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Destructive testing and failure analysis of a full-scale composite tidal turbine blade
Get PDFTidal stream turbines play a pivotal role in harnessing marine energy, yet their reliability remains a critical challenge, impeding the cost-effectiveness of tidal energy. Deviations in blade performance can significantly impact turbine efficiency, potentially leading to unbalanced loads and consequential damage to the turbine and ad- jacent blades. Experience of blade failure, attributed to factors including material fatigue, manufacturing defects, environmental conditions, and operational stresses, under- scores the urgency for comprehensive investigation and development of mitigation strategies. This study addresses these challenges by subjecting a composite tidal blade to a series of incremental static and fatigue tests, culminating in controlled failure experiments conducted at the FastBlade structural fatigue testing facility. The facility’s advanced capabilities include a regenerative digital displacement hy- draulic pump system yielding substantial energy savings; an advanced multi-camera digital image correlation system; and an acoustic emission crack detection system. Using these we systematically explore the factors contributing to blade failure. The failure modes examined in this study include: metal-composite bond failure; crack propagation in thick-section composites; and adhesive failure of the hydrodynamic outer skin. Our findings have significant implications for the structural engineering, composite ma- terial, and tidal energy development communities. Notably, our study offers valuable insights into the mechanisms underlying both blade failure under extreme loads and the accumulation of damage in large, thick composite struc- tures. This research represents an important step towards enhancing the reliability and efficiency of tidal turbine blades, thus advancing the viability of tidal stream energy as a sustainable power source
Towards multi-faceted visual process analytics
Get PDFBoth the fields of Process Mining (PM) and Visual Analytics (VA) aim to make complex phenomena understandable. In PM, the goal is to gain insights into the execution of complex processes by analyzing the event data that is captured in event logs. This data is inherently multi-faceted, meaning that it covers various data facets, including spatial and temporal dependencies, relations between data entities (such as cases/events), and multivariate data attributes per entity. However, the multi-faceted nature of the data has not received much attention in PM. Conversely, VA research has investigated interactive visual methods for making multi-faceted data understandable for about two decades. In this study, we bring together PM and VA with the goal of advancing towards Visual Process Analytics (VPA) of multi-faceted processes. To this end, we present a systematic view of relevant (VA) data facets in the context of PM and assess to what extent existing PM visualizations address the data facets’ characteristics, making use of VA guidelines. In addition to visualizations, we look at how PM can benefit from analytical abstraction and interaction techniques known in the VA realm. Based on this, we discuss open challenges and opportunities for future research towards multi-faceted VPA
Conceptualizing transformative climate action: insights from sufficiency research
Get PDFThis synthesis article conceptualizes transformative climate actions (TCAs) by reviewing social-science-based climate and transformation research, with a particular focus on (Western) sufficiency literature. It identifies six key characteristics of TCAs. First, they aim to transform social practices and provisioning systems to reshape society-nature relations, requiring a ‘whole-of-government’ approach and state capacity building for cross-sectoral coordination. Second, TCAs prioritize sufficiency, using efficiency and substitution as supporting strategies rather than parallel goals. Third, they empower collective agency, shifting the focus from individual behaviour changes to societal structures. Fourth, they presuppose a shift toward a multi-level planning framework that moves beyond market-based governance, integrating top-down steering with bottom-up, reflexive deliberation and experimentation. Fifth, TCAs recognize the distributional character of ecological crises, ensuring universal access to essential provisioning while curbing excess production and consumption through eco-social policy portfolios. Finally, they rely on broad alliances of diverse actors, grounded in everyday interests, with empowered multi-stakeholder platforms to challenge entrenched interests. In developing these six characteristics, the article bridges conceptual debates with real-world policymaking, highlighting key climate policy challenges while demonstrating how integrating these characteristics can drive deep societal transformations and support policymakers in designing holistic strategies for effective climate action
Using optical coherence tomography in plant biology research: review and prospects
Get PDFVisualizing the microscopic structure of plants in vivo, non-invasively, and in real-time is the Holy Grail of botany. Optical coherence tomography (OCT) has all the characteristics necessary to achieve this feat. Indeed, OCT provides volumetric images of the internal structure of plants without the need for histological preparation. With its micrometric resolution, OCT is commonly used in medicine, primarily in ophthalmology. But it is seldom used in the field of botany. The aim of the present work is thus to review the latest technical development in the field of OCT and to highlight its current use in botany, in order to promote the technique and further advance research in the field of botany
A gentrification stage‐model for London? Through the ‘looking Glass’ of Kensington
Get PDFDespite the term ‘gentrification’ being coined in London by the British sociologist Ruth Glass, there has not been an attempt to develop a stage model of gentrification for London, nor any up‐to‐date discussion of the different waves of gentrification there in one academic paper or book. Research on urban gentrification tends to see gentrification as an evolving wave, or set of waves, that change in relation to context and the dynamics of urban change. In this paper we look at the different stages of gentrification that have affected London over time, we do so by looking through the lens of a long gentrified part of inner London—Kensington, part of the Royal Borough of Kensington and Chelsea. After establishing a stage model of gentrification in Kensington, we argue that stage models, like ours, have value in, for example, rethinking past trajectories of gentrification, but that we should be more critical of stage models going forwards
AULC 2025 conference reflections
No full textThe 26th annual conference of the Association of University Language Communities in the UK and Ireland (AULC) took place on 7-8 April 2025 and was hosted by the University of Liverpool. This year’s theme was “Multilingualism, Multiliteracies, Digital Technologies, and Accessibility in Language Teaching”.
The theme reflected a broader focus on the tools that we use in teaching and the multiple perspectives and creative approaches that we include in our teaching. A number of presentations shared current practice in taking a multimodal approach, developing students’ multiliteracies and digital skills, and the use of artificial intelligence in our teaching, including how it can assist us with lesson and materials preparation
Coronal jet identification with machine learning
Get PDFCoronal jets are narrow eruptions observable across various wavelengths, primarily driven by magnetic activity. These phenomena may play a pivotal role in solar activity, which significantly impacts the dynamics of the solar system, however they have not been studied in depth thus far. This work employs machine learning, specifically, via a random forest model, to enhance the assembly of the dataset of coronal jets. By combining data from two segmentation methods, semi-automated jet identification algorithm (SAJIA) and mathematical morphology (MM), we strove to develop a more comprehensive dataset. Our model was trained and validated initially on a robust dataset and subsequently applied to classify unlabelled data. To ensure a higher level of confidence for positive identifications, the classification threshold was increased to 0.95. This adjustment led to the identification of 3452 new jet candidates. The new candidates were then validated through visual inspection. The validation resulted in the identification of 3268 true jets and 184 false positives. Our findings highlight the e ectiveness of integrating machine learning with traditional analysis techniques to enhance the accuracy and reliability of solar jet identification. These results contribute to a deeper understanding of coronal jets and their role in solar dynamics, demonstrating the potential of machine learning in advancing solar physics research
Measures of adiposity, clothing size and risk of rheumatoid arthritis in middle-aged UK women: A prospective cohort study
Get PDFObjectives: To estimate the association between various indicators of obesity-related health risk and the incidence of rheumatoid arthritis (RA) in a large cohort of women.
Methods: The UK Women’s Cohort Study is a prospective cohort of 35,372 middle-aged women (aged 35–69 at recruitment) initiated in 1995–1998. Obesity was assessed using body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), categorised according to WHO and NICE guidelines, as well as clothing size. Incident RA cases were identified via Hospital Episode Statistics (HES) linkage up to March 2019. Cox regression models were used to estimate RA risk, adjusting for demographics, reproductive factors, and lifestyle factors. Non-linear associations were examined using restricted cubic splines.
Results: Among 27,968 eligible subjects with complete data linkage (625,269 person-years of follow-up), there were 255 incident RA cases. Obesity (≥30.0 kg/m2) was associated with increased RA risk (HR (95% CI) 1.48 (1.02, 2.17), as were abdominal obesity (WC > 88 cm: 1.58 (1.10, 2.27)), WHR ≥ 0.85 (1.56 (1.03, 2.36)), and WHtR ≥ 0.6 (2.25 (1.34, 3.80)). Each 2.5 kg/m² increase in BMI was associated with a 9% higher risk of RA; each 5 cm increase in WC with 6%; each 0.1 increase in WHR with 20%, and each 0.1 increase in WHtR with 27%. Larger clothing sizes were associated with a greater RA risk: for each onesize increment in blouse size and skirt size, the HRs were 1.13 (95% CI: 1.04, 1.22) and 1.13 (95% CI: 1.05, 1.22), respectively. Notably, skirt size ≥ 20 was associated with a 2.36-fold increased risk of RA. There was evidence of effect modification by weight change and menopausal status in obesity-related RA risk.
Conclusions: Our findings suggest that managing obesity and central adiposity in middle-aged women may be associated with the risk of developing RA. WHtR may serve as a practical alternative to BMI in assessing RA risk. Clothing size, particularly skirt size, could provide a simple, cost-effective proxy for identifying at high risk of RA
AgriPV system with climate, water and light spectrum control for safe, healthier and improved crop production
Get PDFThe PV4Plants project aims to optimise the synergy between agriculture and photovoltaic (agriPV) systems to improve crop yield, land use efficiency, and renewable energy conversion. Using cutting-edge nanoparticles coated between PV panels to optimise light transmission, the system tailors conditions for specific crops and climatic regions. Demonstrations in Türkiye, Spain, and Denmark test the adaptability and effectiveness of these systems, to evaluate improvements in crop health and renewable energy output. Central to the project are efforts to increase recyclability and promote farmer engagement through innovative financing models and policy recommendations
Remarks on the spectra of minimal hypersurfaces in the hyperbolic space
Get PDFWe compute the Laplacian spectra of singular area-minimising hypersurfaces in the hyperbolic space with prescribed asymptotic data. We also obtain similar results in higher codimension, and explore related extremal properties of the bottom of the spectrum
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