103 research outputs found

    Development of helium turbine loss model based on knowledge transfer with Neural Network and its application on aerodynamic design

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    Helium turbines are widely used in the Closed Brayton Cycle for power generation and aerospace applications. The primary concerns of designing highly loaded helium turbines include choosing between conventional and contra-rotating designs and the guidelines for selecting design parameters. A loss model serving as an evaluation means is the key to addressing this issue. Due to the property disparities between helium and air, turbines utilizing either as working fluid experience distinct loss mechanisms. Consequently, directly applying gas turbine experience to the design of helium turbines leads to inherent inaccuracies. A helium turbine loss model is developed by combining knowledge transfer and the Neural Network method to accurately predict performance at design and off-design points. By utilizing the loss model, design parameter selection guidelines for helium turbines are obtained. A comparative analysis is conducted of conventional and contra-rotating helium turbine designs. Results show that the prediction errors of the loss model are below 0.5% at over 90% of test samples, surpassing the accuracy achieved by the gas turbine loss model. Design parameter selection guidelines for helium turbines differ significantly from those based on gas turbine experience. The contra-rotating helium turbine design exhibits advantages in size, weight, and aerodynamic performance

    A retrospective study evaluating the correlation between the severity of intervertebral disc injury and the anteroposterior type of thoracolumbar vertebral fractures

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    OBJECTIVE: To evaluate the correlation between the severity of intervertebral disc injury and the anteroposterior type of thoracolumbar vertebral fractures. METHODS: Fifty-six cases of thoracolumbar vertebral fractures treated in our trauma center from October 2012 to October 2013 were included in this study. The fractures were classified by the anteroposterior classification, whereas the severity of intervertebral disc injury was evaluated using magnetic resonance imaging. The Spearman correlation coefficient was used to analyze the correlation between the severity of intervertebral disc injury and the anteroposterior type of thoracolumbar fractures, whereas a χ2 test was adopted to measure the variability between different fracture types and upper and lower adjacent disc injuries. RESULTS: The Spearman correlation coefficients between fracture types and the severity of the upper and lower adjacent disc injuries were 0.739 (P

    Defining the Genetic Features of O-Antigen Biosynthesis Gene Cluster and Performance of an O-Antigen Serotyping Scheme for Escherichia albertii

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    Escherichia albertii is a newly described and emerging diarrheagenic pathogen responsible for outbreaks of gastroenteritis. Serotyping plays an important role in diagnosis and epidemiological studies for pathogens of public health importance. The diversity of O-antigen biosynthesis gene clusters (O-AGCs) provides the primary basis for serotyping. However, little is known about the distribution and diversity of O-AGCs of E. albertii strains. Here, we presented a complete sequence set for the O-AGCs from 52 E. albertii strains and identified seven distinct O-AGCs. Six of these were also found in 15 genomes of E. albertii strains deposited in the public database. Possession of wzy/wzx genes in each O-AGC strongly suggest that O-antigens of E. albertii were synthesized by the Wzx/Wzy-dependent pathway. Furthermore, we performed an O-antigen serotyping scheme for E. albertii based on specific antisera against seven O-antigens and a high throughput xTAG Luminex assay to simultaneously detect seven O-AGCs. Both methods accurately identified serotypes of 64 tested E. albertii strains. Our data revealed the high-level diversity of O-AGCs in E. albertii. We also provide valuable methods to reliably identify and serotype this bacterium

    2023 roadmap for potassium-ion batteries

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    The heavy reliance of lithium-ion batteries (LIBs) has caused rising concerns on the sustainability of lithium and transition metal and the ethic issue around mining practice. Developing alternative energy storage technologies beyond lithium has become a prominent slice of global energy research portfolio. The alternative technologies play a vital role in shaping the future landscape of energy storage, from electrified mobility to the efficient utilization of renewable energies and further to large-scale stationary energy storage. Potassium-ion batteries (PIBs) are a promising alternative given its chemical and economic benefits, making a strong competitor to LIBs and sodium-ion batteries for different applications. However, many are unknown regarding potassium storage processes in materials and how it differs from lithium and sodium and understanding of solid–liquid interfacial chemistry is massively insufficient in PIBs. Therefore, there remain outstanding issues to advance the commercial prospects of the PIB technology. This Roadmap highlights the up-to-date scientific and technological advances and the insights into solving challenging issues to accelerate the development of PIBs. We hope this Roadmap aids the wider PIB research community and provides a cross-referencing to other beyond lithium energy storage technologies in the fast-pacing research landscape
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