In this paper, based on the CFD software ANSYS-Fluent, two-dimensional numerical models are established to investigate the hydrodynamic performance of a self-starting H-Darrius vertical axis tidal turbine (VATT) array of three turbines in a triangular layout with 3D in axial and radial distance. Three main aspects are explored in this study: (1) the self-starting performance, power coefficient, flow fields, and blade force of the double-row VATT array, which are compared with a stand-alone turbine, (2) the wake development of the front and rear displacement turbines, and (3) the feasibility of the double-row self-starting VATT array in practical applications. It is found that the power coefficients of the three turbines in the array all improved compared with that of the stand-alone turbine, and as the load increased, the difference between the averaged power coefficient of the array and a stand-alone turbine was more obvious, with a maximum difference of 3%. The main effects of the front turbines on the rear turbine are energy utilization and turbine vibration. Due to the beam effect between the front turbines, the incident flow rate of the rear turbine increased to approximately 1.2 times the free flow rate. However, the greater rotational fluctuations of the rear turbine mean that although it had a higher power factor, it was more susceptible to fatigue damage. The wake of the rear turbine in the array had a much larger area of influence on both the length and width, but the velocity deficit recovered more quickly to over 95% at a distance of 10D behind it. The rate of wake velocity recovery is load-dependent for a stand-alone self-starting turbine, but this was not evident in the arrays. The positive torque of the turbine is mainly generated when the blade rotates through an azimuth angle from 45° to 160° and mainly benefits from the inner side of the blade. For the double-row three-turbine array, the axial and radial spacing of 3D is reasonable in practical applications.
Abstract Despite the progressive decline in the virulence of the novel coronavirus, there has been no corresponding reduction in its associated hospital mortality. Our aim was to redefine an accurate predictor of mortality risk in COVID-19 patients, enabling effective management and resource allocation. We conducted a retrospective analysis of 2917 adult Chinese patients diagnosed with COVID-19 who were admitted to our hospital during two waves of epidemics, involving the Beta and Omicron variants. Upon admission, NT-proBNP levels were measured, and we collected demographic, clinical, and laboratory data. We introduced a new concept called the NT-proBNP ratio, which measures the NT-proBNP level relative to age-specific maximum normal values. The primary outcome was all-cause in-hospital mortality. Our analysis revealed a higher in-hospital mortality rate in 2022, as shown by the Kaplan–Meier Survival Curve. To assess the predictive value of the NT-proBNP ratio, we employed the time-dependent receiver operating characteristic (ROC) curve. Notably, the NT-proBNP ratio emerged as the strongest predictor of mortality in adult Chinese hospitalized COVID-19 patients (area under the curve, AUC = 0.826; adjusted hazard ratio [HR], 3.959; 95% confidence interval [CI] 3.001–5.221; P < 0.001). This finding consistently held true for both the 2020 and 2022 subgroups. The NT-proBNP ratio demonstrates potential predictive capability compared to several established risk factors, including NT-proBNP, hsCRP, and neutrophil-to-lymphocyte ratio, when it comes to forecasting in-hospital mortality among adult Chinese patients with COVID-19. Trial registration Clinical Trial Registration: www.clinicaltrials.gov NCT05615792.
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