Staff publications (SATM)

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Open Access
Modular model and simulation for process optimisation in advanced material recovery facilities (MRFs)
(Elsevier, 2024) Liu, Milan; Grimes, Sue; Salonitis, Konstantinos; Litos, Lampros
At a time when the supply of critical materials is threatened, waste recycling and reuse is an essential solution for human development. The role of Material Recovery Facilities (MRFs) to deliver efficiently high-purity material fractions as feedstock cannot be underestimated. However, MRF sorting processes need to remain adaptive with evolving smart technologies and systems that further enhance their effectiveness. For example, a re-designed MRF with AI-based robotics can improve the performance of waste recycling, leading to significant economic and environmental benefits. This study assesses the performance of potential optimisation methods for future proofing MRFs using modular simulation methods. The authors set out to review current robotics sorting technology and pointed out the challenge of efficiency analysis with multiple variables. The study develops a new conceptual model of efficiency analysis considering the identification and sorting limitations of robots, as well as the coordination requirements between robots and conveyor belts. A computational model is designed and developed by modularity program codes to help practitioners gain insight into the MRF performance by modifying the variables (composition of input waste, separation coefficients and configurations) and analysing the resulting assessment factors (purity and recovery). In the end, this study demonstrates the performance of the optimisation methods of MRF (two target materials for one robot and recirculation loops) through simulation.
Open Access
Enabling net-zero GHG emissions in the UK metals and transport industries through a circular supply chain framework
(Elsevier, 2024-05) Adeyemi, Olabisi I.; Sarfraz, Shoaib; Salonitis, Konstantinos
The UK metals industry is indispensable in achieving the country’s net-zero greenhouse gas (GHG) emissions target by 2050, especially considering the heavy reliance of the transport sector on metals. This paper proposes strategies based on recycling and refining locally sourced scrap metals to build a robust circular supply chain. Findings revealed that 16% of global crude steel is used in transport and this accounts for 8% of the world’s GHG emissions. Domestically, iron and steel account for 14% of the UK industrial emissions, with over 8 million metric tons of scrap metals exported annually. Insights from stakeholders revealed export dependency and infrastructure gaps impeding circularity. Collaborative efforts between industry, government, and recyclers are vital. Investing in electric arc furnaces and storage can enable the processing of domestic metal scrap for high-quality yield. A closed-loop flow of battery-critical metals will also support sustainable manufacturing of electric vehicles. Ultimately, this paper advocates systemic efforts across policy, technology, infrastructure, and partnerships to realise a sustainable supply chain in the metals industry aligned with the decarbonisation and circular economy goals.
Open Access
A conceptual assessment framework for sustainability in the foundation industries
(Elsevier, 2024) Litos, Lampros; Paddea, Sanjooram; Salonitis, Konstantinos; Jolly, Mark R.
Foundation industries in the UK are in constant pursuit of better technological solutions to enhance materials conversion efficiency and supply chain economies of scale. However, sustainable materials and strategies to conserve resources and better utilize waste streams tend to be ever more challenging to achieve when technological advances fall short in being widely adoptable by companies. Knowledge and technology transfer across multiple companies within the same sector (for example, construction materials production) or across seemingly common core processes (such as size reduction or furnaces) must be achieved for sustainability efforts to achieve economies of scale. Part of the reason why this is a difficult endeavor is the lack of visibility of the steps and drivers involved in a circular economy context with a view to achieve scale. Materials and technologies that could help foundation industries become more sustainable are being examined through the introduction of a novel framework that could help companies and policy makers understand where the opportunities exist. In this paper, the authors describe the design and development of the framework and offer examples drawn from an ongoing research and innovation project in foundation industries.
Open Access
Facilitating lean implementation through change management
(Elsevier, 2024) Al Manei, Mohammed; Kaur, Rashmeet; Patsavellas, John; Salonitis, Konstantinos
Implementing lean manufacturing can be challenging and requires all stakeholders to be engaged. Several frameworks have been presented in the last decades, with most of them being conceptual and failing to consider that change inertia exists. In the present paper, a social change management model is used to develop a lean implementation framework, with each step prescribed for the practitioners. The elements of the model are selected after a series of workshops, a thorough literature review, and the development of an interpretive structural model for this reason. The model was validated through experts’ opinions and presents an alternative approach to the established lean implementation roadmaps available in the literature.
Open Access
Randomness-restricted diffusion model for ocular surface structure segmentation
(Institute of Electrical and Electronics Engineers (IEEE), 2025-03) Guo, Xinyu; Wen, Han; Hao, Huaying; Zhao, Yifan; Meng, Yanda; Liu, Jiang; Zheng, Yalin; Chen, Wei; Zhao, Yitian
Ocular surface diseases affect a significant portion of the population worldwide. Accurate segmentation and quantification of different ocular surface structures are crucial for the understanding of these diseases and clinical decision-making. However, the automated segmentation of the ocular surface structure is relatively unexplored and faces several challenges. Ocular surface structure boundaries are often inconspicuous and obscured by glare from reflections. In addition, the segmentation of different ocular structures always requires training of multiple individual models. Thus, developing a one-model-fits-all segmentation approach is desirable. In this paper, we introduce a randomness-restricted diffusion model for multiple ocular surface structure segmentation. First, a time-controlled fusion-attention module (TFM) is proposed to dynamically adjust the information flow within the diffusion model, based on the temporal relationships between the network’s input and time. TFM enables the network to effectively utilize image features to constrain the randomness of the generation process. We further propose a low-frequency consistency filter and a new loss to alleviate model uncertainty and error accumulation caused by the multi-step denoising process. Extensive experiments have shown that our approach can segment seven different ocular surface structures. Our method performs better than both dedicated ocular surface segmentation methods and general medical image segmentation methods. We further validated the proposed method over two clinical datasets, and the results demonstrated that it is beneficial to clinical applications, such as the meibomian gland dysfunction grading and aqueous deficient dry eye diagnosis.
Open Access
Cultural dynamics and ambidextrous innovation: insights from Saudi Arabia’s project-based organizations—a thematic–explorative study
(MDPI, 2025-03-21) AlSaied, Mohammad Khalid; McLaughlin, Patrick; Afy-Shararah, Mohamed; Patsavellas, John; Alkhoraif, Abdullah
The implementation of ambidextrous innovation in project organizations within the cultures of the Global South, such as Saudi Arabia, is a significant problem. Organizational culture is positioned as a key factor that can help project organizations in cultures such as Saudi Arabia to implement ambidexterity as a key innovation framework. However, knowledge of ambidextrous innovations in such an important cultural and organizational context is highly limited. Thus, the aim of the present research is to explore key cultural aspects and themes based on action and a grounded theory research approach that can help organizations employ projects as a key work structure to implement ambidextrous innovations in project management offices (PMOs) in Saudi Arabia. To achieve this aim, the current study employed in-depth semi-structured interviews with 36 participants. The results, employing open coding procedures as a tool of data analysis using the NVivo 14.0 software package, revealed 62 key cultural aspects that can be critical in implementing the innovation of ambidexterity. To further validate and triangulate the findings, inter-rater reliability was undertaken with the help of two experts, and two sessions of focus group discussions were also conducted. The first session of the focus group helped us critically evaluate and filter the cultural aspects, resulting in the final 56 key cultural aspects. The second focus group session was undertaken with participants with the aim of grouping aspects into theoretical themes, which resulted in 10 themes. The research is novel in that it addresses both project organizations and the culture of the Global South, including Saudi Arabia. Empirical research needs to be conducted to predict and achieve other key outcomes.
Open Access
A review of material-related mechanical failures and load monitoring-based structural health monitoring (SHM) technologies in aircraft landing gear
(MDPI, 2025-03-20) Deng, Kailun; Ompusunggu, Agusmian Partogi; Xu, Yigeng; Skote, Martin; Zhao, Yifan
The aircraft landing gear system is vital in ensuring the aircraft’s functional completeness and operational safety. The mechanical structures of the landing gear must withstand significant operational forces, including repeated high-intensity impact loads, throughout their service life. At the same time, they must resist environmental degradation, such as corrosion, temperature fluctuations, and humidity, to ensure structural integrity and long-term reliability. Under this premise, investigating material-related mechanical failures in the landing gear is of great significance for preventing landing gear failures and ensuring aviation safety. Compared to failure investigations, structural health monitoring (SHM) plays a more active role in failure prevention for aircraft landing gears. SHM technologies identify the precursors of potential failures and continuously monitor the operational or health conditions of landing gear structures, which facilitates condition-based maintenance. This paper reviews various landing gear material-related failure investigations. The review suggests a significant portion of these failures can be attributed to material fatigue, which is either induced by abnormal high-stress concentration or corrosion. This paper also reviews a series of load monitoring-based landing gear SHM studies. It is revealed that weight and balance measurement, hard landing detection, and structure load monitoring are the most typical monitoring activities in landing gears. An analytical discussion is also presented on the correlation between reviewed landing gear failures and SHM activities, a comparison of sensors, and the potential shift in load-based landing gear SHM in response to the transition of landing gear design philosophy from safe life to damage tolerance.
Open Access
Traffic prediction with shared causal inference in ORAN computing continuum
(IEEE, 2024-12-08) Guo, Weisi; Cordiez, Theophile
Data-driven proactive network optimisation is critical for 5G advanced and 6G, allowing operators to dynamically allocate cellular spectrum reuse in anticipating for demand surges. Current approaches to traffic prediction are largely temporal correlation based. We know causal inference of key factors can help to improve prediction accuracy for spike traffic events and identify pathways to improve services. Current causal inference identify stationary independent variables, but real environments have open challenges: (i) dynamic and heterogeneous causal maps, (ii) cascade partially observable variables, and/or (iii) have coupled / confounding relationships. Currently there is no research that dynamically configures the causal relationship according to emerging real-time data and shares inference outcomes across the data sharing and computing continuum of Open-RAN (ORAN) architecture. Here, we use both real cellular network traffic and social event triggers to perform nonlinear causal inference as an rApp: Predictability Improvement (PI), Conditional Mutual Information (CMI), and Convergent Cross Map (CCM). This causal knowledge is then shared across the ORAN to be embedded in traffic prediction xApps: hard causal embedding to Recurrent Neural Network (RNN) and soft causal feature embedding to a Gaussian Processes (GP). The results show a significant accuracy improvement (93-99%) over baseline non-causal correlated prediction (76-94%) and blind multi-variate approaches (87-95%). This work paves the way to causal proactive network optimisation.
Open Access
International collaboration
(The Foundation for Science and Technology, 2025-03-01) Neale, Geoffrey
Open Access
Numerical predictions of Low-Reynolds-Number propeller aeroacoustics: comparison of methods at different fidelity levels
(MDPI, 2025-02-18) Huang, Guangyuan; Sharma, Ankit; Chen, Xin; Riaz, Atif; Jefferson-Loveday, Richard
Low-Reynolds-number propeller systems have been widely used in aeronautical applications, such as unmanned aerial vehicles (UAV) and electric propulsion systems. However, the aerodynamic sound of the propeller systems is often significant and can lead to aircraft noise problems. Therefore, effective predictions of propeller noise are important for designing aircraft, and the different phases in aircraft design require specific prediction approaches. This paper aimed to perform a comparison study on numerical methods at different fidelity levels for predicting the aerodynamic noise of low-Reynolds-number propellers. The Ffowcs-Williams and Hawkings (FWH), Hanson, and Gutin methods were assessed as, respectively, high-, medium-, and low-fidelity noise models. And a coarse-grid large eddy simulation was performed to model the propeller aerodynamics and to inform the three noise models. A popular propeller configuration, which has been used in previous experimental and numerical studies on propeller noise, was employed. This configuration consisted of a two-bladed propeller mounted on a cylindrical nacelle. The propeller had a diameter of D=9″ and a pitch-to-diameter ratio of P/D=1, and was operated in a forward-flight condition with a chord-based Reynolds number of Re=4.8×104, a tip Mach number of M=0.231, and an advance ratio of J=0.485. The results were validated against existing experimental measurements. The propeller flow was characterized by significant tip vortices, weak separation over the leading edges of the blade suction sides, and small-scale vortical structures from the blade trailing edges. The far-field noise was characterized by tonal noise, as well as broadband noise. The mechanism of the noise generation and propagation were clarified. The capacities of the three noise modeling methods for predicting such propeller noise were evaluated and compared.
Open Access
Coriolis massflow measurement errors due to inhomogeneous entrained particles: an analytical model
(Elsevier, 2025-06) Wernli, Stephan; Huber, Lilach Goren; Avdelidis, Nicolas P.; Rieder, Alfred
The Coriolis mass flow meter is a critical instrument used in various industries for the precise measurement of mass flow rate and density of a fluid. Despite its widespread use, the impact of entrained particles within the fluid can significantly affect the accuracy of the meter, leading to potential errors and inefficiencies. Previous calculations of the mass flow errors assumed that the entrained particles are uniformly distributed along the axis of the measurement tube. In this paper we extend the analytical investigation of the measurement errors beyond the previous work to the regime of non-uniform density distribution of the entrained particles. We provide a clear analysis of the contributions of various physical effects in this regime to the mass-flow measurement error.
Open Access
Influence of thermal contrast and limitations of a deep-learning based estimation of early-stage tumour parameters in different breast shapes using simulated passive and dynamic thermography
(Elsevier, 2025-04) Moraes, M. F. B.; Sfarra, Stefano; Fernandes, Henrique; Figueiredo, Alisson A. A.
To enhance diagnostic sensitivity compared to passive thermography, thermal stress can be applied to the breast surface with the temperatures being measured in the thermal recovery phase, a process called dynamic thermography. This study aims to evaluate the limitations of both passive and dynamic thermography in estimating early-stage tumour parameters across different breast shapes and how to improve the results. Three breast models with thermoregulation were solved numerically using COMSOL Multiphysics®. A neural network developed in PyTorch was used to estimate breast tumour location and size. The estimates obtained using each approach were compared, and the effects of thermal contrast, noise, and tumour depth range were analysed. Dynamic thermography provided the most accurate estimates compared to passive thermography, with mean error reductions that reached up to 33.25%. Additionally, the number of estimates with errors higher than 10% was up to 48.42% lower. Tumour radius showed the lowest noise threshold, providing the highest estimations errors. Adding deeper tumours to the datasets caused mean error increases of up to 51.27%. Thus, this work contributes by comparing both types of thermography, analysing thermal aspects of the temperature data that influences the neural network's estimation process, and suggesting alternatives to improve its accuracy.
Open Access
Recovery from startle and surprise: a survey of airline pilots' operational experience using a startle and surprise management method
(Elsevier, 2025-05-01) Vlaskamp, Daan; Landman, Annemarie; van Rooij, Jeroen; Blundell, James
A significant safety challenge airline pilots contend with is the possibility of experiencing startle and surprise. These are cognitive-emotional responses that may temporarily impair performance and that have contributed to multiple fatal loss of control events. Several self-management methods exist that are intended to facilitate recovery from startle and surprise, but these have only been tested in simulator experiments. The current study addresses this research gap by surveying the perceptions of 239 airline pilots on the utility and benefit of a method which they use in operational practice– the “Reset Method”. Overall, the survey results revealed that pilots felt the method improved mental preparedness, and reduced stress. A reported reason for not applying the method was the urge to act quickly. In addition, not all steps of the method were applied equally, and some pilots found the method difficult to fit into the existing procedures of several time-critical scenarios (e.g., aircraft upsets and emergency landings). We recommend training self-management methods in scenarios which carry the most risk of negative effects of startle and surprise. We also recommend instilling awareness of the ‘startle paradox': self-management techniques are most difficult to apply in situations where they are most beneficial. Method shortening and simplification may facilitate application. Future research should focus on refining the method's implementation, addressing the startle paradox, and understanding the transferability of startle and surprise management methods to other safety critical industries defined by complex sociotechnical interactions.
Open Access
The ‘hangar of the future’ for sustainable aviation
(Cambridge University Press (CUP), 2024-11) Plastropoulos, Angelos; Fan, Ip-Shing; Avdelidis, Nicolas P.; Angus, Jim; Maggiore, John; Atkinson, Helen
Sustainability is becoming a major strategic driver within the aviation industry, which has moved from providing primarily economic benefits to delivering the ‘triple bottom line’, including social and environmental impact as well as financial performance. Sustainable aviation is also being tracked by the International Civil Aviation Organisation (ICAO) Global Collation for Sustainable Aviation. Operations and Infrastructure is an important near-term opportunity to deliver sustainability benefits. Digital Technologies, Integrated Vehicle Health Management (IVHM) and Maintenance Repair and Overhaul (MRO) play a prominent role in implementing these benefits, with a particular focus on operational efficiencies. As part of this, the sustainable smart hangar of the future is a concept that is becoming more and more important in forming the future of the aviation industry. The Hangar of the Future is an excellent opportunity for innovation, combining the progress in manufacturing, materials, robotics and artificial intelligence technologies. Succeeding in developing a hangar with these characteristics will provide us with potential benefits ranging from reduced downtime and costs to improved safety and environmental impact. This work explores some of the key features related to the sustainable smart hangar of the future by discussing research that takes place in DARTeC’s (Digital Aviation Research and Technology Centre) hangar led by the IVHM Centre in Cranfield. Additionally, the paper touches on some longer-term aspirations.
Open Access
Battery pack technological considerations for hybrid-electric regional aircraft feasibility
(Cambridge University Press (CUP), 2025-05) Spinelli, Andrea; Krupa, Gustavo P.; Kipouros, Timoleon; Laskaridis, Panos; Berseneff, Boris
This paper presents a study of the effects of the durability and level of energy storage technology on energy management strategies and the performance of hybrid electric turboprops. The results highlight the key role of battery energy density on the durability of the battery pack and the viability of the concept of hybrid electric aircraft. Additionally, the trade-off between zero-day environmental compatibility and battery lifetime is identified, caused by the size of the pack. The effective energy density would decrease with the aging of the cells, leaving a significant inert mass and increasing fuel consumption. Optimal energy management strategies are suggested in light of this new information. Higher specific energy of the pack would mitigate this aspect, along with a reduction in fuel consumption and NOx emissions. Indeed, the improvement of environmental compatibility was found to be nonlinear with a positive rate, suggesting high returns in investing in great improvements in energy density over a gradual increase. This result relates to the results of the statistical technological forecast presented in this study, which, without an increase in funding, predicts the availability of the specific energy required to match the fuel-only baseline in the 2040–2050 decade.
Open Access
Assessment of hydrogen storage and pipelines for hydrogen farm
(MDPI, 2025-02-27) Alssalehin, Esmaeil; Holborn, Paul; Pilidis, Pericles
This paper presents a thorough initial evaluation of hydrogen gaseous storage and pipeline infrastructure, emphasizing health and safety protocols as well as capacity considerations pertinent to industrial applications. As hydrogen increasingly establishes itself as a vital energy vector within the transition towards low-carbon energy systems, the formulation of effective storage and transportation solutions becomes imperative. The investigation delves into the applications and technologies associated with hydrogen storage, specifically concentrating on compressed hydrogen gas storage, elucidating the principles underlying hydrogen compression and the diverse categories of hydrogen storage tanks, including pressure vessels specifically designed for gaseous hydrogen containment. Critical factors concerning hydrogen gas pipelines are scrutinized, accompanied by a review of appropriate compression apparatus, types of compressors, and particular pipeline specifications necessary for the transport of both hydrogen and oxygen generated by electrolysers. The significance of health and safety in hydrogen systems is underscored due to the flammable nature and high diffusivity of hydrogen. This paper defines the recommended health and safety protocols for hydrogen storage and pipeline operations, alongside exemplary practices for the effective implementation of these protocols across various storage and pipeline configurations. Moreover, it investigates the function of oxygen transport pipelines and the applications of oxygen produced from electrolysers, considering the interconnected safety standards governing hydrogen and oxygen infrastructure. The conclusions drawn from this study facilitate the advancement of secure and efficient hydrogen storage and pipeline systems, thereby furthering the overarching aim of scalable hydrogen energy deployment within both energy and industrial sectors.
Open Access
Brief review of vibrothermography and optical thermography for defect quantification in CFRP material
(MDPI, 2025-03-16) Hidayat, Zulham; Avdelidis, Nicolas P.; Fernandes, Henrique
Quantifying defects in carbon-fiber-reinforced polymer (CFRP) composites is crucial for ensuring quality control and structural integrity. Among non-destructive evaluation techniques, thermography has emerged as a promising solution for defect detection and characterization. This literature review synthesizes current advancements in active thermography methods, with a particular focus on vibrothermography and optical thermography, in identifying defects such as delaminations and BVID in CFRP composites. The review evaluates state-of-the-art techniques, highlighting the advanced applications of optical thermography. It identifies a critical research gap in the integration of vibrothermography with advanced image-processing methods, such as computer vision, which is more commonly applied in optical thermography. Addressing this gap holds significant potential to enhance defect quantification accuracy, improve maintenance practices, and ensure the safety of composite structures.
Open Access
Emerging decision-making for transportation safety: collaborative agent performance analysis
(MDPI, 2025-01-15) Maguire-Day, Jack; Al-Rubaye, Saba; Warrier, Anirudh; Sen, Muhammet A.; Whitworth, Huw; Samie, Mohammad
This paper addresses the challenge of improving decision-making capabilities and safety in autonomous vehicles (AVs) using Agent-Based Modelling (ABM). The study evaluates ABM’s effect on Advanced Driver Assistance Systems (ADASs) in challenging driving situations, like lane merging, by incorporating it into a simulation framework designed for autonomous vehicles. Identifying emergent behaviours that enhance safety and efficiency, verifying the efficacy of ABM in AV decision-making, and investigating the function of hardware acceleration to enable practical application in ADASs are some of the major achievements. According to the simulation results, ABM can greatly improve AV performance, providing a practical and scalable means of enhancing safety in future transportation systems.
Open Access
Vertical-horizontal actor collaboration in governance network: a systematic review
(Springer, 2024-12-01) Hendra, Oke; Prasojo, Eko; Fathurrahman, Reza; Pilbeam, Colin
This research proposes a categorization framework to analyse multi-actor collaboration variations in governance network. It examines both vertical (government levels) and horizontal (sectors) interactions. This study reviewed 92 academic articles, adhering to the PRISMA methodology and utilizes 2 × 2 and "who-how-what" frameworks to capture the breadth of vertical-horizontal collaboration arrangements. The study identifies a rise in multi-actor collaborations and a dominance of qualitative research. It exposes research gaps: limited cross-sectoral and international actor studies, and under-researched sectors beyond environment. The proposed framework, capturing actors, levers, purposes, and context, aims to guide future research on vertical-horizontal actor collaboration in governance network.
Open Access
Temperature-dependent solid material properties of GRCop-42 for an additively manufactured liquid rocket engine LOx cooling channel
(University of Miskolc, 2024-11-06) Monokrousos, Nikos; Könözsy, László; Pachidis, Vassilios; Sozio, Ernesto; Rossi, Federico
Recent technological developments in the field of Additive Manufacturing (AM) provide a number of opportunities for the utilisation of high-performance copper alloys for aerospace applications. The additively manufactured LOx/LNG DemoP1 aerospike engine demonstrator designed by Pangea Aerospace is a characteristic example based on the Direct Metal Laser Sintering (DMLS) technology. The aerospike engine thrust chamber and LOx cooling channels are manufactured using GRCop-42 material powder, a Cu-Cr-Nb based copper alloy developed by the National Aeronautics and Space Administration (NASA) for the regenerative cooling technology of high thermal demand thrust chambers and nozzles. In the current work temperature-dependent correlations are derived for the density, specific heat capacity at constant pressure and thermal conductivity of the GRCop-42 material. The correlations for the solid material properties are then introduced into the ANSYS Fluent 2023 R2 Computational Fluid Dynamics (CFD) package and their capabilities are investigated for the characterisation of the flow-field characteristics of the LOx flow in the cooling channel. The numerical solution of the coolant flow in the AM cooling channel is compared against experimental data of the DemoP1 engine demonstrator. The main objective of this study is to provide a realistic physical description of the temperature-dependent properties of the AM solid material in high heat flux applications where the material properties are mostly considered as constant in previous studies.