189 research outputs found

    Progress on the development of a holistic coupled model of dynamics for offshore wind farms : phase II - study on a data-driven based reduced-order model for a single wind turbine

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    At present, over 1500 offshore wind turbines (OWTs) are operating in the UK with a capacity of 5.4GW. Until now, the research has mainly focused on how to minimise the CAPEX, but Operation and Maintenance (O&M) can represent up to 39% of the lifetime costs of an offshore wind farm, mainly due to the assets’ high cost and the harsh environment in which they operate. Focusing on O&M, the HOME Offshore research project (www.homeoffshore.org) aims to derive an advanced interpretation of the fault mechanisms through holistic multiphysics modelling of the wind farm. With the present work, an advanced model of dynamics for a single wind turbine is developed, able to identify the couplings between aero-hydro-servo-elastic (AHSE) dynamics and drive train dynamics. The wind turbine mechanical components, modelled using an AHSE dynamic model, are coupled with a detailed representation of a variable-speed direct-drive 5MW permanent magnet synchronous generator (PMSG) and its fully rated voltage source converters (VSCs). Using the developed model for the wind turbine, several case studies are carried out for above and below rated operating conditions. Firstly, the response time histories of wind turbine degrees of freedom (DOFs) are modelled using a full-order coupled analysis. Subsequently, regression analysis is applied in order to correlate DOFs and generated rotor torque (target degree of freedom for the failure mode in analysis), quantifying the level of inherent coupling effects. Finally, the reduced-order multiphysics models for a single offshore wind turbine are derived based on the strength of the correlation coefficients. The accuracy of the proposed reduced-order models is discussed, comparing it against the full-order coupled model in terms of statistical data and spectrum. In terms of statistical results, all the reducedorder models have a good agreement with the full-order results. In terms of spectrum, all the reduced-order models have a good agreement with the full-order results if the frequencies of interest are below 0.75Hz

    Racial and ethnic disparities in access to minimally invasive mitral valve surgery

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    IMPORTANCE: Whether people from racial and ethnic minority groups experience disparities in access to minimally invasive mitral valve surgery (MIMVS) is not known. OBJECTIVE: To investigate racial and ethnic disparities in the utilization of MIMVS. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used data from the Society of Thoracic Surgeons Database for patients who underwent mitral valve surgery between 2014 and 2019. Statistical analysis was performed from January 24 to August 11, 2022. EXPOSURES: Patients were categorized as non-Hispanic White, non-Hispanic Black, and Hispanic individuals. MAIN OUTCOMES AND MEASURES: The association between MIMVS (vs full sternotomy) and race and ethnicity were evaluated using logistic regression. RESULTS: Among the 103 753 patients undergoing mitral valve surgery (mean [SD] age, 62 [13] years; 47 886 female individuals [46.2%]), 10 404 (10.0%) were non-Hispanic Black individuals, 89 013 (85.8%) were non-Hispanic White individuals, and 4336 (4.2%) were Hispanic individuals. Non-Hispanic Black individuals were more likely to have Medicaid insurance (odds ratio [OR], 2.21; 95% CI, 1.64-2.98; P \u3c .001) and to receive care from a low-volume surgeon (OR, 4.45; 95% CI, 4.01-4.93; P \u3c .001) compared with non-Hispanic White individuals. Non-Hispanic Black individuals were less likely to undergo MIMVS (OR, 0.65; 95% CI, 0.58-0.73; P \u3c .001), whereas Hispanic individuals were not less likely to undergo MIMVS compared with non-Hispanic White individuals (OR, 1.08; 95% CI, 0.67-1.75; P = .74). Patients with commercial insurance had 2.35-fold higher odds of undergoing MIMVS (OR, 2.35; 95% CI, 2.06-2.68; P \u3c .001) than those with Medicaid insurance. Patients operated by very-high volume surgeons (300 or more cases) had 20.7-fold higher odds (OR, 20.70; 95% CI, 12.7-33.9; P \u3c .001) of undergoing MIMVS compared with patients treated by low-volume surgeons (less than 20 cases). After adjusting for patient risk, non-Hispanic Black individuals were still less likely to undergo MIMVS (adjusted OR [aOR], 0.88; 95% CI, 0.78-0.99; P = .04) and were more likely to die or experience a major complication (aOR, 1.25; 95% CI, 1.16-1.35; P \u3c .001) compared with non-Hispanic White individuals. CONCLUSIONS AND RELEVANCE: In this cross-sectional study, non-Hispanic Black patients were less likely to undergo MIMVS and more likely to die or experience a major complication than non-Hispanic White patients. These findings suggest that efforts to reduce inequity in cardiovascular medicine may need to include increasing access to private insurance and high-volume surgeons

    A System Development Kit for Big Data Applications on FPGA-based Clusters: The EVEREST Approach

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    Modern big data workflows are characterized by computationally intensive kernels. The simulated results are often combined with knowledge extracted from AI models to ultimately support decision-making. These energy-hungry workflows are increasingly executed in data centers with energy-efficient hard-ware accelerators since FPG As are well-suited for this task due to their inherent parallelism. We present the H2020 project EVEREST, which has developed a system development kit (SDK) to simplify the creation of FPGA-accelerated kernels and manage the execution at runtime through a virtualization environment. This paper describes the main components of the EVEREST SDK and the benefits that can be achieved in our use cases

    Crop changes from the XVI century to the present in a hill/mountain area of eastern Liguria (Italy)

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    <p>Abstract</p> <p>Background</p> <p>Chronological information on the composition and structure of agrocenoses and detailed features of land cover referring to specific areas are uncommon in ethnobotanical studies, especially for periods before the XIX century. The aim of this study was to analyse the type of crop or the characteristics of soil cover from the XVI century to the present.</p> <p>Methods</p> <p>This diachronic analysis was accomplished through archival research on the inventories of the Parish of St. Mary and those of the Municipality of Pignone and from recent surveys conducted in an area of eastern Liguria (Italy).</p> <p>Results</p> <p>Archival data revealed that in study area the primary means of subsistence during the last five centuries, until the first half of the XX century, was chestnuts. In the XVIII and XIX centuries, crop diversification strongly increased in comparison with previous and subsequent periods. In more recent times, the abandonment of agricultural practices has favoured the re-colonisation of mixed woodland or cluster-pine woodland.</p> <p>Conclusion</p> <p>Ancient documents in the ecclesiastic or municipal inventories can be a very useful tool for enhancing the knowledge of agricultural practice, as well as of subsistence methods favoured by local populations during a particular time and for reconstructing land use change over time.</p

    Evidence-based Kernels: Fundamental Units of Behavioral Influence

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    This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior
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