Staff publications (SATM)

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An experimental and simulation screening of X-65 steel weldment corrosion in high flow rate conditions
(Elsevier, 2024-04-01) Nofrizal, Nofrizal; Wulandari, Meyliana; Impey, Susan; Georgarakis, Konstantinos; Papanikolaou, Michail; Raja, Pandian Bothi
Over many decades, the oil and gas industry has encountered significant challenges due to weldment corrosion. The issue of internal-pipeline local corrosion at the welded joint region has garnered significant concern, especially due to the combined impact of high shear stress and electrochemical corrosion. This combination can lead to pipeline rupture with relative ease. Hence, a new approach to screen the flow corrosion of X-65 steel via electrochemical methods, predicting fluid shear stress and velocity using computational fluid dynamic (CFD) simulation is positively tested and presented here. For that, the X-65 steel specimens were cut/designed as the inner, centre, and outer electrodes of the target to analyse the Weld Metal (WM), Heat Affected Zone (HAZ), and Parent Metal (PM). Electrochemical screening was carried out simultaneously at a flow of 10 m/s using a brine solution saturated with CO2. The PM and HAZ will corrode less than the WM, in some cases at 30–23% of the rate of the WM. Thus in an environment of uninhibited brine saturated with CO2 at 10 m/s, preferential weld corrosion (PWC) is expected to occur. In addition, the surface morphology screening (scanning electron microscope with energy dispersive x-ray analysis, X-Ray diffraction, focus ion beam, raman spectroscopy) was employed to monitor the corrosion damage on the metal surface and also to support the electrochemical measurements (linear polarization resistance, galvanic measurement, and electrochemical impedance spectroscopy).
Embargo
Safety leadership and safety citizenship behavior: the mediating roles of safety knowledge, safety motivation, and psychological contract of safety
(Taylor and Francis, 2024-06-13) Omidia, Leila; Karimi, Hossein; Pilbeam, Colin; Mousavi, Saeid; Moradi, Gholamreza
The relationship between safety leadership and safety citizenship behavior (SCB) is well established in prior research; however, the effects of safety knowledge, safety motivation, and psychological contract of safety (PCS) on this relationship still need to be examined. This study investigated the mediating roles of safety knowledge, safety motivation, and psychological contract of safety in the relationship between safety leadership and SCB. Cross-sectional survey data were gathered from 205 employees in a high-risk industry in Iran. Path analysis showed that safety knowledge, safety motivation, and PCS played mediating roles between safety leadership and SCB. Improving the safety of employees and enhancing safety in organizations can be achieved by considering the significance of safety leadership and enhancing SCB among employees. Creating environments with higher levels of fulfillment of safety obligations between leaders and employees is important in achieving safety goals.
Open Access
Practices and challenges of safety management in outsourced facilities management
(Elsevier, 2024-06-24) Pilbeam, Colin
Introduction: Outsourcing is a commonly occurring organizational activity, but one associated with negative occupational safety outcomes. Improving the management of safety in workplaces where contractors are employed is vital, but under-researched in the service sectors. The aims of this paper were to investigate both the practices and challenges of safety management in outsourced facility management (FM), an important global service sector. Method: Twenty-three semi-structured interviews were conducted with clients and contractors in three different FM outsourcing arrangements between large corporations in the UK. Data were thematically coded against frameworks derived from existing literature to identify deployed safety management practices and reveal challenges associated with safety management in these outsourced relationships. Results: Safety management practices in outsourced FM conformed to known practices clustering into four previously identified categories (planning, selecting, on-site working, and checking). A fifth category (reviewing) was not observed. Operating across national boundaries, applying national contracts locally, working with mandated KPIs, and contract specifications all created new challenges for safety management not previously reported. Other known challenges associated with economic pressure and disorganization were observed. Conclusion: Safety management practices observed in safety critical industries also apply in FM. However, the challenges of safety management in these three cases included regulatory failures that have not been routinely identified in other empirical studies of safety in outsourcing arrangements. Practical application: Adopting widely accepted safety management practices support safer working in outsourced FM and encourage cross-sector learning. New challenges for safety management noted here encourage consideration of unintended consequences of contract terms and conditions, require corporate agreement on how to ensure safety compliance when working transnationally, and a review of decision-making and processes and procedures to enable effective and safe working locally.
Open Access
Exploring potential causal models for climate-society-conflict interaction
(Scitepress, 2023-04-22) Guo, Weisi; Sun, Schyler; Wilson, Alan
Climate change affects human liveability and may increase the likelihood of armed violence. However, the precise repercussions on social cohesion and conflict are difficult to model, and several socio-economic mechanisms exist between local climate changes and conflict, and are often hidden to us. Nonetheless, we offer an exploratory data analysis in this paper at a global scale, on the relationship between diverse climate indicators and conflict. Here we investigate potential basic causal models between climate change and conflict, including the causal direction, causal lag, and causal strength. We use historical climate and extreme environmental event data from the past 50 years across the world to identify geographic region-specific causal indicators. The initial broad findings are: (1) rainfall is a reasonably general indicator of conflict, (2) there are fragile regions which exhibit a strong causal link between extreme climate variations and conflict (predominantly in Africa and South Asia), and 3. there exists a common time lag of the causality between the climate variations and the conflict in many regions, which is worth further study.
Open Access
Design and validation of structural causal model: a focus on SENSE-EGRA datasets
(Society of Visual Informatics (SOTVI), 2023-12-15) Ayem, Gabriel Terna; Nsang, Augustine Shey; Igoche, Bernard Igoche; Naankang, Garba
Designing and validation of causal model correctness from a dataset whose background knowledge is gotten from a research process is not a common phenomenon. In fact, studies have shown that in many critical areas such as healthcare and education, researchers develop models from direct acyclic graphs without testing them. This phenomenon is worrisome and is bound to cast a dark shadow on the inference estimates that many arise from such models. In this study, we have design a novel application-based SCM for the first time using the background knowledge gotten from the American university of Nigeria (AUN), Yola, on the letter identification subtask of Early Grade reading Assessment (EGRA) program on Strengthen Education in Northeast Nigeria (SENSE-EGRA) project dataset, which was sponsored by the USAID. We employed the conditional independence test (CIT) criteria for the model’s correctness validation testing, and the results shows a near perfect SCM.
Open Access
Consensus-based deep reinforcement learning for mobile robot mapless navigation
(IEEE, 2024-06-05) Liu, Wenxing; Niu, Hanlin; Caliskanelli, Ipek; Xu, Zhengjia; Skilton, Robert
When using mobile robots to perform data collection about the surroundings, the performance might be dissatisfying since the environments could be unknown and challenging. This situation will pose challenges for mobile robot navigation and exploration. To tackle this issue, we propose a consensus-based deep reinforcement learning (DRL) algorithm for multiple robots to perform mapless navigation and exploration. The proposed algorithm leverages both consensus-based training and DRL, which reduces required training steps while maintaining the same training reward. Once trained with fixed obstacles, the proposed training model can demonstrate adaptability in handling real-world random static obstacles and sudden obstacles. The experimental video is available at: at: https://youtu.be/ym2yvbKg4fU.
Open Access
An innovative tactile sensor roller for composites inspection
(IEEE, 2024-06-05) Lu, Zhenyu; Li, Xiaolong; Li, Tunwu; Xu, Xiaodong; Yang, Chenguang
A vision-based tactile sensor roller prototype has been designed and developed to detect defects on composite prepreg and dry fabric surfaces. The tactile sensor features an innovative design comprising a transparent acrylic tube encased in a gel elastomer. The outer tube serves as a protective and flexible layer, while the inner structure includes a connecting shaft equipped with a camera, force, and speed sensors. This configuration allows for detailed capture of tactile information, integrating visual and pressure data for comprehensive sensory feedback. The connecting shafts are fitted with wheels and handles at both ends, enabling human manipulation and control. Typical defects such as wrinkles, gaps, overlaps and foreign objects and debris (FOD) can be detected by this prototype. In this study, we assessed the performance of the tactile sensor roller by rolling it across areas affected by human-made composite prepreg and dry fabric defects that include wrinkles and foreign objects. With the comparison of the tactile image results, we have demonstrated that the tactile sensor roller can identify flaws with a precision of 0.125mm. It can efficiently examine a 35cm by 18cm section of woven fabric without compromising the integrity of the 3D data gathered. This innovative tactile sensor is set to enhance the automation of the hand layup process. It enables real-time quality control, substantially reducing the need for extensive manual inspections. This leads to a significant cut in inspection costs, making the manufacturing process both more efficient and cost-effective.
Open Access
Is there a need for robots with moral agency? a case study in social robotics
(IEEE, 2024-06-05) Raper, Rebecca
There has been significant recent interest in the risks associated with Artificial Intelligence (AI), so much so that a Global AI Summit was recently hosted at Bletchley Park in the United Kingdom. One supposed risk associated with Artificial Intelligence is the threats that might be associated with an Artificial General Intelligence (AGI) carrying out acts detrimental to humanity. In the past, some researchers have attempted to bestow machines with morals to mitigate against these types of threat, however, in recent times the approach has been largely dismissed, with claims that giving machines moral agency poses more of a threat in of itself, than preventing it. One critique of the calls of the risk associated with AGI is that it is unrealistic, and that there is no grounding for any threat to humanity. The aim of this paper is to present a case study in social robotics to illustrate two points: 1) what real-life risks associated with AI might be, and 2) to reinstate the discussion surrounding whether there is a requirement for robots with moral agency.
Open Access
Reduced-order model prediction of far-field mixing noise from internally-notched nozzles
(AIAA, 2024-05-30) de Souza, Francisco J.; Lawrence, Jack; Proenca, Anderson
This work presents a numerical investigation of the effect of internal notches on the reduction of jet mixing noise from round nozzles. The baseline jet is produced by the University of Southampton’s Doak Laboratory 40mm-diameter convergent, round nozzle. Numerical predictions of mixing noise for both round and internally-notched nozzles are conducted using a Generalized Acoustic Analogy that relies on Reynolds-Averaged Navier-Stokes (RANS) solutions of the nozzle flows, particularly the one proposed by Leib and Bridges. In this method, the RANS variables of interest, including mean axial velocity, Mach number, density, turbulence kinetic energy, and its dissipation rate, are interpolated onto a cylindrical structured grid suitable for aeroacoustic calculations. Subsequently, the respective Green’s function and a hybrid spectral-time source model are computed, and power spectral densities at various polar and azimuthal angles are predicted. Comparison between predictions and experiments demonstrates good qualitative agreement for both nozzles, although the inversion in trends at certain Strouhal numbers is not captured by the numerical model. Additionally, the significance of the numerical scheme’s order employed to solve the adjoint Green’s function is evaluated. To elucidate the noise reduction attributed to internal notches, distributions of turbulent kinetic energy are analyzed at different azimuthal cross-sections.
Open Access
Prediction of far-field noise from installed corrugated nozzles
(AIAA, 2024-05-30) de Souza, Francisco J.; Lawrence, Jack; Cruz, Ricardo H.; Proenca, Anderson
In this study, a reduced order model, devised by Lyu and Dowling, is used to predict the farfield installation noise of corrugated nozzles installed beneath a NACA aerofoil. A complementary investigation, detailed in another paper, reveals that employing square corrugations near the nozzle lip diminishes jet-surface interaction (JSI) noise compared to a round 40-mm diameter nozzle. This reduction is particularly notable for Strouhal numbers ranging from 0.3 to 0.9 and at high polar angles. The near-field pressure data, required for Lyu and Dowling’s model, is gathered using a circular array consisting of eight 1/8-inch microphones in the Doak Laboratory, at the University of Southampton, UK. Generally, the predictions align well with the experimental trends for Mach numbers ranging from 0.4 to 1 under static ambient flow conditions. Furthermore, it is observed that a minimum of four azimuthal modes must be available to accurately predict the noise generated by the corrugated nozzles. The effects of free-stream Mach number, particularly focusing on the predictive capacity of Lyu and Dowling’s model, are also investigated. Quantitative agreement at Strouhal numbers between 0.1 and 0.5 in evidenced.
Open Access
Framework for multi-fidelity assessment of open rotor propeller aeroacoustics
(AIAA, 2024-05-30) Huang, Guangyuan; Sharma, Ankit; Chen, Xin; Riaz, Atif; Jefferson-Loveday, Richard
Aerodynamically generated noise from open rotor aircraft has received immense research interests. Multi-fidelity numerical approaches are in demand for evaluating open rotor propeller noise without compromising computational accuracy and reducing cost. In this paper, propeller noise modelling methods at different fidelity levels are assessed by application to an aircraft propeller configuration at an advance ratio of 0.485 together with tip Reynolds and Mach numbers of 3.7×10^5 and 0.231, respectively. The flow solution of the propeller is obtained using coarse-grid Large Eddy Simulation and then inputted into three acoustic solvers. At higher-fidelity level, Ffowcs-Williams and Hawkings analogy method is employed. Hanson’s method and Gutin’s method are applied at the medium- and lower -fidelity levels, respectively. Results from the three models are compared correlatively, as well as against existing experimental measurement data. Through the assessment, insight is given into future development of a multi-fidelity model for low-emission open rotor aircraft design. The presented multi-fidelity framework is being developed as part of the Innovate UK, Aerospace Technology Institute (ATI) funded research project – ONEheart (Out of Cycle NExt generation highly efficient air transport).
Open Access
Novel prognostic methodology of bootstrap forest and hyperbolic tangent boosted neural network for aircraft system
(MDPI, 2024-06-10) Fu, Shuai; Avdelidis, Nicolas P.
Complex aviation systems’ integrity deteriorates over time due to operational factors; hence, the ability to forecast component remaining useful life (RUL) is vital to their optimal operation. Data-driven prognostic models are essential for system RUL prediction. These models benefit run-to-failure datasets the most. Thus, significant factors that could affect systematic integrity must be examined to quantify the operational component of RUL. To expand predictive approaches, the authors of this research developed a novel method for calculating the RUL of a group of aircraft engines using the N-CMAPSS dataset, which provides simulated degradation trajectories under real flight conditions. They offered bootstrap trees and hyperbolic tangent NtanH(3)Boost(20) neural networks as prognostic alternatives. The hyperbolic tangent boosted neural network uses damage propagation modelling based on earlier research and adds two accuracy levels. The suggested neural network architecture activates with the hyperbolic tangent function. This extension links the deterioration process to its operating history, improving degradation modelling. During validation, models accurately predicted observed flight cycles with 95–97% accuracy. We can use this work to combine prognostic approaches to extend the lifespan of critical aircraft systems and assist maintenance approaches in reducing operational and environmental hazards, all while maintaining normal operation. The proposed methodology yields promising results, making it suitable for adoption due to its relevance to prognostic difficulties.
Open Access
Investigation of wind turbine static yaw error based on utility-scale controlled experiments
(IEEE, 2024-05-08) Astolfi, Davide; De Caro, Fabrizio; Pasetti, Marco; Gao, Linyue; Pandit, Ravi; Vaccaro, Alfredo; Hong, Jiarong
Wind energy represents a promising alternative to replace traditional fossil-based energy sources. For this reason, increasing the efficiency in the conversion process from wind to electrical energy is crucial. Unfortunately, the presence of systematic errors (mostly related to the yaw and pitch angles) is one of the key factors causing underperformance, and for this reason, it requires adequate identification. The present work deals with diagnosing wind turbine static yaw error, occurring when the wind vane sensor is incorrectly aligned with the rotor shaft. A thorough investigation methodology is proposed by considering a unique experimental test-up shared by the Eolos Wind Research Station. A utility-scale wind turbine has been imposed to operate subjected to several static yaw errors and reference meteorological data collected nearby the wind turbine were available. By analyzing the relation between the meteorological data and the SCADA data collected by the wind turbine, a systematic alteration in the measurements of nacelle wind speed in the presence of the yaw error is explicitly shown. This phenomenon has been overlooked in the literature and leads to revisiting the methods mostly employed for the diagnosis of the error. Furthermore, a correlation between the presence of static error, increased blade pitch, and heightened levels of tower vibration is observed. In summary, this work provides a comprehensive characterization of the experimental evidence associated with the presence of a wind turbine static yaw error. This paves the way for more effective diagnostic techniques for wind turbine yaw errors, potentially revolutionizing data-driven maintenance strategies.
Open Access
Path-tracking control at the limits of handling of a prototype over-actuated autonomous vehicle
(Taylor & Francis, 2024-05-31) Lin, Chenhui; Siampis, Efstathios; Velenis, Efstathios
Considering the vehicle dynamics at the limits of handling is vital to improve the performance and safety of autonomous vehicles especially in extreme situations. This paper presents the development of a path-tracking controller for an over-actuated autonomous vehicle. The vehicle is an electric prototype equipped with torque vectoring and four-wheel steering, which enable enhanced control of vehicle dynamics. A model predictive controller is proposed taking into account the nonlinearities in vehicle dynamics at the limits of handling as well as the crucial actuator constraints. The controller is examined in both high-fidelity simulation and practical testing to validate the vehicle's handling performance. Both the simulation and testing results illustrate that the over-actuation topology can enhance the handling performance as well as vehicle stability at conditions close to the limits of handling. With additional references such as side slip angle, the vehicle's attitude under such extreme condition can also be manipulated. The testing also demonstrates the real-time capability of the controller. Further testing has been done to confirm that side slip angle reference plays an important role in path-tracking control at the limits of handling, and to push the vehicle to the friction limits.
Open Access
Practice effects of a breathing technique on pilots’ cognitive and stress associated heart rate variability during flight operations
(Taylor & Francis, 2024-06-10) Zhang, Jingyi; Li, Wen-Chin; Braithwaite, Graham; Blundell, James
Commercial pilots endure multiple stressors in their daily and occupational lives which are detrimental to psychological well-being and cognitive functioning. The Quick coherence technique (QCT) is an effective intervention tool to improve stress resilience and psychophysiological balance based on a five-minute paced breathing exercise with heart rate variability (HRV) biofeedback. The current research reports on the application of QCT training within an international airline to improve commercial pilots’ psychological health and support cognitive functions. Forty-four commercial pilots volunteered in a one-month training programme to practise self-regulated QCT in day-to-day life and flight operations. Pilots’ stress index, HRV time-domain and frequency-domain parameters were collected to examine the influence of QCT practice on the stress resilience process. The results demonstrated that the QCT improved psychophysiological indicators associated with stress resilience and cognitive functions, in both day-to-day life and flight operation settings. HRV fluctuations, as measured through changes in RMSSD and LF/HF, revealed that the resilience processes were primarily controlled by the sympathetic nervous system activities that are important in promoting pilots’ energy mobilization and cognitive functions, thus QCT has huge potential in facilitating flight performance and aviation safety. These findings provide scientific evidence for implementing QCT as an effective mental support programme and controlled rest strategy to improve pilots’ psychological health, stress management, and operational performance.
Embargo
Energy consumption optimisation for unmanned aerial vehicle based on reinforcement learning framework
(Inderscience, 2024-04-16) Wang, Ziyue; Xing, Yang
The average battery life of drones in use today is around 30 minutes, which poses significant limitations for ensuring long-range operation, such as seamless delivery and security monitoring. Meanwhile, the transportation sector is responsible for 93% of all carbon emissions, making it crucial to control energy usage during the operation of UAVs for future net-zero massive-scale air traffic. In this study, a reinforcement learning (RL)-based model was implemented for the energy consumption optimisation of drones. The RL-based energy optimisation framework dynamically tunes vehicle control systems to maximise energy economy while considering mission objectives, ambient circumstances, and system performance. RL was used to create a dynamically optimised vehicle control system that selects the most energy-efficient route. Based on training times, it is reasonable to conclude that a trained UAV saves between 50.1% and 91.6% more energy than an untrained UAV in this study by using the same map.
Open Access
Bipartite consensus of nonlinear agents with actuator fault
(IEEE, 2024-05-22) Mondal, Sabyasachi; Tsourdos, Antonios
This paper introduces a bipartite consensus controller to address the challenge of achieving consensus among nonlinear agents, particularly when actuator faults are present, leading to significant obstacles. To tackle this issue, the controller is developed by adapting the Distributed Nonlinear Dynamic Inversion (DNDI) technique, thereby accommodating the impact of actuator faults. The randomness of the actuator the fault is taken into account to reflect real-world conditions. The the paper also furnishes comprehensive mathematical insights into the convergence of the fault-tolerant controller, establishing a robust theoretical foundation. An extensive array of simulation studies demonstrate that the proposed controller effectively manages actuator faults, leading to the successful attainment of bipartite consensus.
Open Access
Quaternion-based attitude estimation of an aircraft model using computer vision
(MDPI, 2024-06-12) Kasula, Pavithra; Whidborne, James F.; Rana, Zeeshan A.
Investigating aircraft flight dynamics often requires dynamic wind tunnel testing. This paper proposes a non-contact, off-board instrumentation method using vision-based techniques. The method utilises a sequential process of Harris corner detection, Kanade–Lucas–Tomasi tracking, and quaternions to identify the Euler angles from a pair of cameras, one with a side view and the other with a top view. The method validation involves simulating a 3D CAD model for rotational motion with a single degree-of-freedom. The numerical analysis quantifies the results, while the proposed approach is analysed analytically. This approach results in a 45.41% enhancement in accuracy over an earlier direction cosine matrix method. Specifically, the quaternion-based method achieves root mean square errors of 0.0101 rad/s, 0.0361 rad/s, and 0.0036 rad/s for the dynamic measurements of roll rate, pitch rate, and yaw rate, respectively. Notably, the method exhibits a 98.08% accuracy for the pitch rate. These results highlight the performance of quaternion-based attitude estimation in dynamic wind tunnel testing. Furthermore, an extended Kalman filter is applied to integrate the generated on-board instrumentation data (inertial measurement unit, potentiometer gimbal) and the results of the proposed vision-based method. The extended Kalman filter state estimation achieves root mean square errors of 0.0090 rad/s, 0.0262 rad/s, and 0.0034 rad/s for the dynamic measurements of roll rate, pitch rate, and yaw rate, respectively. This method exhibits an improved accuracy of 98.61% for the estimation of pitch rate, indicating its higher efficiency over the standalone implementation of the direction cosine method for dynamic wind tunnel testing.
Open Access
Communication network architecture with 6G capabilities for urban air mobility
(IEEE, 2024-02-28) Al-Rubaye, Saba; Conrad, Christopher; Tsourdos, Antonios
As the demand for urban air mobility (UAM) increases, a robust communication, navigation, and surveillance (CNS) network architecture is needed to support the integration of sustainable UAM vehicles and technologies. Specifically, a new digital communication infrastructure is imperative to support increased levels of digitisation and autonomy within the aviation industry. This infrastructure must remain compatible with existing technologies, while enabling the integration of future 6G systems. This paper thereby discusses the communication challenges and opportunities associated with UAM integration. Potential communication technologies and standards needed to support UAM operations are presented and consolidated into a unified communication architecture with ground-, air-, and satellite-based infrastructure. The functional requirements of this architecture are also discussed, to enable seamless communication between UAM vehicles, air traffic control, and other ground- or air-based systems. Notably, 6G is highlighted as a key enabler of dense and sustainable UAM operations with high data traffic demands. A simple link budget analysis for a 6G air-to-ground data link in a green urban environment is thereby performed, em-phasising the infrastructural development necessary to support 6G roll-out. These findings pave the way for a more sustainable and accessible UAM transportation system, backed by a secure and reliable communication infrastructure.
Open Access
Simulating enhanced vertiport management in a multimodal transportation ecosystem
(IEEE, 2024-05-13) Conrad, Christopher; Xu, Yan; Panda, Deepak; Tsourdos, Antonios
The advanced air mobility (AAM) industry envisions a transformative transportation ecosystem for passengers and cargo deliveries. Nonetheless, coordinating large volumes of new aerial vehicles necessitates innovative unmanned aircraft system (UAS) traffic management (UTM) solutions, supported by a robust vertiport infrastructure. Moreover, AAM will form part of a broader multimodal ecosystem, posing additional technical, procedural and operational challenges. This work thereby presents a simulation tool in AnyLogic for deploying, training and testing collaborative and intelligent AAM decision-making frameworks within a multimodal transportation system. The platform integrates multiple vertiports with diverse resource constraints, and offers a flexible solution to investigate the impact of different vertiport designs, layouts and procedures. AAM-specific influences are also introduced, including electric vehicle batteries, heterogeneous vehicle specifications, stricter flight envelopes, and hyper-local micro-weather variations. The model further acknowledges the complex inter-dependencies within a multimodal environment to capture fluctuating travel demands and dynamic passenger flows within transportation terminals. This scalable simulation tool thereby enables the development of enhanced vertiport management and AAM traffic coordination solutions, and facilitates exploratory research on multimodal coordination amongst air, ground, rail and sea transportation systems.