Staff publications (SATM)

Permanent URI for this collection

https://dspace.lib.cranfield.ac.uk/handle/1826/8738

Browse

Now showing 1 - 20 of 4731

Open Access
The role of behavioural and environmental economics in sustainable manufacturing
(Springer, 2023-12-04) Kaur, Rashmeet; Patsavellas, John; Salonitis, Konstantinos
Sustainable 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.
Open Access
Analyzing frictional noise for wear monitoring under dry and lubrication condition: experimental modelling with pin-on-disc tribometer
(Trans Tech Publications Ltd, 2025-01-06) Kalifa, Mohamed; Starr, Andrew; Khan, Muhammad
In industrial settings, the use of frictional noise to improve wear monitoring is highly promising. It enables the identification of changes in friction and wear conditions, the assessment of different phases of wear, and the examination of the impact of wear on machine performance. By analysing acoustic signatures, it is conceivable to continuously monitor the wear characteristics and surface conditions. This helps in predicting wear and detecting aberrant wear regimes in real-time. The data demonstrate that in dry conditions, the aluminum disc has higher coefficients of friction relative to cast iron and mild steel, likely due to the absence of graphite flakes in aluminum. Under lubricated conditions, a layer of lube significantly decreases the coefficient of friction, with no apparent deviations across the materials, demonstrating that complete lubrication avoids direct metal contact. In lubrication-starved applications, oily depictions nevertheless help minimize friction, though less efficiently than complete lubrication. In dry conditions, frictional sound levels for mild steel are higher due to direct surface hits, while lubrication reduces noise by eliminating metal-on-metal contact. As a result, monitoring noise levels is a helpful indicator of lubrication difficulties, aiding in maintenance and repairs.
Open Access
Navigating circular economy and digitalisation: a comparative study of manufacturing strategies in the UK and Saudi Arabia
(Elsevier, 2024-05-29) Sarfraz, Shoaib; Sherif, Ziyad; Alshammari, Serhan; Salonitis, Konstantinos
This study presents an integrated framework for evaluating manufacturing maturity in embracing circular economy principles and digital technologies, with a focus on comparing best practices between the UK and Saudi Arabia. The framework incorporates circular economy principles, such as waste elimination, material circulation, and nature regeneration, across product, process, and business model innovations. It also encompasses key Industry 4.0 technologies that facilitate smart and connected manufacturing. Utilising secondary data sources, the research maps the capabilities of selected manufacturers in both countries across categories including operations and technology. The findings indicate that the UK leads in most areas due to its sustained emphasis on sustainability and digitalisation over the past decade. In contrast, Saudi Arabia exhibits a lack of concrete policies and investments in these domains but demonstrates the potential for adapting UK practices to its unique context. The study proposes a staged roadmap to guide Saudi Arabia in a systematic transition towards circular and digital manufacturing, emphasising coordinated efforts in policy, infrastructure development, skills enhancement, and industry collaboration. This comparative assessment offers valuable insights into manufacturing best practices and opportunities for improvement.
Open Access
Impedimetric biosensors for the quantification of serum biomarkers for early detection of lung cancer
(MDPI, 2024-12-01) Arabnejad, Mahdi; Tothill, Ibtisam E.; Chianella, Iva
Lung cancer is the most common type of cancer diagnosed worldwide and is also among the most fatal. Early detection, before symptoms become evident, is fundamental for patients’ survival. Therefore, several lung cancer biomarkers have been proposed to enable a prompt diagnosis, including neuron-specific enolase (NSE) and carcinoembryonic antigen (CEA). NSE and CEA are two serum proteins whose elevated levels have been associated with lung cancer. Hence, in this study, impedimetric biosensors (immunosensors) able to quantify NSE and CEA were developed as proof-of-concept devices for lung cancer diagnosis. The sensing platform exploited for the immunosensors comprises a novel combination of a magnetic platform, screen-printed gold electrode (SPGE), and magnetic nanobeads (MB). The MB were functionalized with antibodies to capture the analyte from the sample and to move it over the sensing area. The immunosensors were then developed by immobilizing another set of antibodies for either CEA or NSE on the SPGE through formation of self-assembled monolayer (SAM). The second set of antibodies enabled a sandwich assay to be formed on the surface of the sensor, while MB manipulation was applied during the sensor performance to depict a microfluidic system and increase antigen–antibody complex formation prior to CEA or NSE detection and quantification. The optimized immunosensors were successfully tested to measure various concentrations of CEA and NSE (0–100 ng/mL) in both phosphate buffer and 100% human serum samples. Clinically relevant detection limits of 0.26 ng/mL and 0.18 ng/mL in buffer and 0.76 ng/mL and 0.52 ng/mL in 100% serum for CEA and NSE, respectively, were achieved via electrochemical impedance spectroscopy with the use of potassium ferri/ferrocyanide as a redox probe. Hence, the two immunosensors demonstrated great potential as tools to be implemented for the early detection of lung cancer.
Open Access
Degradation and fatigue life methods for ceramic matrix composite and nickel superalloy materials in gas turbine combustor liner
(Springer Nature, 2024-12-08) Karadimas, Georgios; Pagone, Emanuele; Georgarakis, Konstantinos; Salonitis, Konstantinos
This paper investigates the durability of Ceramic Matrix Composite (CMC) and Nickel Superalloy materials in gas turbine combustor liners across different flight conditions. Thermo-mechanical and physical properties of CMCs are assessed and compared with selected superalloys (i.e., Inconel 625, Hastelloy X, SiC/SiC, Al2O3/B4C, and Al2O3/SiO2) using Finite Element Analysis (FEA). An integrated methodology employing Computational Fluid Dynamics (CFD) and FEA is introduced to analyze thermal stresses and fatigue life, establishing a direct connection between combustion dynamics and structural responses. The study addresses a research gap by thoroughly evaluating CMC materials in gas turbine combustor liners, offering valuable insights for material selection and design strategies in aerospace engineering. The findings enhance understanding of CMC behavior, showcasing their reliability and durability for gas turbine components and their usage for advancements in aerospace applications.
Open Access
Cooperative tracking strategies for optical space-to-space surveillance constellations
(International Astronautical Federation (IAF), 2024-10-18) D'Anniballe, Antonio; Felicetti, Leonard; Hobbs, Stephen
Most space surveillance and tracking systems are constituted by networks of ground stations of observing radars and optical telescopes. These systems are usually reliable, easily serviceable, and effective under ideal conditions, but suffer from strong bounds on scalability and coverage due to the heavy constraints on their geographic locations, potential cloud coverage and the perturbing effect of the atmosphere. A large constellation of small satellites carrying optical telescopes could complement these limitations, thanks to the lack of such constraints and the possibility of observing target objects at close range. As a result, it would be theoretically possible to track objects more accurately and for longer times, improving the accuracy of collision risk analysis and manoeuvre detection amid other tasks. However, due to the small fields of view of suitable onboard optical sensors, a random static arrangement of their lines of sight would be largely inefficient in reaching good performance levels, as the target would unpredictably enter and exit the observable portion of the sky. To solve this problem, we propose a cooperative intelligent tracking strategy for the constellation. Assuming known initial states for some targets, we use predictions on the future states to dynamically control the attitudes of the constellation satellites to maximise the length of the tracking window while minimising energy expenditures. We evaluate the performance of the strategy using quality figures such as the number of effectively trackable targets and the mean square error of the estimation error during tracking. We repeat the analysis for various constellation geometries and multiple target orbits to investigate the general applicability of such a strategy. In conclusion, we check for robustness by analysing performance drops under the loss of operating nodes. The results thus obtained will inform on the usefulness of space-to-space SST constellations and the general design of strategies for the dynamic scheduling of operations of distributed systems observing multiple targets.
Open Access
A causal learning approach to in-orbit inertial parameter estimation for multi-payload deployers
(International Astronautical Federation (IAF), 2024-10-18) Platanitis, Konstantinos; Arana-Catania, Miguel; Upadhyay, Saurabh; Felicetti, Leonard
This paper discusses an approach to inertial parameter estimation for the case of cargo carrying spacecraft that is based on causal learning, i.e. learning from the responses of the spacecraft, under actuation. Different spacecraft configurations (inertial parameter sets) are simulated under different actuation profiles, in order to produce an optimised time-series clustering classifier that can be used to distinguish between them. The actuation is comprised of finite sequences of constant inputs that are applied in order, based on typical actuators available. By learning from the system’s responses across multiple input sequences, and then applying measures of time-series similarity and F1-score, an optimal actuation sequence can be chosen either for one specific system configuration or for the overall set of possible configurations. This allows for both estimation of the inertial parameter set without any prior knowledge of state, as well as validation of transitions between different configurations after a deployment event. The optimisation of the actuation sequence is handled by a reinforcement learning model that uses the proximal policy optimisation (PPO) algorithm, by repeatedly trying different sequences and evaluating the impact on classifier performance according to a multi-objective metric.
Open Access
A collaborative robotic system for entering and mapping Martian caves
(International Astronautical Federation (IAF), 2024-10-18) Devaguptapu, Venkata; Elsayed, Abdulla; Ferreyra, Marie; Guichandut, Thibault; James, Ajina; Laguelle, Aurore; Maniraj, Krishna Priya; Mouchot, Axel; Nair, Aditi; Palange, Mihir; Shufflebotham, Alex; Felicetti, Leonard; Upadhyay, Saurabh; Weclewski, Piotr
Martian caves represent prime locations for investigating evidence of extinct or extant life. In this paper, we propose a technology demonstration mission for Martian cave exploration using a heterogeneous robotic system. Heterogeneous systems are advantageous for Martian cave exploration due to their specialisation for specific tasks, flexibility, and adaptability to diverse conditions. Our mission focuses on the exploration of type 1 atypical pit crater caves in the Elysium Mons region due to their scientific value regarding the potential existence of life and ice water deposits. These caves, situated near the equator, offer low elevation and reduced radiation effects, ensuring safer landing conditions and high scientific outputs. Our mission considers the design of a robotic system capable of entering and mapping the cave environment under five work packages (System, Mission, Payload, Electrical and Mechanical). A risk analysis, concept of operations and budget were established to make sure the requirements and objectives of the mission were fulfilled. To accomplish this mission, we have traded-off different rover locomotion concepts and selected a heterogeneous robotic system comprising a wheeled rover and a multi-rotor aerial robot in a parent-child configuration. The mission is defined in multiple phases starting with the traversal of the wheeled rover and the aerial robot from the landing site to the selected cave. Once at the cave entrance, the rover scans the circumference, and the aerial robot goes into the cave through the entrance to map it. The aerial robot will use a Simultaneous Localisation and Mapping (SLAM) algorithm along with a LIDAR to map and navigate the cave’s interior. The wheeled rover (parent ship), powered by solar arrays, serves as a communication and recharging station at the cave entrance. Using a docking station, it will enable the aerial robot to recharge and communicate with Earth. The cave entry and mapping are demonstrated with a simulation to test the viability of the proposed approach. The proposed autonomy of the heterogeneous robotic system is demonstrated using simulation results in MATLAB Simulink.
Open Access
Implementation of a federated laboratories network for testing formation flying technologies
(International Astronautical Federation (IAF), 2024-10-18) Sabatini, Marco; Felicetti, Leonard; Shufflebotham, Alex; Leslie, Cameron; Upadhyay, Saurabh; Platanitis, Konstantinos; Laufer, Rene; Persson, Olle; Rao Ramavaram, Harish
Formations of microsatellites are a highly attractive solution for achieving responsive space missions focused on Earth observation and communication support, due to their low cost and mass. However, operating these formations is challenging and requires extensive testing, which can be difficult to carry out due to the need for multiple platforms and large testing spaces. This paper presents the first concept and the first steps of a research program funded by NATO in the framework of the Science for Peace and Security program, with the specific purpose to develop and evaluate the necessary infrastructure for establishing a virtual, multi-platform distributed laboratory network comprised of laboratories from Sapienza, Lulea and Cranfield Universties. The value of this network will be increased by sharing resources, equipment, and expertise among the participating laboratories.
Open Access
Guided by principles or rules: a Delphi study on how safety professionals frame safety practices
(Elsevier, 2025-04-01) Pilbeam, Colin; Denyer, David; Sutliff, Mike
This study explores how safety professionals conceptualize and articulate safety practices, examining how their framing influences actions, facilitates learning from failures, and impacts overall safety outcomes. Twenty-nine safety professionals participated in a Delphi study, which included three online workshops and three rounds of surveys. Eighteen safety practices were developed, framed as both rules-based and principles-based practices. Survey results indicated that both rules-based and principles-based practices were considered essential for achieving safety, with their relative balance likely being context-dependent. While all practices were considered important for preventing accidents, those framed as principles were seen as more challenging to implement but ultimately more effective, especially in complex situations. Better understanding of the way in which safety practices are framed has significant implications for the development of safety standards, guidelines, and recommendations.
Open Access
On the conditions for absolute minimum fuel burn for turbofan powered, civil transport aircraft and a simple model for wave drag
(Cambridge University Press (CUP), 2024-06-01) Poll, D. I. A.; Schumann, Ulrich
In a recent series of papers, Poll and Schumann have been developing a simple model for estimating fuel burn for turbofan powered, civil transport aircraft for a given mass, Mach number and flight level and in a specified ambient temperature profile for all phases of flight. This paper focuses upon the combination of Mach number and flight level at which an aircraft cruises with the absolute minimum fuel burn. For a given aircraft type, the information necessary to determine these conditions must be specified and this poses a challenge. An initial attempt to obtain these data has been described previously by the first author. In this paper, the optimum conditions are found using a completely different approach. Starting from first principles and using established theory, the equations governing the situation where engine overall efficiency and airframe lift-to-drag ratio both have local maxima at the same flight condition are developed. This special case is termed the “design optimum” condition and, for a specified aircraft mass and a specified atmospheric temperature versus pressure profile, it gives the lowest possible fuel burn for any aircraft and engine combination. The design optimum occurs at a particular Mach number and Reynolds number, and it is a fixed characteristic of the aircraft. The analysis reveals the significance of Reynolds number variations, wave drag, including its derivatives with respect to both lift coefficient and Mach number, and the atmospheric properties. Whilst wave drag is notoriously difficult to determine accurately, it is found that solutions to the equations are not particularly sensitive to the accuracy of this quantity. Consequently, a simple, physically realistic model can give good results. An appropriate model is developed and a complete, approximate solution is obtained. Taking the International Standard Atmosphere as the design atmosphere, results are presented for the 53 aircraft types previously considered by Poll and Schumann. Relative to the design optimum conditions, when Reynolds number is constant and wave drag is zero, compressibility alone reduces L/D by about 5%, reduces lift coefficient by about 1.5% and increases drag coefficient by about 3.5%. Reynolds number variation has little effect upon L/D, but it reduces lift coefficient and drag coefficient by a further 7% and 8% respectively. The reduction in lift coefficient has a significant impact on the optimum cruise flight level. In general, an aircraft’s operating optimum will not coincide with its design optimum, but deviations are expected to be small. Therefore, using the design optimum solution as a reference point, an improved version of the operating optimum estimation method described by Poll and Schumann in previous work is developed. This allows the estimation of the conditions for absolute minimum fuel burn for an aircraft of given mass flying thorough any atmosphere. Updated coefficients for the 53 aircraft types are given.
Open Access
Structural sizing and mass estimation of transport aircraft wings with distributed, hydrogen, and electric propulsions
(Cambridge University Press (CUP), 2024) Taflan, Murat; Smith, Howard; Loughlan, Joseph
Current literature offers limited mass estimation methodologies and their application in the conceptual or preliminary design stages of moderate to high aspect ratio wings with electric, hydrogen or distributed propulsions. This study presents the development and application of a quasi-analytical wing mass estimation method to address this limitation. The proposed method is distinguished from the existing mass estimation methods by its expanded realistic load cases, sensitivity to several design parameters, improved accuracy with short computational time and capabilities for future applications. To achieve these features, new geometric models are introduced; 483 load cases including symmetric manoeuvre, rolling, and combined cases are covered following airworthiness requirements; the structural elements are idealised and sized with strength and buckling criteria; existing methods are evaluated and integrated cautiously for secondary structures and non-optimum masses. A computation time of 0.1s is accomplished for one load case. The developed method achieved the highest accuracy with an average error of -2.2% and a standard error of 1.8% for wing mass estimates compared with six existing methods, benchmarked against thirteen wings of different aircraft categories. The effects of engine numbers with dual- to 16-engine setups and the dry wing concepts on the wing mass are investigated. The optimised number of engines and their locations decreased the wing mass of the high aspect ratio wing significantly. In contrast, the dry wing design increased the wing masses of all baseline aircraft. The future applications and improvements of the presented method in novel configurations and multidisciplinary designed optimisation studies are explained.
Open Access
Take-off performance of a single engine battery-electric aeroplane
(Cambridge University Press (CUP), 2024-12-01) Gratton, Guy; Delaney, Thomas; Zaghari, Bahareh; Kendall, Gary
This paper investigates the take-off performance of a single engine battery-electric aeroplane, using the example of the 300kg Sherwood eKub. It shows analysis of take-off performance of such an aeroplane must include as a minimum two new parameters not normally considered: time at full throttle and state of charge. It was shown in both ground and flight test that the state of available power reduces both as the throttle is fully open, and as battery charge is consumed, although recovers partially when power is reduced for a period. It is possible to schedule take-off performance as a function of the usual parameters plus state of charge. Because of the reducing climb performance with use of state of charge, and the requirement in airworthiness standards for minimum climb performance being available, it becomes necessary to introduce the concept of minimum-indicated state of charge for take-off, SoCiMTO; means to calculate that are shown for compliance with both microlight aeroplane standards and larger aeroplane standards, and the calculations are demonstrated for the eKub. Conclusions are also drawn about the use of commercial products SkyDemon and Google Earth for recording and analysing aeroplane performance data.
Open Access
Simulation framework and development of the Future Systems Simulator
(Cambridge University Press (CUP), 2024-12-01) Korek, Wojciech T.; Beecroft, P.; Lone, Mudassir; Bragado Aldana, Estela; Mendez, Arthur; Enconniere, J.; Asad, Hafiz ul; Grzedzinski, Kacper; Milidere, Murat; Whidborne, James F.; Li, Wen-Chin; Lu, Linghai; Alam, Mushfiqul; Asmayawati, Saryani; Del Barrio Conde, L.; Hargreaves, D.; Jenkins, D.
The Aerospace Integration Research Centre (AIRC) at Cranfield University offers industry and academia an open environment to explore the opportunities for efficient integration of aircraft systems. As a part of the centre, Cranfield University, Rolls-Royce, and DCA Design International jointly have developed the Future Systems Simulator (FSS) for the purpose of research and development in areas such as human factors in aviation, single-pilot operations, future cockpit design, aircraft electrification, and alternative control approaches. Utilising the state-of-the-art modularity principles in simulation technology, the FSS is built to simulate a diverse range of current and novel aircraft, enabling researchers and industry partners to conduct experiments rapidly and efficiently. Central to the requirement, a unique, user-experience-centred development and design process is implemented for the development of the FSS. This paper presents the development process of such a flight simulator with an innovative flight deck. Furthermore, the paper demonstrates the FSS’s capabilities through case studies. The cutting-edge versatility and flexibility of the FSS are demonstrated through the diverse example research case studies. In the final section, the authors provide guidance for the development of an engineering flight simulator based on lessons learned in this project.
Open Access
Development of a virtual environment for rapid generation of synthetic training images for artificial intelligence object recognition
(MDPI, 2024-12-01) Wang, Chenyu; Tinsley, Lawrence; Honarvar Shakibaei Asli, Barmak
In the field of machine learning and computer vision, the lack of annotated datasets is a major challenge for model development and accuracy improvement. Synthetic data generation addresses this issue by providing large, diverse, and accurately annotated datasets, thereby enhancing model training and validation. This study presents a Unity-based virtual environment that utilises the Unity Perception package to generate high-quality datasets. First, high-precision 3D (Three-Dimensional) models are created using a 3D structured light scanner, with textures processed to remove specular reflections. These models are then imported into Unity to generate diverse and accurately annotated synthetic datasets. The experimental results indicate that object recognition models trained with synthetic data achieve a high rate of performance on real images, validating the effectiveness of synthetic data in improving model generalisation and application performance. Monocular distance measurement verification shows that the synthetic data closely matches real-world physical scales, confirming its visual realism and physical accuracy.
Open Access
Optimized AI methods for rapid crack detection in microscopy images
(MDPI, 2024-12-06) Lou, Chenxukun; Tinsley, Lawrence; Duarte Martinez, Fabian; Gray, Simon; Honarvar Shakibaei Asli, Barmak
Detecting structural cracks is critical for quality control and maintenance of industrial materials, ensuring their safety and extending service life. This study enhances the automation and accuracy of crack detection in microscopic images using advanced image processing and deep learning techniques, particularly the YOLOv8 model. A comprehensive review of relevant literature was carried out to compare traditional image-processing methods with modern machine-learning approaches. The YOLOv8 model was optimized by incorporating the Wise Intersection over Union (WIoU) loss function and the bidirectional feature pyramid network (BiFPN) technique, achieving precise detection results with mean average precision (mAP@0.5) of 0.895 and a precision rate of 0.859, demonstrating its superiority in detecting fine cracks even in complex and noisy backgrounds. Experimental findings confirmed the model’s high accuracy in identifying cracks, even under challenging conditions. Despite these advancements, detecting very small or overlapping cracks in complex backgrounds remains challenging. Our future work will focus on optimizing and extending the model’s generalisation capabilities. The findings of this study provide a solid foundation for automatic and rapid crack detection in industrial applications and indicate potential for broader applications across various fields.
Open Access
On the composition gradient of steel/Invar functionally graded material manufactured by wire-based direct energy deposition
(Elsevier, 2024-09-25) Wang, Jun; Biswal, Romali; Chen, Guangyu; Pardal, Goncalo Rodrigues; Lu, Yao; Ding, Jialuo; Williams, Stewart
This study utilized double-wire plasma arc direct energy deposition to produce functionally graded materials (FGMs) with two transition designs, abrupt (AT) and gradual (GT), from Er90s steel to Invar. The study systematically compared the transition in chemical composition, microstructure, phase evolution, thermal stress, and mechanical performance. Both FGM types exhibited a band structure in the Er90s section and coarse columnar grains in the Invar section, with the AT deposit showing a 1 mm thick, defect-free interface and the GT deposit having an 18 mm thick transition region with distinct boundaries. It revealed diverse microstructures across the transition zones, including fine ferrite, martensite with minor retained austenite (RA), coarse columnar austenite with martensite dendrites, and single FCC austenite. The GT sample uniquely featured a microstructure of martensite laths inside prior austenite decorated by RA semicontinuous network, with a crack detected due to dilatational stresses from martensite transformation. Hardness was similar in both FGM types, with higher values at the interfaces, especially in the GT FGM. The GT FGM demonstrated higher strength but lower ductility compared to the AT FGM, with failure occurring in the Invar portion for both. Thermal stress modelling indicated smoother stress transitions in the GT sample but no significant performance differences between Er90s and Invar. This study showcases the effectiveness of double-wire plasma arc DED in producing steel/Invar FGMs with varying composition gradients. It also underscores the importance of selecting the right mixing ratio for Er90s/Invar FGM deposits to avoid cracking and deterioration of properties in the gradient area.
Open Access
Development and characterisation of integrated wet-spun alginate-Moringa oleifera composite fibers for potential water purification
(Elsevier, 2025-03) Orisawayi, Abimbola Oluwatayo; Koziol, Krzysztof; Rahatekar, Sameer S
Ensuring access to safe drinking water requires effective materials and technologies to treat contaminated water. In this study, we developed sodium alginate fibre (SAlgF) and their composite fibres functionalised with pulverised Moringa oleifera (MoP) at concentrations of 0.5 %, 1 %, 4 %, and 8 % using the wet-spinning technique. Both SAlgF and MoP are biodegradable, offering eco-friendly alternatives to synthetic polymers in line with green manufacturing. The results showed significant improvements in the mechanical properties, with the 1 % MoP composite fibre exhibiting 6 times the strength of pure SAlgF in terms of ultimate tensile strength (UTS) and Young's modulus (YM). X-ray Diffraction (XRD) analysis revealed enhanced fibres interactions, while Fourier Transform Infrared Spectroscopy (FTIR) and Thermogravimetric Analysis (TGA) confirmed the successful incorporation of MoP into the alginate matrix and improved thermal stability. Furthermore, the result obtained from the Scanning Electron Microscopy-Energy Dispersive X-ray Spectroscopy (SEM-EDX) indicated morphological changes and the uptake of heavy metal ions when immersed into solutions containing Cu²⁺, Ni²⁺, and Cd²⁺. These findings demonstrate the potential of MoP-modified composite fibres for sustainable and cost-effective water treatment applications, particularly in developing countries.
Open Access
A COLREGs compliance reinforcement learning approach for USV manoeuvring in track-following and collision avoidance problems
(Elsevier, 2025-01-15) Sonntag, Valentin; Perrusquía, Adolfo; Tsourdos, Antonios; Guo, Weisi
The development of new technologies for autonomous platforms has allowed their integration into sea mine countermeasures. This has allowed to remove the personnel from the potential danger by having the mine search task performed by an unmanned surface vessel (USV). Traditional intelligent systems are built by agglomerating hand-coded behaviours that determine how a good manoeuvre looks like. This induces cognitive bias into the pre-defined behaviours that can violate safety and regulatory rules imposed by the COLREGs. To alleviate this issue, this paper proposes a COLREGs compliant reinforcement learning (RL) approach that gives a solution for the autonomous navigation of USVs. A custom simulation environment is developed. The RL agents are trained to deal with path-following problem with obstacle avoidance capabilities. A custom reward function is defined to consider the turning disks for the agent's decision process. A smoothing decision feature is used to smooth the transitions between consecutive actions. The results demonstrate good convergence and high performance under different scenarios. The collision avoidance with COLREGs compliances shows the effectiveness of the proposed approach under several scenarios with static and moving obstacles.
Open Access
Achieving on-site trustworthy AI implementation in the construction industry: a framework across the AI lifecycle
(MDPI AG, 2024-12-25) Yang, Lichao; Allen, Gavin; Zhang, Zichao; Zhao, Yifan
In recent years, the application of artificial intelligence (AI) technology in the construction industry has rapidly emerged, particularly in areas such as site monitoring and project management. This technology has demonstrated its great potential in enhancing safety and productivity in construction. However, concerns regarding the technical maturity and reliability, safety, and privacy implications have led to a lack of trust in AI among stakeholders and end users in the construction industry, which slows the intelligent transformation of the industry, particularly for on-site AI implementation. This paper reviews frameworks for AI system design across various sectors and government regulations and requirements for achieving trustworthy and responsible AI. The principles for the AI system design are then determined. Furthermore, a lifecycle design framework specifically tailored for AI systems deployed in the construction industry is proposed. This framework addresses six key phases, including planning, data collection, algorithm development, deployment, maintenance, and archiving, and clarifies the design principles and development priorities needed for each phase to enhance AI system trustworthiness and acceptance. This framework provides design guidance for the implementation of AI in the construction industry, particularly for on-site applications, aiming to facilitate the intelligent transformation of the construction industry.