Search Results (26)

Wireless sensor networks provide a solution for structural health monitoring of aviation pipelines. In the installation environment of aviation pipelines, widespread vibrations can be utilized to extract energy through vibration energy harvesting technology to achieve self-powering of sensors. This study analyzed the vibration characteristics of aviation pipeline structures. The vibration characteristics and influencing factors of typical aviation pipeline structures were obtained through simulations and experiments. An N-shaped symmetric vibration energy harvester was designed considering the limited space in aviation pipeline structures. To improve the efficiency of electrical energy extraction from the vibration energy harvester, expand its operating frequency band, and achieve efficient vibration energy harvesting, this study first analyzed its natural frequency characteristics through theoretical analysis. Finite element simulation software was then used to analyze the effects of the external excitation acceleration direction, mass and combination of counterweights, piezoelectric sheet length, and piezoelectric material placement on the output power of the energy harvester. The structural parameters of the vibration energy harvester were optimized, and the optimal working conditions were determined. The experimental results indicate that the N-shaped symmetric vibration energy harvester designed and optimized in this study improves the efficiency of vibration energy harvesting and can be arranged in the limited space of aviation pipeline structures. It achieves efficient energy harvesting under multi-modal conditions, different excitation directions, and a wide operating frequency band, thus meeting the practical application requirement and engineering feasibility of aircraft design. Full article

In the rapidly advancing era of intelligent technology, flexible strain sensors are emerging as a key component in wearable electronics. Laser-induced graphene (LIG) stands out as a promising fabrication method due to its rapid processing, environmental sustainability, low cost, and superior physicochemical properties. However, the stretchability and conformability of LIG are often limited by the substrate material, hindering its application in scenarios requiring high deformation. To address this issue, we propose a high-performance flexible and stretchable strain sensor fabricated by generating graphene on a polyimide (PI) substrate using laser induction and subsequently transferred onto a polydimethylsiloxane (PDMS). The resultant sensor demonstrates an ultra-low detection limit (0.1%), a rapid response time (150 ms), a wide strain range (40%), and retains stable performance after 1000 stretching cycles. Notably, this sensor has been successfully applied to the real-time monitoring of civil aviation test pilots during flight for the first time, enabling the accurate detection of physiological signals such as pulse, hand movements, and blink frequency. This study introduces a unique and innovative solution for the real-time health monitoring of civil aviation test pilots, with significant implications for enhancing flight safety. Full article

The adoption of chrome-free anodizing and sealing systems for aluminum alloys, particularly AA2024, is gaining prominence due to environmental and health concerns associated with traditional Cr(VI)-based processes. This study evaluates the environmental and economic impacts of sulfuric acid anodizing (SAA) combined with sealing based on fluorozirconate, molybdate, and cerate. Comparative analyses were conducted against conventional Cr(VI) systems and SAA with Cr(III) sealing, focusing on corrosion resistance, energy consumption, washing steps and material flows. The entire anodizing process was examined, including pretreatment, anodization, and sealing. Electrochemical analyses and surface characterization through SEM/EDS, FIB, and XPS were conducted. The results demonstrate that the chromium-free system offers competitive corrosion resistance while significantly reducing environmental and economic costs. Furthermore, fluorozirconate, molybdate, and cerate-based post-treatments broaden its application spectrum in corrosion science and warrant further exploration. However, adopting new sealing technologies in aerospace requires extensive certification involving corrosion resistance, durability assessments, and stringent environmental simulations. Compliance with regulatory standards set by the FAA (Federal Aviation Administration) and EASA (European Union Aviation Safety Agency) necessitates thorough documentation, third-party validation, and testing to ensure safety and performance before industrial implementation. These challenges underscore the complexity of transitioning to more sustainable anodizing and sealing technologies in the aerospace industry. Full article

This study presents the development of a real-time simulation model for electromechanical actuators tailored to a hybrid iron bird for next-generation regional turboprop aircraft. This iron bird is aimed at integrating real and virtual components, enabling advanced validation of flight control systems while balancing risk and cost. The mathematical models of actuators needed for the development and operation of the iron bird must comply with stringent requirements, especially in terms of computational cost. A novel two-step iterative methodology is proposed, combining bottom-up and top-down approaches. This process begins with simplified low-fidelity models. Then, the models are incrementally refined to capture complex dynamics while maintaining computational efficiency. Using the proposed approach, the computational time of the real-time model remained almost unvaried and consistent with the sampling frequency, while the number of state variables and the range of described phenomena grew significantly. The real-time model is validated against simulated data from a reference high-fidelity model and experimental data, achieving excellent agreement while reducing the computational time by 93%. The enhanced model incorporates selected failure modes equivalent models regarding the electric motor, power drive unit, and mechanical transmission, supporting possible future prognostics and health management (PHM) applications. These results showcase a scalable solution for integrating electromechanical actuation in modern aerospace systems, paving the way for full virtual iron birds and greener aviation technologies. Full article

Investigations of aviation accidents are based on provisions of the International Civil Aviation Organization (ICAO) Annex 13 agreement. A safety recommendation may be addressed to international aviation organizations, such as the European Aviation Safety Agency (EASA) and the ICAO, by the Accident Investigation Agency of any country, following a safety investigation into an occurrence. This process also promotes learning from smaller aviation accidents internationally. This article highlights two relatively small aviation accidents in Finland from 2016 and 2021, respectively, both of which fall under general aviation and have led to significant aeromedical safety recommendations for the EASA and the ICAO. In the 2016 accident, a general aviation pilot, who had previously suffered heart attacks, suffered another heart attack and died shortly after landing. This incident led to a recommendation issued to EASA calling for additional training of aeromedical officers in aeromedical risk assessment on pre-existing health conditions. The 2021 accident involved an elderly general aviation pilot who became incapacitated due to health issues. The recommendations resulting from this investigation were brought further to the ICAO and EASA in order for them to emphasize the importance of the age of a pilot in current aviation health assessment guidelines. Full article

This work describes the collaboration practices of a community of interest in the UK that brings together cybersecurity professionals with a shared interest in improving supply chain cybersecurity for Operational Technology (OT) environments. This research emphasizes the need for collective responsibility between organizations and provides a set of principles for adopting a code of practice and partnership approach to supply chain cybersecurity. This work has enabled cybersecurity experience from several critical infrastructure sectors, including energy, rail, aviation, water, health, and food, to analyze the uptake and practical use of existing supply chain guidance, identifying gaps and challenges. The community has examined touch points with the supply chain and identified improvements related to the communication of cybersecurity requirements, technical and commercial engagement between customers and suppliers, and in the tailoring of implementations towards operational technology contexts. Communicating the context of securing cyber-physical systems is an essential perspective for this community. This work exemplifies a partnership framework and is translating experiences into useful guidance, particularly for OT systems, to improve cybersecurity levels across multiple contributors to critical infrastructure systems. Full article

An expected increase in the demand for aviation transport service will result in the deterioration of the environment and human health, respectively, due to extra greenhouse gas (GHG) emissions. Concerns from EU institutions about the issue have led to legislation initiatives and, later, to development of Regulation (EU) 2023/2405 for the reduction of GHG emissions via the substitution of fossil kerosene with an increasing share of sustainable components. Hydroprocessed esters and fatty acids (HEFAs) are the most commercially acceptable sustainable alternative but their influence on aviation fuel properties needs to be further evaluated in terms of all required and extended properties, as per ASTM D1655. The main properties, together with the rarely reported upon existent gum, water separation, corrosion, and the electrical conductivity of HEFAs and their blends with fossil kerosene were quantitatively evaluated in this study. For every increase of 10% (v/v) of HEFAs, the following fuel properties improve: the freezing point decreases by 1.3 °C, the smoke point increases by an average of 3 mm, and the specific net energy increases by 0.08 MJ/kg. The acidity of HEFAs are an order of magnitude higher than that of conventional aviation fuel and, thus, close to the limit. The existent gum of the studied SAF is higher than that of fossil kerosene due to, most probably, the presence of non-evaporated residual material. Full article

In industry, forecast prediction and health management (PHM) is used to improve system reliability and efficiency. In PHM, remaining useful life (RUL) prediction plays a key role in preventing machine failures and reducing operating costs, especially for reliability requirements such as critical components in aviation as well as for costly equipment. With the development of deep learning techniques, many RUL prediction methods employ convolutional neural network (CNN) and long short-term memory (LSTM) networks and demonstrate superior performance. In this paper, a novel two-stream network based on a bidirectional long short-term memory neural network (BiLSTM) is proposed to establish a two-stage residual life prediction model for mechanical devices using CNN as the feature extractor and BiLSTM as the timing processor, and finally, a particle swarm optimization (PSO) algorithm is used to adjust and optimize the network structural parameters for the initial data. Under the condition of lack of professional knowledge, the adaptive extraction of the features of the data accumulated by the enterprise and the effective processing of a large amount of timing data are achieved. Comparing the prediction results with other models through examples, it shows that the model established in this paper significantly improves the accuracy and efficiency of equipment remaining life prediction. Full article

In recent years, there has been a significant increase in the use of structural health monitoring (SHM) technologies as systems for monitoring the integrity of aircraft’s structures. The use of compact and embeddable sensor networks, like the ones based on fibre optics (FO), is particularly attractive from the perspective of releasing an integrated structural system with intrinsic sensing capacity. Usually, an SHM system architecture is completed by a dedicated algorithm that processes the data gathered from the sensors to elaborate on the level of damage currently suffered by the structure, with the further possibility of providing information to the relevant specialists involved with its supervision. One of the main SHM applications that is attracting major interest is related to the inspection and detection of anomalies in bonded joints, which is extremely relevant in many composite realizations. Aeronautical regulations allow the use of bonded joints on an aircraft’s primary structure but require the implementation of a means to ensure their absolute safety, such as the introduction of further mechanical links aimed at stopping the propagation of a possible flaw or the availability of Non-Destructive Inspection (NDI) systems to prove the absence of relevant damaged areas. Generally, the main typical defects occurring during the manufacturing of bonded joints include adhesive curing, kissing bonds, poor porosity, and poor surface preparation. The current NDI systems more widely used and available to detect defects are still inaccurate due to the lack of standard procedures for the creation of representative defects in a controlled manner, which would allow for the development of reliable methodologies and tools able to ensure the safety of a bonded joint, as required by safety regulations. This paper shows the results relative to the implementation of an SHM system developed by the Italian Aerospace Research Centre (CIRA) aimed at monitoring the bonding lines between spar caps and panels of a typical composite wingbox section and detecting faults in location and length. The work was performed during typical ground static tests by using a fibre optical sensing network embedded within relevant adhesive paste layers during the manufacturing process of the structure. In the reported investigation, the SHM system assumed the function of an NDI system tool. The results show that the developed SHM system has good reliability for the detection of both the position and size of damage areas that were artificially inserted within the test article during the bonding phase, showing its potential as a candidate to be used as a tool to verify the conditions of a bonded joint, as required by aviation authorities’ regulations. Full article

A digital twin is a computer-based “virtual” representation of a complex system, updated using data from the “real” twin. Digital twins are established in product manufacturing, aviation, and infrastructure and are attracting significant attention in medicine. In medicine, digital twins hold great promise to improve prevention of cardiovascular diseases and enable personalised health care through a range of Internet of Things (IoT) devices which collect patient data in real-time. However, the promise of such new technology is often met with many technical, scientific, social, and ethical challenges that need to be overcome—if these challenges are not met, the technology is therefore less likely on balance to be adopted by stakeholders. The purpose of this work is to identify the facilitators and barriers to the implementation of digital twins in cardiovascular medicine. Using, the Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework, we conducted a document analysis of policy reports, industry websites, online magazines, and academic publications on digital twins in cardiovascular medicine, identifying potential facilitators and barriers to adoption. Our results show key facilitating factors for implementation: preventing cardiovascular disease, in silico simulation and experimentation, and personalised care. Key barriers to implementation included: establishing real-time data exchange, perceived specialist skills required, high demand for patient data, and ethical risks related to privacy and surveillance. Furthermore, the lack of empirical research on the attributes of digital twins by different research groups, the characteristics and behaviour of adopters, and the nature and extent of social, regulatory, economic, and political contexts in the planning and development process of these technologies is perceived as a major hindering factor to future implementation. Full article

The KC-46A Pegasus, a Boeing 767 (B767) commercial derivative aircraft (CDA), is a key part of the United States Air Force’s (USAF) efforts to modernize their aging tanker fleet. The Department of Defense (DoD) and the USAF have heavily emphasized the desire and need for Condition-Based Maintenance Plus (CBM+) to improve aircraft maintenance programs such as the KC-46A. This study reviews existing CBM+ practices on B767 and related aircraft fleets at Delta Air Lines to identify initial steps for implementing CBM+ in the KC-46 maintenance program. Specifically, comparative vacuum monitoring (CVM) sensors are proposed for KC-46A structural health monitoring (SHM) as a Federal Aviation Administration (FAA)-certified CBM+ technology. As demonstrated at Delta Air Lines Technical Operations (Delta TechOps), CVM sensors satisfy the technological, procedural, financial, and regulatory requirements to advance KC-46A SHM and serve as a template for future CBM+ initiatives. Full article

(1) Background: The safe performance of pharmacists is an important issue for patients and regulators. It is recognized that pharmacists interact with a variety of healthcare professionals and act as a bridge between other healthcare providers and systems and patients in the health setting. There has been growing activity in exploring factors that impact optimal performance and determinants that are linked with medication errors and practice incidents. The aviation and military industries have used S.H.E.L.L modeling to identify how personnel interact with factors that affect outcomes. A human factors approach is a useful angle to take when trying to improve optimal practice. Little is known about the experiences of New Zealand pharmacists and S.H.E.L.L factors that affect day-to-day practices in their work environment. (2) Methods: We investigated environment, team, and organizational considerations as the determining factors of optimal work practices using an anonymous online questionnaire. The questionnaire was built from a modified version of the software, hardware, environment, and liveware (S.H.E.L.L) model. This identified components of a work system that were vulnerable and that provided risks to optimal practice. Participants were New Zealand pharmacists approached through a subscriber list provided by the regulatory authority of the profession. (3) Results: We received responses from 260 participants (8.56%). The majority of participants indicated that optimal practice was occurring. More than 95% of respondents agreed that knowledge, fatigue interruptions, complacency, and stress affected optimal practice. Equipment and tools, medication arrangement on the shelf, lighting, physical layout, and communication with staff and patients were important factors for optimal practice. A smaller cohort of participants, 13 percent (n = 21), stated that dispensing processes, dissemination, and enforcement of standard operating procedures and procedural guidance did not affect pharmacy practice, 21.3% responded that professional and ethical requirements did not affect optimal practice, 20% stated that having a staffroom affected optimal practice, 20% did not think substance use affected optimal practice, and 30% did not state that cultural differences affected optimal practice. Optimal practice is constrained when there is a lack of experience, professionalism, and communication among staff, patients, and external agencies. COVID-19 also has had an impact on pharmacists both personally and in their work environments. Exploring how the pandemic has affected pharmacists and their work environment warrants further research. (4) Conclusions: Pharmacists across New Zealand agreed that optimal practices were occurring and considered other factors that were perceived to not affect optimal practice. A human factor S.H.E.L.L framework has been used to analyze themes to understand the optimal practice. The rising body of international literature on the effect of the pandemic on pharmacy practice serves as a foundation for many of these themes. Longitudinal data would be useful in exploring some factors, such as pharmacist well-being over time. Full article

The rapid development of the aviation industry has put forward higher and higher requirements for material properties, and the research on smart material structure has also received widespread attention. Smart materials (e.g., piezoelectric materials, shape memory materials, and giant magnetostrictive materials) have unique physical properties and excellent integration properties, and they perform well as sensors or actuators in the aviation industry, providing a solid material foundation for various intelligent applications in the aviation industry. As a popular smart material, piezoelectric materials have a large number of application research in structural health monitoring, energy harvest, vibration and noise control, damage control, and other fields. As a unique material with deformation ability, shape memory materials have their own outstanding performance in the field of shape control, low-shock release, vibration control, and impact absorption. At the same time, as a material to assist other structures, it also has important applications in the fields of sealing connection and structural self-healing. Giant magnetostrictive material is a representative advanced material, which has unique application advantages in guided wave monitoring, vibration control, energy harvest, and other directions. In addition, giant magnetostrictive materials themselves have high-resolution output, and there are many studies in the direction of high-precision actuators. Some smart materials are summarized and discussed in the above application directions, aiming at providing a reference for the initial development of follow-up related research. Full article

An aircraft engine is expected to have a high-reliability system as a safety-critical asset. A scheduled maintenance strategy based on statistical calculation has been employed as the current practice to achieve the reliability requirement. Any improvement to this maintenance interval is made after significant reliability issues arise (such as flight delays and high component removals). Several publications and research studies have been conducted related to this issue, one of them involves performing simulations and providing aircraft operation datasets. The recently published NASA CMAPPS datasets have been utilised in this paper since they simulate flight data recording from various measurements. A prognostics model can be developed by analysing these datasets and predicting the engine’s reliability before failure. However, the state-of-the-art prognostics techniques published in the literature using these NASA CMAPPS datasets are mainly purely data-driven. These techniques mainly deal with a “black box” process which does not include uncertainty quantification (UQ). These two factors are barriers to prognostics applications, particularly in the aviation industry. To tackle these issues, this paper aims at developing explainable and transparent algorithms and a software tool to compute the engine health, estimate engine end of life (EoL), and eventually predict its remaining useful life (RUL). The proposed algorithms use hybrid metrics for feature selection, employ logistic regression for health index estimation, and unscented Kalman filter (UKF) to update the prognostics model for predicting the RUL in a recursive fashion. Among the available datasets, dataset 02 is chosen because it has been widely used and is an ideal candidate for result comparison and dataset 03 is employed as a new state-of-the-art. As a result, the proposed algorithms yield 34.5–55.6% better performance in terms of the root mean squared error (RMSE) compared with the previous work. More importantly, the proposed method is transparent and it quantifies the uncertainty during the prediction process. Full article

In Australia, there is a significant health gap between rural and urban populations. One set of tools that could help lessen that gap is drones used for pharmaceutical delivery. There are extensive regulations surrounding the dispensing of prescription and controlled drugs, as well as strict requirements from aviation regulations for drone operators to meet. To assess and analyse the issues associated with operating at the intersection of pharmaceutical and aviation regulations in Australia, institutional theories can be applied. To inductively shed light on the key issues associated with the use of drones for the delivery of pharmaceuticals, a series of interviews were conducted using a truncated convergent interviewing approach. The common issues raised amongst experts highlight the complex challenge when developing drone networks for the delivery of pharmaceuticals. The main constraints appear to be due to aviation, not medication regulation. Legal grey areas, regulator inflexibility and other regulatory concerns stemming from strong institutional forces have created an environment limiting the use of drone delivery. Until drone regulations are changed, the potential of this innovative and developing sector is substantially restrained and those living in regional and rural areas will continue to have limited access to healthcare. Full article