Numerical simulation of drop impact and jet buckling problems using the eXtended Pom-Pom model

This work presents numerical simulations of two fluid flow problems involving moving free surfaces: the impacting drop and fluid jet buckling. The viscoelastic model used in these simulations is the eXtended Pom-Pom (XPP) model. To validate the code, numerical predictions of the drop impact problem for Newtonian and Oldroyd-B fluids are presented and compared with other methods. In particular, a benchmark on numerical simulations for a XPP drop impacting on a rigid plate is performed for a wide range of the relevant parameters. Finally, to provide an additional application of free surface flows of XPP fluids, the viscous jet buckling problem is simulated and discussed. (C) 2011 Elsevier B.V. All rights reserved.

A New Method to Predict the Epidemiology of Fungal Keratitis by Monitoring the Sales Distribution of Antifungal Eye Drops in Brazil

Purpose: Fungi are a major cause of keratitis, although few medications are licensed for their treatment. The aim of this study is to observe the variation in commercialisation of antifungal eye drops, and to predict the seasonal distribution of fungal keratitis in Brazil. Methods: Data from a retrospective study of antifungal eye drops sales from the only pharmaceutical ophthalmologic laboratory, authorized to dispense them in Brazil (Opthalmos) were gathered. These data were correlated with geographic and seasonal distribution of fungal keratitis in Brazil between July 2002 and June 2008. Results: A total of 26,087 antifungal eye drop units were sold, with a mean of 2.3 per patient. There was significant variation in antifungal sales during the year (p < 0.01). A linear regression model displayed a significant association between reduced relative humidity and antifungal drug sales (R-2 = 0.17, p < 0.01). Conclusions: Antifungal eye drops sales suggest that there is a seasonal distribution of fungal keratitis. A possible interpretation is that the third quarter of the year (a period when the climate is drier), when agricultural activity is more intense in Brazil, suggests a correlation with a higher incidence of fungal keratitis. A similar model could be applied to other diseases, that are managed with unique, or few, and monitorable medications to predict epidemiological aspects.

Two-phase flow patterns and pressure drop inside horizontal tubes containing twisted-tape inserts

This paper presents an experimental study on two-phase flow patterns and pressure drop of R134a inside a 15.9 mm ID tube containing twisted-tape inserts. Experimental results were obtained in a horizontal test section for twisted-tape ratios of 3, 4, 9 and 14, mass velocities ranging from 75 to 250 kg/m(2) s and saturation temperatures of 5 and 15 degrees C. An unprecedented discussion on two-phase flow patterns inside tubes containing twisted-tape inserts is presented and the flow pattern effects on the frictional pressure drop are carefully discussed. Additionally, a new method to predict the frictional pressure drop during two-phase flow inside tubes containing twisted-tape inserts is proposed. (C) 2012 Elsevier Ltd. All rights reserved.

Two-Phase Frictional Pressure Drop and Flow Boiling Heat Transfer for R245fa in a 2.32-mm Tube

Experimental two-phase frictional pressure drop and flow boiling heat transfer results are presented for a horizontal 2.32-mm ID stainless-steel tube using R245fa as working fluid. The frictional pressure drop data was obtained under adiabatic and diabatic conditions. Experiments were performed for mass velocities ranging from 100 to 700 kg m−2 s−1 , heat flux from 0 to 55 kW m−2 , exit saturation temperatures of 31 and 41◦C, and vapor qualities from 0.10 to 0.99. Pressures drop gradients and heat transfer coefficients ranging from 1 to 70 kPa m−1 and from 1 to 7 kW m−2 K−1 were measured. It was found that the heat transfer coefficient is a strong function of the heat flux, mass velocity, and vapor quality. Five frictional pressure drop predictive methods were compared against the experimental database. The Cioncolini et al. (2009) method was found to work the best. Six flow boiling heat transfer predictive methods were also compared against the present database. Liu and Winterton (1991), Zhang et al. (2004), and Saitoh et al. (2007) were ranked as the best methods. They predicted the experimental flow boiling heat transfer data with an average error around 19%.