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Item Open Access Position uncertainty reduction in visualInertial navigation systems using multi-ML error compensation(Institute of Navigation, 2024-10-09) Tabassum, Tarafder Elmi; Petrunin, Ivan; Rana, Zeeshan AIn the absence of signals from global navigation satellite systems (GNSS), visual-inertial navigation systems (VINS) are usually utilized in urban air mobility (UAM) applications which require reliable navigation in complex urban areas. This paper focuses on improving vision-based alternatives to GNSS navigation solutions with position uncertainty correction for safe and uninterrupted flights. The novel contribution introduces multiple machine-learning aided hybrid visual-inertial odometry (multi-ML hybrid VIO) that utilizes gated recurrent unit (GRU) based error compensators to enhance positioning within complex environments by reducing the impacts of various sources of uncertainty. Unlike state-of-the-art systems that lack evidence of demonstrating performance enhancement with position uncertainty correction within VIO architectures, the proposed framework simultaneously reduces position uncertainty and improves accuracy. Furthermore, training and testing datasets are generated using MATLAB incorporating unreal engine simulation environment for UAVs to replicate complex scenarios including environmental conditions, illumination variations, weather effects and flight dynamics where traditional VIO systems tend to fail. The proposed hybrid VIO architecture has been validated under combinations of complex scenarios including various sources of uncertainty such as sensor noise, feature tracking error, environmental dynamics, weather effects and lighting conditions for extended flights. The comparison results have demonstrated reduction in horizontal positioning RMSE errors: 1.7m for VIO with VO error compensation 2.18m for VIO with KF error compensation, 1.4m for multi-ML hybrid VIO. Furthermore, it demonstrates generalization ability over seen and unseen fault scenarios that indicates performance improvement of 89% in 3D position compared to VIO with VO error compensation, VIO with KF error compensation, and ESKF-based VIO. Additionally, experimental results demonstrate overall horizontal position uncertainty reduction by 79% for test 1 and 22% for test 2. Finally, this work represents a step forward in improving the safety and effectiveness of UAV navigation by providing vision-based alternative to GNSS solution for uninterrupted flights.Item Open Access Impact of installation on the performance of a civil turbofan exhaust at wind-milling: a combined experimental and numerical approach(Elsevier, 2025-03) Goulos, Ioannis; MacManus, David; Hueso Rebassa, Josep; Alderman, James; Sheaf, ChristopherThis work presents a combined experimental and numerical investigation of the effect of wing integration on the aerodynamic behaviour of a typical large civil aero-engine exhaust at wind-milling conditions. Engine performance simulations established estimates of Fan and Core Nozzle Pressure Ratios (FNPR and CNPR, respectively) for representative “engine-out” wind-milling scenarios. The experimental data and Reynolds Averaged Navier Stokes (RANS) Computational Fluid Dynamic (CFD) simulations encompassed End of Runway (EoR) take-off, diversion, and cruise wind-milling conditions for both isolated and installed configurations. The impact of FNPR, CNPR, free-stream Mach number (M∞), and high-lift surfaces on the installed suppression effect were evaluated. The measured and CFD predicted fan and core nozzle maps were implemented into the engine performance model to estimate the engine re-matching characteristics due to the impact of the installation, and the effect on engine mass flow. The effect of installation can reduce the fan and core nozzle discharge coefficients by up to 13% and 26%, respectively, relative to the isolated configuration for representative EOR wind-milling conditions. RANS CFD captures the effect of suppression on both the fan and core with an accuracy between 0.1% and 1.2%, depending on Mach number, which is sufficient for industrial design and analysis purposes. The engine performance analyses showed that the installed suppression effect can result in a 10% reduction of engine mass flow at EOR wind-milling. Within the context of nacelle design under wind-milling, this effect of exhaust suppression must be considered in determining the intake Mass Flow Capture Ratio (MFCR).Item Open Access Resilient or fragile? modelling economic disruptions in India's electronics sector due to the Red Sea crisis(Elsevier, 2025-02) Sarkar, Bishal Dey; Gupta, Laxmi; Jagtap, SandeepThe Red Sea crisis and the recent attacks on commercial ships have drawn significant attention worldwide, underscoring the need to understand how such geopolitical conflicts can disrupt global supply chains and economic stability. This paper thoroughly examines the complex impacts of the crisis on India's electronics and photonics sector, recognizing the sector's crucial importance as a fundamental pillar in the country's economic structure. The study creates a mathematical model to assess how disruptions in the Electronics and Photonics Sector affect India's economy in light of the Red Sea Crisis. The model uses two specific methods: interval programming and input-output modelling. How disruption in one area of the economy ripples to another is studied using Wassily Leontief's Inoperability Input-output Model (IIM). IIM now includes interval programming to handle data uncertainties. The findings disclose that, because of the Red Sea crisis, Indian Sector has experienced a huge economic loss of 605.52 million USD. The study also determines which sectors are anticipated to suffer significant losses due to the crisis, allowing decision-makers to prioritize their investment plans. Further, the research uses the inoperability value to analyse the interconnections between the sectors. Additionally, a decision-support conclusion is included in the research to analyse the sectors under various situations.Item Open Access Review of bioinspired composites for thermal energy storage: preparation, microstructures and properties(MDPI, 2025-01-15) Yu, Min; Wang, Mengyuan; Xu, Changhao; Zhong, Wei; Wu, Haoqi; Lei, Peng; Huang, Zeya; Fu, Renli; Gucci, Francesco; Zhang, DouBioinspired composites for thermal energy storage have gained much attention all over the world. Bioinspired structures have several advantages as the skeleton for preparing thermal energy storage materials, including preventing leakage and improving thermal conductivity. Phase change materials (PCMs) play an important role in the development of energy storage materials because of their stable chemical/thermal properties and high latent heat storage capacity. However, their applications have been compromised, owing to low thermal conductivity and leakage. The plant-derived scaffolds (i.e., wood-derived SiC/Carbon) in the composites can not only provide higher thermal conductivity but also prevent leakage. In this paper, we review recent progress in the preparation, microstructures, properties and applications of bioinspired composites for thermal energy storage. Two methods are generally used for producing bioinspired composites, including the direct introduction of biomass-derived templates and the imitation of biological structures templates. Some of the key technologies for introducing PCMs into templates involves melting, vacuum impregnation, physical mixing, etc. Continuous and orderly channels inside the skeleton can improve the overall thermal conductivity, and the thermal conductivity of composites with biomass-derived, porous, silicon carbide skeleton can reach as high as 116 W/m*K. In addition, the tightly aligned microporous structure can cover the PCM well, resulting in good leakage resistance after up to 2500 hot and cold cycles. Currently, bioinspired composites for thermal energy storage hold the greatest promise for large-scale applications in the fields of building energy conservation and solar energy conversion/storage. This review provides guidance on the preparation methods, performance improvements and applications for the future research strategies of bioinspired composites for thermal energy storage.Item Open Access Air rage from the sharp end: cabin crew perspectives on disruptive passenger behaviour in Europe and its impact on occupational safety and well-being(Taylor and Francis, 2024-09-12) Rösch, Alexander; Chernak, Erin; Blundell, JamesDisruptive passenger behaviour (DPB) incidents spiked during the COVID-19 pandemic period, compromising the safety of commercial flights on a daily basis. This qualitative semi-structured interview study examined the perceived triggering factors and motivations for DPB and the subsequent impact of DPB upon cabin crew well-being and safety. Twenty-four European cabin crew disclosed experiences, subjective observations of perpetrator traits, assessment of DPB development and information regarding their well-being and perceived safety. Thematic analysis revealed that the perceived frequency of DPB had increased, driven by an accumulation of pandemic-related factors–such as enforcing mask wearing amongst intoxicated passengers. DPB was found to decrease resilience and spur maladaptive coping strategies in crew. Suggested enhancements to current DPB mitigation consisted of stricter punishment for DPB as a deterrent, alcohol bans and higher quality training. These findings can inform decision-makers’ efforts to support cabin crew well-being and create safer cabin workplaces in the future.Item Open Access Board and executive gender diversity as a driver of airline efficiency: a network-DEA analysis(Elsevier, 2025-04-01) Suau-Sanchez, Pere; Voltes-Dorta, Augusto; Lamolla, LauraThis paper investigates the influence of gender diversity on the efficiency of airlines. Despite global progress towards gender equality, the airline industry continues to exhibit a considerable gender gap, especially in leadership positions. Our study utilises a Network Data Envelopment Analysis (DEA) to assess the performance of airlines concerning gender diversity in board and executive roles. By analysing a dataset of airlines of different continents and covering the period before and after the COVID-19 crisis, gender diversity's impact on airline efficiency (defined as the ratio of the sum of its weighted outputs to the sum of its weighted inputs) is examined. A second-stage estimation further enriches the analysis to assess the influence of external variables. Our findings reveal that airlines with higher gender diversity on their boards and executive teams exhibit better efficiency before and after COVID-19 crisis. The study contributes to the broader discourse on gender diversity in traditionally male-dominated sectors, offering insights into the strategic benefits of inclusive leadership practices.Item Open Access End-to-end identification of autoregressive with exogenous input (ARX) models using neural networks(Springer, 2025-02-01) Dong, Aoxiang; Starr, Andrew; Zhao, YifanTraditional parametric system identification methods usually rely on apriori knowledge of the targeted system, which may not always be available, especially for complex systems. Although neural networks (NNs) have been increasingly adopted in system identification, most studies have failed to derive interpretable parametric models for further analysis. In this paper, we propose a novel end-to-end autoregressive with exogenous input (ARX) model identification framework using NNs. An order-wise neural network structure is introduced and trained using a multitask learning approach to simultaneously identify both the model terms and coefficients of the ARX model. Through testing with various neural network backbones and training data sizes in different scenarios, we empirically demonstrate that the proposed framework can effectively identify an arbitrary stable ARX model with finite simulation training data. This study opens up a new research opportunity for parametric system identification by harnessing the power of deep learning.Item Open Access The Aegis orbit determination and impact monitoring system and services of the ESA NEOCC web portal(Springer, 2024-12-01) Fenucci, M.; Faggioli, L.; Gianotto, F.; Bracali Cioci, D.; Cano, J. L.; Conversi, L.; Devogèle, M.; Di Girolamo, G.; Drury, C.; Föhring, D.; Gisolfi, L.; Kresken, R.; Micheli, M.; Moissl, R.; Ocaña, F.; Oliviero, D.; Porru, A.; Ramirez-Moreta, P.; Rudawska, R.; Bernardi, F.; Bertolucci, A.; Dimare, L.; Guerra, F.; Baldisserotto, V.; Ceccaroni, Marta; Cennamo, R.; Chessa, A.; Del Vigna, A.; Koschny, D.; Teodorescu, A. M.; Perozzi, E.The NEO Coordination Centre (NEOCC) of the European Space Agency is an operational centre that, among other activities, computes the orbits of near-Earth objects and their probabilities of impact with the Earth. The NEOCC started providing information about near-Earth objects in 2012 on a dedicated web portal, accessible at https://neo.ssa.esa.int/. Since the beginning of the operational phase, many developments and improvements have been implemented regarding the software, the data provided, and the portal. One of the most important upgrades is that the NEOCC is now independently providing data through a newly developed Orbit Determination and Impact Monitoring system, named Aegis. All the data computed by Aegis are publicly available on the NEOCC web portal, and Aegis is also used to maintain all the major services offered. The most important services comprise an orbital catalogue of all known asteroids, a list of possible future impacts with the Earth (also called Risk List), a list of forthcoming close approaches, a set of graphical toolkits, and an on-demand ephemerides service. Many of the services are also available through dedicated APIs, which can be used to automatically retrieve data. Here we give an overview of the algorithms implemented in the Aegis software and provide a summary of the services offered by the NEOCC that are supported by Aegis.Item Open Access SmartSocks: a new data collection paradigm for dementia and other neurological disorders(Wiley, 2024-12) Steer, Zeke; Venkatesh, Prabha Thirthahalli; Mejia‐Mejia, Elisa; Dennis, William Wu; Ogundele, Patrick Ademola; Brooking, Annie; Eimontaite, IvetaBackground Distress and agitation are predictors of entry into long‐term care and health inequalities (Schulz et al., 2004, Weir et al., 2022). Physiological data has been shown to reliably predict distress (Goodwin et al., 2019), yet wearable devices have low acceptance rates (Koumpouros & Kafazis, 2019). The current study discusses findings from a multifaceted approach investigating the detection of early signs of distress via physiological sensors in a foot‐worn device. Method Firstly, the acceptance and concern ratings for a foot‐worn device, SmartSocks, wrist‐worn devices, Empatica E4 and Shimmer GSR+, and chest‐worn device, Equivital within a healthy population (N = 10) were assessed with a self‐report questionnaire. Secondly, data accuracy between Shimmer ECG and Polar OH1+ was compared within a healthy population (N = 12) in a standing, sitting and supine position. Finally, an ongoing ecologically valid feasibility trial (N = 2) involving participants with dementia or a learning disability is assessing the reliability of physiological data and AI‐detected stress from SmartSocks relative to subjective ratings of distress, the Abbey Pain Scale (APS), and the Neuropsychiatric Inventory (NPI). Result Firstly, the SmartSocks received lowest concern ratings compared to wrist‐ and chest‐worn devices (1.64 vs <1.71). Secondly, the accuracy of SmartSocks pulse rate (PR) estimates obtained using photoplethysmography (PPG) in combination with the delineator algorithm was determined by comparing estimates to a Shimmer 1‐lead ECG, recording Mean Absolute Error (MAE)<5bpm at 64HZ for participants in a supine position (Fig. 1). This led to the development of new features for classifying PPG signal quality using neural networks, achieving approximately 95% accuracy. Finally, the initial stage of the feasibility trial indicated APS and NPI scores were lower after the participant with dementia wore SmartSocks for two weeks. Physiological data collected from the participant with a learning disability using SmartSocks showed moderate correlation (χ2 = 0.45) between the reported and AI‐detected stress over the day (Fig. 2 & 3). Conclusion Early findings suggest SmartSocks are more comfortable than comparable wrist‐ and chest‐worn devices, and validity of the data is comparable to other devices. Preliminary data obtained from people with dementia and learning disabilities suggest SmartSocks are capable of detecting distress to alleviate user discomfort.Item Embargo A modular multifidelity approach for multiphysics oleo-pneumatic shock absorber simulations(Springer Nature, 2024-12-03) Sheikh Al-Shabab, Ahmed A; Silva, Paulo ASF; Grenko, Bojan; Tsoutsanis, Panagiotis; Skote, MartinA numerical framework is developed and tested to simulate the internal dynamics of oleo-pneumatic shock absorbers. A modular approach is devised to address the multiphysics nature of the problem, starting with three dimensional scale resolving turbulence simulations and two dimensional axisymmetric multiphase URANS simulations. These simulations capture the main dominant aspects of energy dissipation through turbulence, and the multiphase mixing which can affect the working fluid properties. Internal flow simulations are run on a representative shock absorber geometry based on dimensions provided in the validation study together with sizing guidelines from the literature. A lower fidelity two-equation dynamic system solver is used to scan the design space and test the sensitivity towards various design parameters, in addition to identifying parameter combinations that would be of interest to investigate using higher fidelity methods.Item Open Access We are not equipped to identify the first signs of cyber–physical attacks: emotional reactions to cybersecurity breaches on domestic internet of things devices(MDPI, 2024-12-02) Budimir, Sanja; Fontaine, Johnny R. J.; Huijts, Nicole M. A.; Haans, Antal; IJsselsteijn, Wijnand A.; Oostveen, Anne-Marie; Stahl, Frederic; Heartfield, Ryan; Loukas, George; Bezemskij, Anatolij; Filippoupolitis, Avgoustinos; Ras, Ivano; Roesch, Etienne B.The increasing number of domestic Internet of Things (IoT) devices in our lives leads to numerous benefits, but also comes with an increased risk of cybersecurity breaches. These breaches have psychological consequences for the users. We examined the nature of the psychological impact of cybersecurity breaches on domestic IoT by investigating emotional experiences in a scenario study (Study 1) and a field experiment (Study 2) using the five emotion components of the Component Process Model (CPM) and emotion regulation as a framework. We replicated a three-dimensional structure for emotional experiences found in a previous study, with an addition of an ancillary fourth dimension in the second study. The first dimension represents emotional intensity. The second bipolar dimension describes constructive vs. unconstructive action tendencies. On the third dimension, also bipolar, cognitive and motivational emotion features are opposed to affective emotion features. The fourth dimension, labeled distress symptoms, mainly reflects negative emotions. In Study 2, most of the introduced frequent irregularities on IoT devices were not noticed, and the intensity of emotional reactions and tendencies to react in a constructive way decreased throughout the phases of the experiment. These findings reveal that we are not emotionally equipped to identify potential threats in the cyber world.Item Open Access Potentials for energy savings and carbon dioxide emissions reduction in cement industry(Springer, 2025-01-07) Sarfraz, Shoaib; Sherif, Ziyad; Drewniok, Michal; Bolson, Natanael; Cullen, Jonathan; Purnell, Phil; Jolly, Mark R.; Salonitis, KonstantinosCement production accounts for 7% of global carbon dioxide emissions, 3 to 4% of greenhouse gas emissions, and 7% of global industrial energy use. Cement demand is continuously increasing due to the rising worldwide population and urbanisation trends, as well as infrastructure development needs. By 2050, global cement production is expected to increase by 12 to 23% from its current level. Following the net-zero carbon 2050 agenda, both energy and emissions must be significantly reduced. Different production routes exist to produce cement that differs in energy intensity as well as carbon intensity. Similarly, a range of values exists related to energy and emissions for the major cement production stages i.e., raw meal preparation, clinkerisation and cement grinding. The same is the case with cement types produced. This study presents a literature review-based investigation and comparison of cement production practices in terms of energy consumption and CO2 emissions. This will provide perspectives to the cement industry by identifying approaches that are the least energy and emissions intensive.Item Open Access Quantifying the carbon footprint of events: a life cycle assessment-based framework for evaluating impact of location and timing(Springer Nature, 2025-01-07) Atescan-Yuksek, Yagmur; Paddea, Sanjooram; Jackson, Sharon; Jolly, Mark R.; Salonitis, KonstantinosThis research proposes a Life Cycle Assessment-based framework to quantify the carbon footprint of events, considering the event's location and timing. The framework aims to standardise environmental impact calculations through inventory analysis. To validate it, a comparative analysis on conducting an event in different locations and time periods, while maintaining similar scale and nature is conducted. The assessment includes emissions from attendee transport, accommodation, food and drink, and venue. Additionally, it considers emission reductions resulting from attendees not using their personal household resources. This accounts for the actual additional emissions released into the atmosphere as a consequence of the event. The results highlight variations in emissions across different consumption categories based on the selected location and timing. By providing this information, the LCA-based framework provides valuable guidance for event organizers and policymakers to assess event environmental impacts and promote sustainability.Item Open Access Environmental impact assessment of manufacturing of SiC/SiC composites(Springer Nature, 2025-01-07) Karadimas, Georgios; Yuksek, Yagmur Atescan; Salonitis, KonstantinosSiC/SiC composites have attracted increasing attention in various applications such as turbine blades, exhaust nozzles, and combustor chambers, due to their exceptional mechanical and thermal properties. However, the environmental impact of these composites across their life cycle is an important aspect that needs to be evaluated to support their responsible development and use. In this study, a life cycle assessment of SiC/SiC woven laminate ceramic matrix composites to quantify their environmental impacts from cradle-to-gate was conducted. Three different manufacturing methods to produce SiC/SiC woven laminates were researched: chemical vapour infiltration (CVI), pyrolysis of a preceramic polymer (PIP), and melt infiltration (MI). The Life Cycle Assessment approach was utilized to identify the effect outcomes for each process, analysing the raw material extraction, raw material processing, and final product manufacturing phases to develop the environmental impact assessment. The study's outcome showed that CVI had the lowest average environmental impact between the two methods.Item Open Access A critical review of the decarbonisation potential in the U.K. cement industry(MDPI, 2025-01-10) Sherif, Ziyad; Sarfraz, Shoaib; Jolly, Mark R.; Salonitis, KonstantinosAs urbanisation and infrastructure development continue to drive rising cement demand, the imperative to significantly reduce emissions from this emissions-intensive sector has become increasingly urgent, especially in the context of global climate goals such as achieving net zero emissions by 2050. This review examines the status, challenges and prospects of low-carbon cement technologies and mitigation strategies through the lens of the U.K. cement industry. A mixed-methods approach was employed, combining structured literature searches across academic databases with analyses of industry reports, market data and technological roadmaps to ensure a comprehensive evaluation. Following an outline of cement production, resource flows and the sector’s landscape in the U.K., the review delves into an array of decarbonisation pathways. This includes deploying the best available technologies (BATs), fuel switching, carbon capture utilisation and storage (CCUS), clinker substitution and low-carbon cement formulations. A critical assessment is provided on the technological readiness, costs, resource availability considerations and scalability aspects governing the widespread implementation prospects of these approaches within the U.K. cement industry. Furthermore, this study proposes a roadmap that considers priority avenues and policy needs essential for facilitating the transition towards sustainable cement production aligned with the U.K.’s net zero obligations by 2050. This evaluation contributes significantly to the ongoing decarbonisation discourse by holistically mapping technological solutions and strategic imperatives tailored to the unique challenges and opportunities presented by the U.K. cement sector.Item Open Access Identifying enablers for a circular healthcare supply chain: an integrated fuzzy DEMATEL-MMDE approach with hesitant information(Elsevier, 2025-02) Agrawal, Deepak; Gupta, Sumit; Dusad, Chandni; Meena, ML; Dangayach, GS; Jagtap, SandeepOver the past decade, the healthcare industries have been facing the issue of resource scarcity due to socio-political wars, the COVID-19 pandemic, the luxury lifestyles of people, and the prevalence of single-use medical devices. The circular economy (CE) can be vital in accommodating the evolving patient and provider demands. The CE defies the conventional take-make-dispose process and advocates for optimized resource use throughout its entire lifecycle. Finding the critical enabler for a circular supply chain in the Indian healthcare sector is urgently needed because the CE is still nascent in developing nations like India. This paper identifies the enablers of a circular healthcare supply chain (CHSC) through a comprehensive analysis of cause and effect, interrelationships, and priorities using integrated alpha-level sets based on the fuzzy DEMATEL-MMDE approach with hesitant information. Experts' opinions were gathered using a triangular fuzzy linguistic scale, incorporating hesitant information to minimize data vagueness. The results of this study offer valuable insights into various enablers, emphasizing their criticality and interdependence, thereby benefiting healthcare organizations aiming to implement circular supply chains. Additionally, the findings will assist policymakers in creating policies to accelerate the adoption of CE practices in the healthcare industry.Item Open Access Participatory AI: a method for integrating inclusive and ethical design considerations into autonomous system development(Springer, 2024-12-30) Stimson, Christina E.; Raper, RebeccaThere has been significant work in the field of AI Ethics pertaining to how it might offer guidelines for developers to design, develop and deploy AI in an ethical way. Recently, the European Union’s AI Act has introduced a risk-based regulation approach for AI system development. However, despite the additional requirements the AI Act places on developers to ensure that their systems are created with transparency, fairness, and accountability etc., there is no formalised methodology for how this might be achieved. Drawing on the history of collaborative and emancipatory technology design in Scandinavia, this paper proposes a software development methodology founded on the ethics and praxis-based principles of Participatory Design. Integrating this approach into the established ‘Waterfall Method’, it offers developers a practical way of embedding ethics in AI development, and to thereby satisfy the requirements imposed by the new regulations.Item Open Access Unsteady swirl distortion in a short intake under crosswind conditions(American Institute of Aeronautics and Astronautics (AIAA), 2024-12-31) Piovesan, Tommaso; Zachos, Pavlos K; MacManus, David G; Sheaf, ChristopherUnder crosswind operating conditions, the flow field of an aero-engine intake can be characterized by notable unsteady flow distortion. These distortions are typically associated with flow separation within the intake as well as with the ingestion of the ground vortex. This unsteady flow distortion can have a detrimental effect on the intake performance and potentially on the operability of the downstream compression system. Measurements of the unsteady velocity field within a model-scale intake under crosswind conditions were acquired using stereo particle image velocimetry (S-PIV). This work analyzes the S-PIV data to quantify the unsteady flow distortion, as well as the characteristics of the ingested ground vortex, in a short intake under crosswind conditions. The swirl distortion metrics were calculated for a range of crosswind velocities and intake mass flow capture ratios (MFCRs). The conditions at which the intake flow separates depend on crosswind velocity, ground clearance, the design of the intake, and the MFCR. Flow characteristics of both low MFCR diffusion-driven and high MFCR shock-induced separation were identified. The circumferential extent and intensity of the swirl distortion are strongly dependent on the crosswind velocity and mass flow rate. The swirl distortion caused by the diffusion-driven separation is greater than that due to the shock-induced separation. The diffusion-driven separation affects a larger portion of the intake aerodynamic interface plane with greater time-averaged and peak distortion levels compared to shock-induced separation. The ground vortex characterization at the aerodynamic interface plane showed a decreasing level of unsteadiness in vortex meandering with increasing MFCR.Item Open Access Developing prompts to facilitate generative pre-trained transformer classifying decision-errors in flight operations(EasyChair, 2024-08-27) Li, Wen-Chin; Saunders, Declan; Amanzadeh, HamedThe emergence of artificial intelligence (AI) with advanced natural language processing offers promising approaches for enhancing the capacity of textual classification. The aviation industry is increasingly interested in adopting AI to improve efficiency, safety, and cost efficiency. This study explores the potential and challenges of using AI to analyse decision errors in flight operations based on the HFACS framework. In pre-training, the model is trained based on a large amount of data to predict the next word in a sequence which allows the model to learn relationships between the words and their meaning in the accident investigation reports. Initial discoveries demonstrated that the AI model could supply a consistent HFACS framework and populate these dimensions with moderate accuracy. Future research is focused on the development of this HFACS-GPT model through fi-ne-tuning and deep learning, facilitating more reliable and consistent conversations.Item Open Access The role of behavioural and environmental economics in sustainable manufacturing(Springer, 2023-12-04) Kaur, Rashmeet; Patsavellas, John; Salonitis, KonstantinosSustainable manufacturing is a rapidly growing field that primarily seeks to reduce the environmental impact of manufacturing processes. Although the three-lens approach of social, environmental, and economic aspects remain the primary focus in any sustainability study, the domains of behavioral, and environmental economics along with smart data technologies have not been used in a unified approach. Through a review of the state of the art, this paper establishes the individual cases for each one of these domains and underscores the research interest in their combinatorial application and possible complementary efficacy for advancing the development of sustainable manufacturing strategies. A research agenda involving comparative testing and the development of pertinent policies and interventions for sustainable manufacturing is proposed for the integration of behavioral economics and environmental economics, within the context of sustainable manufacturing.