini belum banyak maskapai yang menerapkan FRMS. Sebagai upaya lain untuk mengelola fatigue di penerbang, maka dibutuhkan panduan langkah-langkah praktis untuk mengelola faktor risiko fatigue di penerbang, khususnya terkait aktivitas fisik, aktivitas di waktu senggang atau istirahat dan pengaturan waktu tidur.Buku Panduan Praktis Pengelolaan Fatigue bagi Penerbang dengan Aktivitas Fisik, Latihan Fisik dan Waktu Tidur ditargetkan untuk menjadi acuan pengelolaan fatigue bagi penerbang, maskapai dan dapat menjadi rekomendasi bagi pemangku kebijakan untuk dapat dijadikan bagian dari prosedur keselamatan penerbangan di Indonesia.

The effect of management practices on aircraft incidents

Many models have been put forward in order to examine the human factors in aircraft accidents and incidents. Human Factors Analysis and Classification System (HFACS) which is the most widely used in literature is one of these models. HFACS is based on Reason's Swiss Cheese Model. The biggest disadvantage of the Reason's model is its post-accident applicability. Mostly HFACS aviation applications are usually based on accident data. This is a reagent (result-focused) approach. In this study, however, HFACS which is an improved version of Reason's model, was applied to aircraft incidents that did not result in an accident. This is a proactive approach. Thus, with this approach, the biggest disadvantage of Reason's model is turned into an advantage. In addition, a realistic application of this approach has been demonstrated in this study, focusing on aircraft incidents that took place between 2000 and 2018. The year 2000 forms a milestone in the manufacture of more technically advanced aircraft models which significantly reduced occurrence of technical errors in aircrafts, hence the choice of 2000 as base year. A total of 328 aircraft incident reports from the National Transportation Safety Board (NTSB) database were studied and among these reports cockpit crew related incidents were analyzed using HFACS. As a result of the analyzes, the root causes of incidents have been identified. In addition, unlike traditional HFACS analysis, the relationship between errors occurred at management levels of HFACS and the unsafe acts of the cockpit crew in aircraft incidents was statistically revealed.