20505 research outputs found
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Dataset: Developing a Techno-economic Framework for National-level End-state Decarbonisation Resource Analysis: a UK Application
No full textAmid growing urgency for net-zero delivery and calls for simplified energy system modelling, this study presents a techno-economic framework, termed“End-state Decarbonisation Resource Analysis” (EDRA), for evaluating national decarbonisation strategies. EDAR integrates demand estimation, technology replacement, generation calculation and economic assessment, and employs scenario modelling and optimisation to estimates the technical, geographical and financial resources required for full national decarbonisation. The framework offers a simplified yet comprehensive approach for national energy system assessment. Applied to the UK, EDRA reveals substantial gaps between current government capacity targets and the requirements of a fully decarbonised system aligned with the UK’s policy goals of net-zero, energy independence and energy security. Meeting these aims would require more than triple the nuclear target, over double the offshore wind target, more than 400 GW of electrolysers, combined cycle hydrogen turbines and electricity grid, ~50thousand km2 of land for wind and solar, and trillion-pound scale investment. Delivering this scale of re-source deployment within 25 years presents a significant policy challenge. Nevertheless, the results demonstrate clear advantages of a decarbonised electrification system over fossil fuel-based alternatives. A key policy recommendation is to prioritise demand reduction to ease generation resource pressure.Cranfield Universit
Dataset: Greening’ the UK: A Comparative Study of Heat Pumps and Hydrogen Boilers in Residential Heating
No full textWith a key policy decision on the role of hydrogen boilers expected by 2026, the UK is at a strategic crossroads in implementing its Heat and Buildings Strategy. This study evaluates the relative advantages of hydrogen boilers and heat pumps in residential heating, focusing on their impact on national energy demand, which is a critical factor in achieving full decarbonisation by 2050. Using the End-state Decarbonisation Resource Analysis framework, this study demonstrates that electrification with widespread heat pumps could reduce current residential primary energy demand by over 53%, whereas a hydrogen boiler-dominant pathway could increase demand by 42%. When translated into generation and infrastructure requirements, the hydrogen pathway would demand significantly more resources than the heat pump alternative. Incorporating heat pumps into the electrification strategy would make the delivery of net-zero targets more achievable. Notably, heat pumps could deliver nearly six times higher economic benefits than hydrogen, while requiring only 67% of investment needed for additional generation assets. These findings support prioritising heat pumps over hydrogen boilers in the UK’s national residential decarbonisation strategy.Cranfield Universit
Deep learning-based rapid identification of Escherichia coli and Klebsiella pneumoniae from chromogenic agar urine cultures using YOLOv12
No full textPurpose: Urinary tract infections (UTIs) are among the most common bacterial infections worldwide, with Escherichia coli and Klebsiella pneumoniae being the predominant pathogens. Diagnostic delays necessitate the use of broad-spectrum antibiotics, which fuels antimicrobial resistance. This study aimed to develop and validate an artificial intelligence (AI) model for the rapid identification of E. coli and K. pneumoniae colonies from urine culture images. Patients and Methods: We analyzed 1547 chromogenic agar urine culture images (850 E. coli, 697 K. pneumoniae) obtained using an automated Copan WASP system. A YOLOv12 deep learning model was trained on expert-labeled colonies. The reference standard comprised MALDI-TOF Mass Spectrometry (MS) for K. pneumoniae and a characteristic chromogenic morphology for E. coli. This phenotypic method is standard in clinical practice, with validation studies for the specific agar used reporting a sensitivity of 98.1–99.0% and a specificity of 99.1% for E. coli identification. Performance was assessed on an internal test set and via external validation using 91 independent images. Results: The model achieved 99% accuracy (precision, recall, F1-score: 0.99) on internal testing. External validation yielded 100% accuracy, with the critical note that species labels in this independent set were inferred from colony colour. Rare errors involved atypical (eg, gold-pigmented) E. coli colonies. YOLOv12 outperformed five benchmark deep learning models. Conclusion: This AI model enables rapid (sub-second), accurate phenotypic classification of the most common UTI pathogens directly from routine culture plates. Integration into automated systems could reduce the diagnostic timeline by approximately 18 hours, facilitating earlier targeted therapy and supporting antimicrobial stewardship. A key consideration for implementation is the model’s basis in phenotypic identification, which aligns with standard laboratory workflow but requires awareness of rare chromogenic variants. The reliance on chromogenic morphology for E. coli ground truth has been a key limitation of the study.Risk Management and Healthcare Polic
Learning what matters now: a dual-critic context-aware RL framework for priority-driven information gain
No full textAutonomous systems operating in high-stakes search-and-rescue (SAR) missions must continuously gather mission-critical information while flexibly adapting to shifting operational priorities. We propose CA-MIQ (Context-Aware Max-Information Q-learning), a lightweight dual-critic reinforcement learning (RL) framework that dynamically adjusts its exploration strategy whenever mission priorities change. CA-MIQ pairs a standard extrinsic critic for task reward with an intrinsic critic that fuses state-novelty, information-location awareness, and real-time priority alignment. A built-in shift detector triggers transient exploration boosts and selective critic resets, allowing the agent to re-focus after a priority revision. In a simulated SAR grid-world, where experiments specifically test adaptation to changes in the priority order of information types the agent is expected to focus on, CA-MIQ achieves nearly four times higher mission-success rates than baselines after a single priority shift and more than three times better performance in multiple-shift scenarios, achieving 100% recovery while baseline methods fail to adapt. These results highlight CA-MIQ’s effectiveness in any discrete environment with piecewise-stationary information-value distributions.This work is funded by EPSRC iCASE with Thales UK (EP/X52475X/1)2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC
The effect of short-term gaseous ozone treatment on physical attributes and senescence-related enzymes of ‘Eureka’ lemons during cold sterilization
No full textDue to restrictions on the use of synthetic fungicides on fresh produce, there is growing interest in residue-free technologies such as ozone (O3), which may enhance fruit defence mechanisms against postharvest disorders. This study examined the effect of gaseous O3 on oxidative stress–related defence enzymes and the physical quality attributes of ‘Eureka’ lemons during cold sterilization. Fruit was exposed to 0.3 mg/L ozone for 24 or 48 h, then stored at 0 °C as the recommended temperature for sterilisation and 95% RH for 28 d, followed by 7 d at ambient temperature. Physicochemical variables, including colour, firmness, lipid peroxidation, catalase (CAT), glutathione reductase (GR), peroxidase (POD) and lipoxygenase (LOX) were assessed bi-weekly. Ozone treatments (48 h and 24 h) exhibited higher decay incidence between day 28 and 35 by 4% and 3.2%, respectively, compared to 0.91% in the untreated fruit. Although the O3 (48 h) treatment showed higher decay (p < 0.001), it had slightly better colour and firmness at the end of the assessment period. Gaseous O3 significantly increased CAT, LOX, POD, and GR (p < 0.001) from 0 to 28 days. A slight decline in CAT and GR was observed during ambient storage, particularly under O3 (48 h). Overall, these results suggest that O3 may exacerbate senescence traits of ‘Eureka’ lemons, and its use may compromise fruit quality and promote decay, particularly during cold sterilization. Considering that CAT and GR were significantly increased, further research should explore the shorter O3 durations and their impact on decay-causing pathogens and senescence-linked enzymes, specifically POD and LOX, to enhance the efficacy and safety of ozone as a postharvest treatment for citrus fruit.This research was financially supported by the National Research Foundation Support for Y-rated Researchers Grant (CSRP: 2205046155).Journal of Agriculture and Food Researc
Conceptual Design of a Hypersonic Vehicle Demonstrator
No full textThe development of airbreathing hypersonic vehicles presents additional technical challenges as the result of various design compromises in disciplines such as aerodynamics, propulsion, systems, and materials, all of which need to be integrated to produce a configuration that is not optimized for a specific speed region but provides enough performance to complete its mission. Given this added complexity to the design process, this paper presents a methodology applicable for conceptual design of airbreathing hypersonic vehicles covering the areas of parametric sizing, propulsion, aerodynamics, weights and balance, and trajectory. This methodology was used to develop the conceptual design of an airbreathing hypersonic vehicle demonstrator capable of cruising at Mach 5 at 80,000 ft with a 3500 nm range and a 10,000 lb payload. For this concept, hydrogen and hydrocarbon fuels were considered as well as two different body types: Wing Body and Blended Body. The effects of these design characteristics were assessed in the development of the propulsion system and the parametric sizing process. The propulsion analysis for the ramjet showed significant advantages of hydrogen over hydrocarbon fuel, as hydrogen presented 62.62% lower fuel consumption as well as 6.69% increase in specific thrust. During parametric sizing, it was found that Blended Bodies were lighter than Wing Bodies using the same fuel, due to having lower wetted surfaces areas and hence lower dry weights. When comparing the effects of fuel type, it was found that even though a hydrogen ramjet would consume less fuel in principle, the effects of its low density (74.6 kg/m3) produced Blended Body vehicle configurations with up to 47.1% heavier MTOW’s, 96% heavier dry weights, and 22.7% more fuel required for the same mission, structural and system characteristics as the Blended Body hydrocarbon vehicle. Based on these results, the chosen configuration was the Blended Body hydrocarbon. Using the values obtained from parametric sizing, the vehicle’s design was defined in the configuration layout phase and was evaluated for aerodynamics, propulsion and trajectory performance, from which it was determined that the vehicle could complete the mission.MSc in Aerospace Vehicle Desig
ESG performance and bank valuation - The influence of the COVID-19 pandemic on the ESG-value relationship
No full textThe thesis examines the relationship between Environmental, Social, and Governance (ESG) performance and banks’ valuation metrics, with a focus on how the COVID-19 pandemic impacted this relationship. The fixed-effects panel regression model, using a sample of 71 publicly listed banks across 29 OECD countries from 2015 to 2023, assesses the impact of overall and individual pillar ESG scores on three valuation and performance metrics. These metrics are the Price-to-Book (P/B) ratio, Return on Assets (ROA), and the Price-to-Earnings (P/E) ratio. The results of the pre-crisis period suggest no statistically significant relationship between ESG performance and valuation. However, COVID-19 had an influence, with results portraying a positive and statistically significant relationship between ESG performance and the P/B ratio and ROA in the post-COVID period. This suggests that investors priced in the resilience impact of strong ESG performance for banks with stronger sustainability during periods of market stress. Further analysis also indicated the ESG effect on valuations was primarily driven by the environmental and governance pillars, with the social pillar remaining statistically insignificant. The results also revealed a non-linear relationship between ESG scores and valuations, with the resilience of the ESG effect being more pronounced for smaller banks. This study contributes to sustainable finance literature, providing evidence for sector-specific relationships between ESG and value in the banking industry. The results provide important considerations for banks, investors, and regulators, since a strong ESG performance is no longer an asset for reputation but a strong indicator for resilience in banks, especially during periods of crisis.MSc in Banking, Economics and Financ
Fatigue Life Enhancement of Metallic Aircraft Structures Using Bonded Crack Retarders - A Finite Element Study with VCCT and Cohesive Surface in ABAQUS
No full textThis research investigates the fatigue life enhancement of aluminium structures through the application of bonded crack retarders, modelled and analysed using the finite element (FE) method in ABAQUS. The study focuses on an aluminium plate specimen with centrally located cracks, reinforced symmetrically on both surfaces by bonded crack retarders, aiming to delay crack propagation and extend structural service life. The FE model incorporates advanced fracture mechanics techniques, including the Virtual Crack Closure Technique (VCCT) and the Cohesive Surface, to accurately simulate crack initiation and growth under cyclic loading. From these simulations, the strain energy release rate (SERR) components are extracted and utilised to compute stress intensity factors (SIFs). These SIF values form the basis for fatigue life prediction, performed through AFGROW simulations. The computational results are rigorously compared against previously conducted experimental data to assess model fidelity and predictive accuracy. The outcomes of this study contribute to the understanding of bonded crack retarder performance and provide a validated numerical framework for fatigue life estimation in aerospace grade aluminium components.MSc in Aerospace Vehicle Desig
Comparative life cycle assessment of WTaTiVCr high-entropy alloy fabricated by mechanical alloying and 3D mixing methods
No full textWTaTiVCr High-Entropy AlloysHigh-entropy alloy (HEAs) are recognized as promising candidates for fusion plasma-facingFusion plasma-facing materials applications. However, the environmental impact of their development and fabrication methods remains insufficiently characterized. This study presents a comparative evaluation of two powder processing routes: mechanical alloying by ball milling and low-shear 3D mixing. Both fabrication methods yield single-phase, Body-Centred Cubic WTaTiVCr HEAs with comparable Vickers hardness and relative densities exceeding 98%. Applying a “cradle-to-gate” (i.e. from raw material production to arc plasma sintering) Life Cycle Assessment method, the carbonCarbon footprint of both routes is estimated to produce the divertor surface of the International Thermonuclear Experimental Reactor. The findings identify the more environmentally friendly route as well as carbonCarbon footprint “hotspots”. Results for the alloy with 30% of tungsten molar content show a carbonCarbon footprint reduction of 48.76 tCO2e, when switching from the ball milling to the 3D mixing manufacturing route. Such difference grows by a further 35% when the tungsten content increases up to 90% molar fraction.Energy Technology 2026The Minerals, Metals & Materials Serie
Developing a techno-economic framework for national-level end-state decarbonisation resource analysis: a UK application
No full textThis article belongs to the Special Issue Energy Transition: Interaction of Gas/Hydrogen and Electricity SystemsAmid growing urgency for net-zero delivery and calls for simplified energy system modelling, this study presents a techno-economic framework, termed “End-state Decarbonisation Resource Analysis” (EDRA), for evaluating national decarbonisation strategies. EDRA integrates demand estimation, technology replacement, generation calculation and economic assessment, and employs scenario modelling and optimisation to estimates the technical, geographical, and financial resources required for full national decarbonisation. The framework offers a simplified yet comprehensive approach for national energy system assessment. Applied to the UK, EDRA reveals substantial gaps between current government capacity targets and the requirements of a fully decarbonised system aligned with the UK’s policy goals of net-zero, energy independence and energy security. Meeting these aims would require more than triple the nuclear target, over double the offshore wind target, more than 400 GW of electrolysers, combined cycle hydrogen turbines and electricity grid, ~50 thousand km2 of land for wind and solar, and trillion-pound scale investment. Delivering this scale of resource deployment within 25 years presents a significant policy challenge. Nevertheless, the results demonstrate clear advantages of a decarbonised electrification system over fossil fuel-based alternatives. A key policy recommendation is to prioritise demand reduction to ease generation resource pressure.This research is funded by a Cranfield University scholarship.Energie