Optimization of an axial fan for air cooled condensers

We report on the low noise optimization of an axial fan specifically designed for the cooling of CSP power plants. The duty point presents an uncommon combination of a load coefficient of 0.11, a flow coefficient of 0.23 and a static efficiency ηstat > 0.6. Calculated fan Reynolds number is equal to Re = 2.85 x 107. Here we present a process used to optimize and numerically verify the fan performance. The optimization of the blade was carried out with a Python code through a brute-force-search algorithm. Using this approach the chord and pitch distributions of the original blade are varied under geometrical constraints, generating a population of over 24000 different possible individuals. Each individual was then tested using an axisymmetric Python code. The software is based on a blade element axisymmetric principle whereby the rotor blade is divided into a number of streamlines. For each of these streamlines, relationships for velocity and pressure are derived from conservation laws for mass, tangential momentum and energy of incompressible flows. The final geometry was eventually chosen among the individuals with the maximum efficiency. The final design performance was then validated through with a CFD simulation. The simulation was carried out using a RANS approach, with the cubic k -  low Reynolds turbulence closure of Lien et al. The numerical simulation was able to verify the air performance of the fan and was used to derive blade-to-blade distributions of design parameters such as flow deviation, velocity components, specific work and diffusion factor of the optimized blade. All the computations were performed in OpenFoam, an open source C++- based CFD library. This work was carried out under MinWaterCSP project, funded by EU H2020 programme

Diagnostic accuracy and interobserver variability of CO-RADS in patients with suspected coronavirus disease-2019: a multireader validation study

Objective: To conduct a multireader validation study to evaluate the interobserver variability and the diagnostic accuracy for the lung involvement by COVID-19 of COVID-19 Reporting and Data System (CO-RADS) score. Methods: This retrospective study included consecutive symptomatic patients who underwent chest CT and reverse transcriptase-polymerase chain reaction (RT-PCR) from March 2020 to May 2020 for suspected COVID-19. Twelve readers with different levels of expertise independently scored each CT using the CO-RADS scheme for detecting pulmonary involvement by COVID-19. Receiver operating characteristic (ROC) curves were computed to investigate diagnostic yield. Fleiss’ kappa statistics was used to evaluate interreader agreement. Results: A total of 572 patients (mean age, 63 ± 20 [standard deviation]; 329 men; 142 patients with COVID-19 and 430 patients without COVID-19) were evaluated. There was a moderate agreement for CO-RADS rating among all readers (Fleiss’ K = 0.43 [95% CI 0.42–0.44]) with a substantial agreement for CO-RADS 1 category (Fleiss’ K = 0.61 [95% CI 0.60–0.62]) and moderate agreement for CO-RADS 5 category (Fleiss’ K = 0.60 [95% CI 0.58–0.61]). ROC analysis showed the CO-RADS score ≥ 4 as the optimal threshold, with a cumulative area under the curve of 0.72 (95% CI 66–78%), sensitivity 61% (95% CI 52–69%), and specificity 81% (95% CI 77–84%). Conclusion: CO-RADS showed high diagnostic accuracy and moderate interrater agreement across readers with different levels of expertise. Specificity is higher than previously thought and that could lead to reconsider the role of CT in this clinical setting. Key Points: • COVID-19 Reporting and Data System (CO-RADS) demonstrated a good diagnostic accuracy for lung involvement by COVID-19 with an average AUC of 0.72 (95% CI 67–75%). • When a threshold of ≥ 4 was used, sensitivity and specificity were 61% (95% CI 52–69%) and 81% (95% CI 76–84%), respectively. • There was an overall moderate agreement for CO-RADS rating across readers with different levels of expertise (Fleiss’ K = 0.43 [95% CI 0.42–0.44])

Cerebral vein thrombosis in patients with Philadelphia-negative myeloproliferative neoplasms : an European Leukemia Net study

To investigate the characteristics and clinical course of cerebral vein thrombosis (CVT) in patients with myeloproliferative neoplasms (MPN) we compared 48 patients with MPN and CVT (group MPN-CVT) to 87 with MPN and other venous thrombosis (group MPN-VT) and 178 with MPN and no thrombosis (group MPN-NoT) matched by sex, age at diagnosis of MPN (\ub15 years) and type of MPN. The study population was identified among 5,500 patients with MPN, from January 1982 to June 2013. Thrombophilia abnormalities were significantly more prevalent in the MPN-CVT and MPN-VT than in MPN-NoT group (P = 0.015), as well as the JAK2 V617F mutation in patients with essential thrombocythemia (P = 0.059). Compared to MPN-VT, MPN-CVT patients had a higher rate of recurrent thrombosis (42% vs. 25%, P = 0.049) despite a shorter median follow-up period (6.1 vs. 10.3 years, P = 0.019), a higher long-term antithrombotic (94% vs. 84%, P = 0.099) and a similar cytoreductive treatment (79% vs. 70%, P = 0.311). The incidence of recurrent thrombosis was double in MPN-CVT than in MPN-VT group (8.8% and 4.2% patient-years, P = 0.022), and CVT and unprovoked event were the only predictive variables in a multivariate model including also sex, blood count, thrombophilia, cytoreductive, and antithrombotic treatment (HR 1.97, 95%CI 1.05-3.72 and 2.09, 1.09-4.00, respectively). \ua9 2014 Wiley Periodicals, Inc

Rheological behaviour of nanocomposites based on polyamide 6 under shear and elongational flow at high strain rates

In this work, the rheological behaviour of high molecular mass polyamide 6 (PA6)/organomontmorillonite nano-composites, obtained via melt blending, was investigated under shear and extensional flow. Capillary rheometry was used for the measurement of high shear rate steady state shear viscosity and die entrance pressure losses; further, by the application of a converging flow method (Cogswell model) to these experimental results, elongational viscosity data were indirectly calculated. The extensional behaviour was directly investigated by means of melt spinning experiments, and data of apparent elongational viscosity were determined. The results evidenced that the presence of the organo-clay in filled PA6 melts modifies the rheological behaviour of the material, with respect to the unfilled polymer, in dependence on the type of flow experienced by the fluid. In shear flow, the nanocomposites showed a slightly lower viscosity than neat PA6, whereas in elongation, they appeared much more viscous, in dependence on the organo-clay content

A meta-model for aerodynamic properties of a reversible profile in cascade with variable stagger and solidity

In this paper, a systematic CFD work is carried out with the aim to inspect the influence of different cascade parameters on the aerodynamic performance of a reversible fan blade profile. From the obtained results, we derive a metamodel for the aerodynamic properties of this profile. Through RANS simulations of different arrangements in cascades, the aerodynamic performance of airfoils are analyzed as Reynolds number, solidity, pitch angle and angle of attack are varied. The definition of a trial matrix allows the reduction of the minimum number of simulations required. The computed CFD values of lift and drag coefficients, stall margin and the zero-lift angle strongly depend on cascade configuration and differ significantly from standard panel method software predictions. In this work, X-Foil has been used as a benchmark. Particularly, the high influence of pitch angle and solidity is here highlighted, while a less marked dependence from the Reynolds number has been found. Meta-models for lift and drag coefficients have been later derived, and an analysis of variance has improved the models by reducing the number of significant factors. The application of the meta-models to a quasi-3D in-house software for fan performance prediction is also shown. The effectiveness of the derived meta-models is proven through a spanwise comparison of a reversible fan with the X-Foil based and metamodel based versions of the software and 3D fields from a standard CFD simulation. The meta-model improves the software prediction capability, leading to a very low global overestimation of the specific work of the fan