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The challenges and potential for increasing the recycling of post-consumer aluminium scrap in the UK
No full textWith the emphasis on circular economy and sustainable development, the demand for the reuse of post-consumer aluminium (Al) scrap is rising. Current recycling processes, such as downgrading and dilution, can lead to the accumulation of contaminants in the resulting alloy and a surplus of non-recyclable scrap. This is not viable for sustainable development of the manufacturing industry, and optimised recycling strategies and systems are required. The existing literature is relatively scattered and lacks a unified integration of related fields. This paper is trying to mitigate the gap by a cohesive synthesis across interconnected domains. It aims to analyse the potential problems and barriers to the upgrading of the aluminium scrap recycling industry in the United Kingdom(UK) and explore feasible solutions from different perspectives. This article reviews the latest literature while also collecting recent information from the industry to analyse the overall development bottlenecks of aluminium recycling and reuse development. These obstacles include a dearth of available data, the complexity of diverse alloy types, mismatches between market supply and demand, and associated recycling costs. It points out potentially effective actions through use cases and provides a framework for improving strategies and future work.Proceedings of the 11th International Conference on Sustainable Design and Manufacturing (KES-SDM 2024)Smart Innovation, Systems and Technologie
On the unsteady behaviour of a liquid hydrogen fuel system pump for aircraft engine applications
Get PDFThe unsteady behaviour of a 2-stage liquid hydrogen (LH2) fuel system pump for future aircraft engine applications is investigated herein by means of full wheel, uRANS simulations. Compressibility, thermodynamic state and leakage flow effects are investigated to assess their individual contribution in the stability and unsteady pump operation. This is achieved by comparing three pump configurations along with two different modelling approaches: a baseline geometry without cavities, one with shroud cavities only, and a full model comprising all cavities, while real gas and constant propertyfluids are used to assess compressibility effects. An initial performance and component stability analysis is carried out using steady-state simulations and standard non-dimensional quantities. Unsteady simulations are subsequently performed combining the different modelling approaches and geometries at very low, off-design flow rates, representative of part-load operation. Unsteady signals are recorded at several planes in the pump flow path along with multiple monitor points around the annulus. These are then analysed in the frequency domain, providing a link between key flow features and the high-power frequency content. Compressibility effects are shown to slightly penalise the head rise of the pump without however penalising stability. The implications of the thermodynamic state of hydrogen on the transient pump response are minor, while the recorded head fluctuation amplitude of the baseline configuration reaches 18.4% of the mean value. Both impellers of the baseline configuration exhibit a mild surge-type of behaviour associated with stalled flow-induced blockage near the volute tongue resulting in heavy stalling of the splitter blades. Leakage flows negatively affect the steady-state pump performance but alleviate full and splitter blade stall, reducing the pump’s oscillation intensity by 30.6% through partial suppression of the stalled flow near the volute tongue. The study highlights the importance of transient performance in low-specific-speed hydrogen fuel pumps, as part-load operation may entail significant operability challenges.The authors would like to thank ATI/iUK for funding this work through UKRI, project LH2GT, with Reference No. 10039770 and Rolls-Royce plc.ASME Turbo Expo 2025: Turbomachinery Technical Conference and Expositio
A sub-hourly precipitation dataset from a pluviographic network in central Chile
Get PDFThis data descriptor presents a unique high-resolution rainfall dataset derived from 14 pluviograph stations across central Chile’s Mediterranean region, covering variable periods starting from between 1969 and 1992, up to 2009. The dataset provides continuous precipitation records at a 5 min temporal resolution, obtained through the digitization and processing of pluviograph strip charts using specialized software. This high temporal resolution is unprecedented for the region and enables detailed analysis of rainfall intensity, duration, and frequency patterns critical for hydrological research, climate studies, and water resource management in general. Each station’s data was subjected to quality control procedures, including manual validation and correction of digitization errors to ensure data integrity. The dataset reveals the significant temporal variability of rainfall in central Chile, capturing both short-duration high-intensity events and longer precipitation patterns. By making this dataset publicly available, we provide researchers with a valuable resource for studying rainfall behavior in a Mediterranean climate zone subject to significant climate variability and change. The dataset supports various applications, including the development of intensity–duration–frequency curves, analysis of rainfall erosivity, calibration of hydrological models, and investigation of precipitation trends in the context of climate change.The authors gratefully acknowledge the support provided by the ANID BASAL Center FB210015 (CENAMAD) and by ANID FONDECYT Regular grant 1251441.Dat
An end-to-end computationally lightweight vision-based grasping system for grocery items
No full textVision-based grasping for mobile manipulators poses significant challenges in machine perception, computational efficiency, and real-world deployment. This study presents a computationally lightweight, end-to-end grasp detection framework that integrates object detection, object pose estimation, and grasp point prediction for a mobile manipulator equipped with a parallel gripper. A transformation model is developed to map coordinates from the image frame to the robot frame, enabling accurate manipulation. To evaluate system performance, a benchmark and a dataset tailored to pick-and-pack grocery tasks are introduced. Experimental validation demonstrates an average execution time of under 5 s on an edge device, achieving a 100% success rate on Level 1 and 96% on Level 2 of the benchmark. Additionally, the system achieves an average compute-to-speed ratio of 0.0130, highlighting its energy efficiency. The proposed framework offers a practical, robust, and efficient solution for lightweight robotic applications in real-world environments.Sensor
Filter-based Tchebichef moment analysis for whole slide image reconstruction
No full textThis article belongs to the Special Issue Image Fusion and Image ProcessingIn digital pathology, accurate diagnosis and prognosis critically depend on robust feature representation of Whole Slide Images (WSIs). While deep learning offers powerful solutions, its “black box” nature presents significant challenges to clinical interpretability and widespread adoption. Handcrafted features offer interpretability, yet orthogonal moments, particularly Tchebichef moments (TMs), remain underexplored for WSI analysis. This study introduces TMs as interpretable, efficient, and scalable handcrafted descriptors for WSIs, alongside a novel two-dimensional digital filter architecture designed to enhance numerical stability and hardware compatibility during TM computation. We conducted a comprehensive reconstruction analysis using H&E-stained WSIs from the MIDOG++ dataset to evaluate TM effectiveness. Our results demonstrate that lower-order TMs accurately reconstruct both square and rectangular WSI patches, with performance stabilising beyond a threshold moment order, confirmed by SNIRE, SSIM, and BRISQUE metrics, highlighting their capacity to retain structural fidelity. Furthermore, our analysis reveals significant computational efficiency gains through the use of pre-computed polynomials. These findings establish TMs as highly promising, interpretable, and scalable feature descriptors, offering a robust alternative for computational pathology applications that prioritise both accuracy and transparency.Electronic
Constituents, morphological and thermal stability characteristics of wood ash and wood charcoal microparticles for composites application
Get PDFThis research investigates the physicochemical properties of wood ash and wood charcoal, two by-products derived from the pyrolysis of wood, focusing on their potential applications as sustainable reinforcement materials in composite manufacturing. Through a systematic characterisation process, we analysed both materials' chemical composition, thermal stability, crystallographic structure, and surface morphology. The findings reveal that wood ash is rich in calcium and magnesium oxides, which enhance its mechanical properties and reactivity, making it an effective additive in composite formulations. Moreover, wood charcoal exhibits a high carbon content and specific surface area, contributing to its thermal stability and adsorptive capabilities. The porous nature of wood ash and the unique structural characteristics of wood charcoal position them as promising candidates for various industrial applications, including construction, environmental remediation, and energy storage. This research underscores the importance of utilizing renewable biomass by-products, highlighting their role in advancing sustainable material practices and promoting environmental stewardship.Next Material
Guest editorial: digitizing food supply chains: a path to ensuring food security
Get PDFInternational Journal of Industrial Engineering and Operations Managemen
Final Report to DEFRA. Project Code: AF0105.
Get PDFSilvoarable agroforestry (the intercropping of trees and arable crops) can diversify farm incomes, increasing tree planting and improve farm biodiversity. In 1992 a silvoarable experiment, comprising three replicate blocks of four poplar (Populus spp.) hybrids (at a spacing of 10 m x 6.4 m) and three arable treatments, was established by Cranfield University in Bedfordshire, Leeds University in West Yorkshire, and the Royal Agricultural University in Gloucestershire. The attached report describes the results from the experiment for the four-year period from April 1999 to April 2003. It covers the effects on tree growth, crop yields, economics, understorey vegetation, and the number and diversity of ground invertebrates.DEFR
Adaptive intelligent traffic control systems in smart city
Get PDFTraffic congestion in urban areas presents a significant challenge with far-reaching impacts on the
economy, environment, and overall quality of life. To address this challenge, this thesis proposes
a novel approach to traffic signal control aimed at alleviating traffic congestion more effectively.
The research problem this study explores is the design and implementation of an adaptive system
for traffic signal control in urban road networks, specifically focused on how to effectively manage
traffic signal timings to mitigate congestion. The major contributions of this study include the
development of a unique coordination algorithm for adaptive traffic signal control, utilizing Multi-
Agent Reinforcement Learning (MARL) and Ant Colony Optimization (ACO). This algorithm's
uniqueness is reflected in its capacity to simulate the behavior of ant colonies to guide multiple
agents in managing traffic signals at various intersections, enabling them to learn from their
environment and interactions to optimize signal timings By simulating the behavior of ant
colonies, the algorithm guides multiple agents in managing traffic signals at various network
intersections, learning from their interactions with the environment and each other to optimize
signal timings. This research sets out to address the challenge of traffic congestion in urban areas.
With cities worldwide struggling with this issue, the task of managing traffic signal timings to
reduce congestion is paramount. The problem formulation involved the exploration of how novel
Machine Learning (ML) techniques, such as Multi-Agent Reinforcement Learning (MARL) and
Ant Colony Optimization (ACO), could be utilized to develop an adaptive coordination algorithm
for traffic signal control. These techniques were chosen due to their potential for learning and
adapting over time to optimize signal timings based on ever-changing traffic conditions. The
novelty of this research lies in the unique combination of MARL, Actor-Critic (AC), and ACO
techniques to develop an adaptive coordination algorithm for traffic signal control. By integrating
these techniques, we've created a system where multiple agents can independently control traffic
signals at different intersections, learning from their surroundings and interactions to continually
improve signal timings. This innovative use of ML, especially MARL and ACO, represents a
significant contribution to the field of traffic management, as it offers the potential to adapt to
changing traffic patterns and conditions in real-time. This adaptability is expected to lead to more
efficient traffic flow and decreased congestion, outcomes not fully realized by existing fixed-time
and traditional adaptive signal control methods.PhD in Aerospac
Investigation of ash and combustion characteristics during co-combustion of coal and solid recovered fuel in a laboratory-scale combustor
Get PDFPopulation growth and limited landfill area increase the problems associated with municipal solid waste (MSW). The MSW conversion into solid recovered fuel (SRF) improves the calorific value which has the potential to be used as a power plant boiler fuel. This study investigates ash deposition and combustion characteristics during co-combustion of coal and SRF at various dosages (5, 10, 15, 20, and 25 wt%). Thermogravimetry analysis, preliminary risk assessment, and morphology analysis of ash deposits are comprehensively performed. The study reveals that based on combustion performance, SRF blends up to 20 wt% show slightly altered burnout temperatures compared to coal combustion, whereas, at 25 wt%, the combustion temperature increases significantly. On the initial risk assessment, the samples tested have a low to medium risk of slagging. Morphological observations show that fine, irregular, and unmelted particles dominate coal ash deposits, while SRF ash deposits are dominated by melted and agglomerated particles. The melted particles gradually increase as the dosage of SRF in the mixture increases. Low melting temperature element-rich particles start to be observed at doses higher than 10 wt%. At 25 wt% SRF blends, material degradation is observed with the presence of Cr in the ash deposit. Overall, co-combustion over 10 wt% SRF shows results that should be considered, particularly the increase in sintering ash that can cause problems in the boiler pipes. This study provides insight into the optimum dosage suitable for blending SRF and coal in power plant boilers.This research was supported financially by the Renewable Energy Program of the Research Organization for Energy and Manufacture, National Research and Innovation Agency.Combustion Science and Technolog