1,721,057 research outputs found
Tempo e poesia in "Cronache e paràbbule" di Nicola G. De Donno
No full textLa poesia dialettale di Nicola G. De Donno trova in 'Cronache e parabbule' la sua espressione universale, che da fattore episodico si eleva a sentimento del tempo in energica tempra morale
A new scaled equation to calculate the surface tension of ketones
No full textThis work presents a new formula to calculate the surface tension of ketones. As a first step, an analysis of the available data of the experimental surface tension data for ketones was made. Experimental data were collected for the following pure fluids: acetone, 2-butanone, 2-pentanone, 3-pentanone, 2-hexanone, 3-heptanone, 4-heptanone, 2-octanone, and 6-undecanone. The data were then regressed with the most reliable semi-empirical correlation methods in the literature based on the corresponding states theory. The final equation proposed is very simple and gives noticeable improvement with respect to existing equations. © 2013 Akadémiai Kiadó, Budapest, Hungary
Saturated pressure and vapor-phase pvT measurements of 1,1-difluoroethene (R1132a)
No full textThis work presents 24 vapor pressures and 131 vapor-phase pvT properties for 1,1-difluoroethene (R1132a) measured using an isochoric apparatus. This fluid is a hydrofluoroolefin with a GWP less than 3 and it is considered to be a potential component for low-GWP refrigerant mixtures for ultralow temperature applications. The saturated pressure data were obtained in the temperature range from (223.15 to 280.65) K and pressure range from (0.471 to 2.675) MPa. The vapor-phase pvT measurements were performed in the temperature range from (223.15 to 303.15) K, pressure range from (0.312 to 2.340) MPa, and specific volume range from (0.013226 to 0.086770) m3 kg−1. The saturated pressure data were compared with the experimental values available in literature and fitted to extended Antoine-type and Wagner-type vapor-pressure correlations. The vapor-phase pvT data were compared with the values available in literature. In addition, the pvT properties were used to develop a truncated virial equation of state
Thermal conductivity of nanofluids: A review of the existing correlations and a scaled semi-empirical equation
No full textEfficiency of energy systems can be improved in different ways. One of these consists in adopting heat transfer fluids with better thermo-physical properties, e.g. thermal conductivity and dynamic viscosity, which can improve convective heat transfer coefficient. Being mixtures of high-conductive nanoparticles and common base fluids, nanofluids have the potential to increase the efficiency of a large number of energy systems. Thus, great importance should be dedicated to a correct and reliable estimation of the thermophysical properties of these fluids. In this work, the thermal conductivity of 11 nanofluids, for a total of 239 experimental points, was analyzed in detail: 7 nanofluids have water as base fluid (Ag, Al2O3, CuO, Fe2O3, SiO2, TiO2, ZnO), while 4 nanofluids have ethylene glycol (Al2O3, CuO, SiC and SnO2). All nanofluids’ thermal conductivity data derive from experimental measurements available in literature, carried out with samples characterized by stable preparation methods. The thermal conductivity of the nanofluids was estimated with 13 well-known correlations, in order to verify their accuracy. A new semi-empirical, scaled equation for predicting the thermal conductivity of nanofluids was also proposed. The equation requires the use of six parameters (volume fraction, temperature, base fluid critical temperature, nanoparticle diameter, nanoparticle thermal conductivity, base fluid thermal conductivity) and shows small deviations respect to the experimental data, having an average absolute relative deviation of 2.60%. This value was found to be the lowest among the other studied correlations. The study also highlights some issues and limitations that the research field related to nanofluids should overcome
Modeling investigation on the viscosity of pure refrigerants and their liquid mixtures by using the Patel–Teja viscosity equation of state|Modélisation de la viscosité des frigorigènes purs et leurs mélanges liquides à l'aide de l’équation d’état de Patel-Teja
No full textA viscosity model based on the Patel–Teja equation of state has been applied to pure refrigerants and their liquid mixtures. 7490 data points, containing 6481 points for pure refrigerants and 1009 points for binary, ternary and quaternary mixtures, have been used. First, 29 pure refrigerants are selected and the pure-component parameters of the model are then fitted. Subsequently, seven binary mixtures have been used to regress the binary interaction parameters of the model. The resulting binary interaction parameters and pure-component parameters are then used to predict the viscosity of two ternary and one quaternary mixtures. The results show that deviations are generally low for all analyzed compounds and mixtures. (Overall AADs% are 7.44 for pure compounds, 3.37 for binary mixtures, 3.77 for ternary mixtures and 3.36 for a quaternary mixture). This model does not require the property of density, which is one of its main advantages. © 2017 Elsevier Ltd and II
Semi-empirical correlations and an artificial neural network for liquid dynamic viscosity of low GWP refrigerants
Full text linkn this work, simple semi-empirical correlations to describe the temperature and the pressure dependence of the dynamic viscosity of low GWP refrigerants, namely HydroFluoroOlefins (HFOs) and HydroChloroFluoroOlefins (HCFOs), in the liquid phase are presented. Firstly, the experimental liquid dynamic viscosity data available in scientific literature and databases were collected and statistically analyzed. From the data collected for low pressures, the Latini et al. (2002, 1990) correlation for the dynamic viscosity of liquid refrigerants in saturated conditions was re-fitted and constants expressly dedicated to the studied low GWP refrigerants were obtained. Then, the proposed temperature-dependent correlation was modified to represent liquid dynamic viscosity dependence on pressure. In addition, an artificial neural network was developed to predict the dependence of the liquid viscosity of the studied refrigerants on temperature and pressure. This model was trained, validated, and tested for the selected dataset. The results of the proposed correlations and the multi-layer perceptron neural network were compared with the liquid viscosity calculations provided by some of the most well-known literature correlations and REFPROP 10.0, proving the accuracy of the proposed models for engineering applications
Surface tension prediction for refrigerant binary systems
No full textThis work presents a literature survey of the available data of the experimental surface tension data for refrigerant binary systems. The experimental data were collected for the following binary systems: R32-R227ea, R32-R125, R32-R134a, R290-R32, R125-R152a, R290-R152a, R290-R600a, RE170-R290, R143a-R134a, R125-R134a, R125-R143a, R134a-R152a and R143a + R227ea. Two recently proposed equations for the prediction of the surface tension of pure fluids were evaluated for their abilities to predict the surface tension of binary systems. A new equation for the prediction of the surface tension of refrigerant binary systems based on the Corresponding States Principle theory is proposed. © 2012 Elsevier Ltd and IIR. All rights reserved
Correlations for liquid thermal conductivity of low GWP refrigerants in the reduced temperature range 0.4 to 0.9 from saturation line to 70 MPa
Full text linkThis paper presents a literature survey of the experimental thermal conductivity data for environmentally friendly refrigerants, namely HydroFluoroOlefins (HFOs) and HydroChloroFluoroOlefins (HCFOs), in the liquid phase. A total of 2073 experimental data for six alternative refrigerants, i.e. R1233zd(E), R1234yf, R1234ze(E), R1234ze(Z), R1224yd(Z), and R1336mzz(Z), was collected in the temperature range from 203.18 K to 434.99 K and in the pressure range from 0.10 MPa to 66.62 MPa. Literature correlations not considering the pressure dependence were compared for reduced pressures lower than 1. Di Nicola et al. (2014a) correlation was re-fitted and new coefficients expressly dedicated to low global warming potential refrigerants were given. The proposed equation gives an overall deviation of 1.78% for the data measured at reduced pressure up to 1. The liquid thermal conductivity dependence on pressure was also considered adding new terms on Di Nicola et al. (2014a) correlation and on Latini and Sotte (2012) correlation. The proposed equations give overall deviation of 1.45% and 1.99%, respectively, for the complete dataset
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