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Thermal history coatings: influence of atmospheric plasma spray parameters on performance
Get PDFFiring temperatures in gas turbines have seen a steady increase over the years to allow for higher engine efficiencies and lower hazardous emission levels. Conversely, these harsh conditions severely challenge component lifetime, requiring a design trade-off. Thus, it is crucial to understand temperature distribution across most of a component surface (>80%) to verify the design and durability. While a range of temperature measurement techniques are available, these primarily focus on lower temperatures, exhibit low durability (thermal paints), require line of sight (pyrometers), are destructive (thermal crystals) and only provide point measurements (thermocouples).
To overcome this challenge, Thermal History Coatings (THCs) measure temperature profiles in the 900-1600°C range. This new temperature profiling capability records the past maximum exposure temperature; this is determined once the component has already cooled down.
THCs are oxide ceramics deposited via Atmospheric Plasma Spraying (APS). APS deposition employs several variable parameters, which can affect the material process and therefore its temperature sensing performance.
This paper shows, for the first time, the influence of APS parameters on luminescent measurements due to changes in the material microstructure. Extensive calibration data was used to develop a new model relating APS spray parameters to the luminescent properties and consequent performance as a temperature sensor. The model identified the optimum spray parameters and was used to demonstrate THCs can achieve measurements in excess of 1600°C.The authors would like to thank the Royal Commission for the Exhibition of 1851 and the National Aerospace Technology Exploitation Programme (NATEP) for their continued financial support during the project.Journal of Engineering for Gas Turbines and Powe
Design and operation of single- and multi-deep shuttle-based storage and retrieval systems (SBS/RS)
No full textWith the rapid growth of e-commerce practices, the efficient management of warehouses and fulfilment centres has become crucial in supply chain operations. One effective strategy for achieving this efficiency is the digital transformation of warehouses through automation. In particular, shuttle-based storage and retrieval systems (SBS/RS) have gained significant attention due to their ultra-high transaction process capability. However, ongoing research focuses on enhancing the operating performance and cost efficiency of these SBS/RS designs. This chapter presents mathematical modelling approaches for estimating the performance of single- and multi-deep SBS/RS designs. These models provide valuable insights for designing warehouses that optimize transaction process rates while ensuring a balanced utilization of elevators and shuttles in the system, tailored to meet the specific requirements of the warehouse. By leveraging these modelling techniques, warehouse managers can make informed decisions regarding the design and configuration of SBS/RSs to improve overall operational efficiency and productivity.This research work was supported by the Slovenian Research Agency (ARRS) in the framework of the Applied research project entitled: “Warehousing 4.0—Integration model of robotics and warehouse order picking systems”; grant number: L5-2626.Warehousing and Material Handling Systems for the Digital Industr
Biological factors and production challenges drive significant UK fruit and vegetable loss
Get PDFBACKGROUND
Food loss and waste estimates are highly inconsistent as a result of methodological and systemic differences. Additionally, the absence of in‐depth evidence surrounding the biological drivers of food loss and waste precludes targeted mitigation action. To address this challenge, we undertook a metanalysis utilising a systematic literature review combined with industry stakeholder surveys to examine the incidence of food loss and waste in the UK fruit and vegetable supply chain between primary production and retail.
RESULTS
We estimated that 37% of fruit and vegetables, equivalent to 2.4 Mt of produce, is lost between production and sale. In the UK, primary production is the main stage responsible for these losses (58%), and is dominated by four crops (apple, onion, carrot and potato), which contribute 71% of total food loss and waste. Quality and supply/demand mismatch are the core drivers, combined with limited ability to control postharvest quality decline as a result of technical or economic barriers.
CONCLUSIONS
Innate biological mechanisms contribute to, and detract from, marketable quality generating food loss risks where these cannot be adequately modified or controlled. Through climate change effects, reduced pesticide availability, changing consumer behaviour and increased pressure to reduce resource/energy inputs during pre‐ and postharvest handling, food loss and waste risk is likely to increase in the short term unless targeted, coordinated action is taken to actively promote its mitigation.Engineering and Physical Sciences Research CouncilWe thank the Engineering & Physical Sciences Research Council for financial support through the project EP/V042548/1.Journal of the Science of Food and Agricultur
Early breast cancer detection using artificial intelligence techniques based on advanced image processing tools
Get PDFThe early detection of breast cancer is essential for improving treatment outcomes, and recent advancements in artificial intelligence (AI), combined with image processing techniques, have shown great potential in enhancing diagnostic accuracy. This study explores the effects of various image processing methods and AI models on the performance of early breast cancer diagnostic systems. By focusing on techniques such as Wiener filtering and total variation filtering, we aim to improve image quality and diagnostic precision. The novelty of this study lies in the comprehensive evaluation of these techniques across multiple medical imaging datasets, including a DCE-MRI dataset for breast-tumor image segmentation and classification (BreastDM) and the Breast Ultrasound Image (BUSI), Mammographic Image Analysis Society (MIAS), Breast Cancer Histopathological Image (BreakHis), and Digital Database for Screening Mammography (DDSM) datasets. The integration of advanced AI models, such as the vision transformer (ViT) and the U-KAN model—a U-Net structure combined with Kolmogorov–Arnold Networks (KANs)—is another key aspect, offering new insights into the efficacy of these approaches in different imaging contexts. Experiments revealed that Wiener filtering significantly improved image quality, achieving a peak signal-to-noise ratio (PSNR) of 23.06 dB and a structural similarity index measure (SSIM) of 0.79 using the BreastDM dataset and a PSNR of 20.09 dB with an SSIM of 0.35 using the BUSI dataset. When combined filtering techniques were applied, the results varied, with the MIAS dataset showing a decrease in SSIM and an increase in the mean squared error (MSE), while the BUSI dataset exhibited enhanced perceptual quality and structural preservation. The vision transformer (ViT) framework excelled in processing complex image data, particularly with the BreastDM and BUSI datasets. Notably, the Wiener filter using the BreastDM dataset resulted in an accuracy of 96.9% and a recall of 96.7%, while the combined filtering approach further enhanced these metrics to 99.3% accuracy and 98.3% recall. In the BUSI dataset, the Wiener filter achieved an accuracy of 98.0% and a specificity of 98.5%. Additionally, the U-KAN model demonstrated superior performance in breast cancer lesion segmentation, outperforming traditional models like U-Net and U-Net++ across datasets, with an accuracy of 93.3% and a sensitivity of 97.4% in the BUSI dataset. These findings highlight the importance of dataset-specific preprocessing techniques and the potential of advanced AI models like ViT and U-KAN to significantly improve the accuracy of early breast cancer diagnostics.Electronic
Human impacts mediate freshwater invertebrate community responses to and recovery from drought
No full textDrought is an increasing risk to the biodiversity within rivers—ecosystems which are already impacted by human activities. However, the long‐term spatially replicated studies needed to generate understanding of how anthropogenic stressors alter ecological responses to drought are lacking.
We studied aquatic invertebrate communities in 2500 samples collected from 179 sites on rivers emerging from England's chalk aquifer over three decades. We tested two sets of alternative hypotheses describing responses to and recovery from drought in interaction with human impacts affecting water quality, fine sediment, water temperature, channel morphology, flow and temporal change in land use. We summarized communities using taxa richness, an index indicating tolerance of anthropogenic degradation (average score per taxon, ASPT) and deviation from the average composition.
Responses to drought were altered by interactions with human impacts. Poor water quality exacerbated drought‐driven reductions in taxa richness. Drought‐driven deviations from the average community composition were reduced and enhanced at sites impacted by flow augmentation (e.g. effluent releases) and flow reduction (e.g. abstraction), respectively.
Human impacts altered post‐drought recovery. Increases in richness were lower at sites impacted by water abstraction and higher at sites with augmented flows, in particular as recovery trajectories extended beyond 3 years. ASPT recovered faster at sites that gained woodland compared to urban land, due to their greater recovery potential, that is, their lower drought‐driven minimum values and higher post‐drought maximum values.
Synthesis and applications. We show that communities in river ecosystems exposed to human impacts—in particular poor water quality, altered flow volumes and land use change—are particularly vulnerable to drought. These results provide evidence that management actions taken to enhance water quality, regulate abstraction and restore riparian land use could promote ecological resilience to drought in groundwater‐dominated rivers such as globally rare chalk streams and other rivers of the Anthropocene, as they adapt to a future characterized by increasing climatic extremity.Department for Environment, Food and Rural AffairsJournal of Applied Ecolog
Exploring the potentialities of thermal asymmetries in composite wind turbine blade structures via numerical and thermographic methods: a thermophysical perspective
Get PDFUsing composite materials in turbine blades has become common in the wind power industry due to their mechanical properties and low mass. This work aims to investigate the effectiveness of the active infrared thermography technique as a non-destructive inspection tool to identify defects in composite material structures of turbine blades. Experiments were carried out by heating the sample and capturing thermographic images using a thermal camera in four different scenarios, changing the heating strategy. Such a preliminary experiments are prodromic to build, in future, the so-called optimal experiment design for thermal property estimation. The experimental results using two heaters arranged symmetrically on the sample detected the presence of the defect through temperature curves extracted from thermal images, where temperature asymmetries of 25% between the regions with and without defect occurred. Moreover, when only a larger heater was used in transmission mode, the defect was detected based on differences between normalized excess temperatures on the side with and without the defect in the order of 20%. Additionally, numerical simulations were carried out to present solutions for improving defect detection. It was demonstrated that active infrared thermography is an efficient technique for detecting flaws in composite material structures of turbine blades. This research contributes to advancing knowledge in inspecting composite materials.National Council for Scientific and Technological DevelopmentThis study was financed in part by the National Council for Scientific and Technological Development (CNPq) - Finance Codes 407.140/2021-2 and 312.530/2023-4.Journal of Thermal Analysis and Calorimetr
Lean thinking and resource efficiency in the design of public services
Get PDFEfficiency in public service organisations is often driven by the need to reduce costs and increase productivity due to the economic and government pressure to make the best use of reduced resources. However, efficiency in public services can go beyond cost cutting, thinking about how organisations design and deliver their service offerings to achieve better outcomes while using the government fund more efficiently to turn public money into positive outcomes for both individuals and society. Through a combined method of literature review and interviews, the authors aim to systematically collect and analyse existing contributions on the current public services design and how Lean Thinking can promote resource efficiency in public service organisations, followed by validating the results through interviews in different public organisations focusing on the role of human resources in the services design. The findings suggest that implementing Lean Thinking allows public service organisations to streamline their resource allocation, eliminate waste, and improve productivity, resulting in more efficient service delivery, user satisfaction, and improved organisational performance. The authors took a panoramic view across different public organisation types, which can be extended through future research on specific organisation types or different regions to explore unique dimensions and find relevant conclusions.34th CIRP Design Conference 2024Procedia CIR
On hysteresis in a variable pitch fan transitioning to reverse thrust mode and back
Get PDFA novel hysteresis phenomenon during the transition to and back from the reverse thrust mode in a Variable Pitch Fan (VPF) is identified and characterised in this work. This is done by using a three-dimensional (3D) fully transient Unsteady Reynolds-averaged Navier-Stokes (URANS) with the transitioning fan blade aerofoils simulated by an adaptation of the mesh displacement method. A “real-time” simulation of the complete VPF hysteresis loop is achieved by specifying a blade wall motion through an Eulerian rotation matrix in differential, gradual steps, that is combined with a mesh probe-and-update routine for improved numerical accuracy and stability. The VPF is modelled to be transitioning in a modern 40000 lbf geared high bypass ratio turbofan engine architecture at “Approach Idle” engine power setting in a typical twin-engine airframe with the flaps, slats, and spoilers set for an aircraft touchdown airspeed of 140 knots.
The transition to reverse thrust mode involves flow starvation into the engine, formation of recirculation zones in the bypass duct and the establishment of the reverse stream, all of which occurs in the opposing presence of the free stream flow at aircraft touchdown velocity. The transition back to forward flow mode involves the gradual re-establishment of the free stream which is opposed by the presence of the reverse stream within the engine. It is quantified that in the transition to reverse thrust, the blockage develops with a larger time delay than the disappearance of the blockage during the transition back due to the interplay of the temporal dynamics of fan blade motion and flow field response. The details of the changes in the flow field behaviour, the effect of engine power setting and aircraft touch down velocity on the hysteresis behaviour are explained in detail in the paper. Additional manifestations of the hysteresis phenomena at reverse thrust involving engine spool-up and down, and aircraft acceleration-deceleration manoeuvres are also explored. The hysteresis phenomena described in this work are critical in properly developing control schedules to adapt for potential bi-stable flow field development during the landing run. The study addresses another part of the puzzle in exploring the feasibility of reverse thrust capable VPF engines for future sustainable aircraft to reach aviation climate neutrality.The authors would like to thank Rolls-Royce plc. for supporting this research and for permission to publish the paper.ASME Turbo Expo 2024: Turbomachinery Technical Conference and Expositio
Automating the derivation of sugarcane growth stages from Earth observation time series
Get PDFSugarcane is a high-impact crop used in the majority of global sugar production, with India being the second largest global producer. Understanding the timing and length of sugarcane growth stages is critical to improving the sustainability of sugarcane management. Earth observation (EO) data have been shown to be sensitive to the variation in sugarcane growth, but questions remain as to how to reliably extract sugarcane phenology over wide areas so that this information can be used for effective management. This study develops an automated approach to derive sugarcane growth stages using EO data from Landsat-8 and Sentinel-2 satellite data in the Indian state of Andhra Pradesh. The developed method is then evaluated in the State of Telangana. Normalised difference vegetation index (NDVI) EO data from Landsat-8 and Sentinel-2 were pre-processed to filter out clouds and to harmonise sensor response. Pixel-based cloud filtering was selected over filtering by scene in order to increase the temporal frequency of observations. Harmonising data from two different sensors further increased temporal resolution to 3–6 days (70% of sampled fields). To automate seasonal decomposition, harmonised signals were resampled at 14 days, and low-frequency components, related to seasonal growth, were extracted using a fast Fourier transform. The start and end of each season were extracted from the time series using difference of Gaussian and were compared to assessments based on visual observation for both Unit 1 (R2 = 0.72–0.84) and Unit 2 (R2 = 0.78–0.82). A trapezoidal growth model was then used to derive crop growth stages from satellite-measured phenology for better crop management information. Automated assessments of the start and the end of mid-season growth stages were compared to visual observations in Unit 1 (R2 = 0.56–0.72) and Unit 2 (R2 = 0.36–0.79). Outliers were found to result from cloud cover that was not removed by the initial screening as well as multiple crops or harvesting dates within a single field. These results demonstrate that EO time series can be used to automatically determine the growth stages of sugarcane in India over large areas, without the need for prior knowledge of planting and harvest dates, as a tool for improving sustainable production.This research was funded by the Natural Environment Research Council (NERC) sponsored by Central England NERC Training Alliance (CENTA2) Doctoral Training Partnership [grant number NE/S007350/1].Remote Sensin
Transparent, sprayable plastic films for luminescent down‐shifted‐assisted plant growth
Get PDFThe world's steadily growing population and global heating due to climate change are a threat to food security. To meet this challenge, novel technologies are needed to increase crop production in a sustainable way. In this work, the use of luminescent down‐shifting (LDS) materials based on molecular Eu3+‐containing polyoxotitanates for plant growth enhancement is investigated. Using a systematic design strategy to optimize down‐shifting properties, conversion of the ultraviolet spectral range to the photosynthetically active radiation (PAR) is achieved with quantum yields as high as 68%. The prototype Eu3+‐compound can be incorporated into water‐based acrylic varnish that can be spray‐coated onto existing greenhouses. Comparing coated with uncoated greenhouses, basil plants produce 9% more leaf dry weight per plant, and a highly significant 10% increase in individual leaf dry weight. The coating reduces the amount of transmitted PAR by 8% but has advantageous effects on diffuse radiation and in reducing the internal mean temperature. Although there is some uncertainty as to the contribution of down‐shifting, with the bulk of the increase probably being due to higher diffused light and the reduction in maximum daily temperatures, this study establishes a model for the design of LDS paints for real‐world agricultural applications.Helmholtz Association of German Research Centres, Federal Ministry of Education and Research, Innovate UKPlant growth trails were supported by the Technology Accelerator Fund at Cranfield, enabled by Green Future In-vestmentsAdvanced Materials Technologie