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Numerical assessment of critical properties of nanofluids: Applications to nanorefrigerants and nanolubricants

In recent years, researchers have proposed the use of nanoparticles suspended in the working fluid (nanorefrigerants) of vapour compression refrigeration cycles so as to increase the efficiency of the system. It takes a number of variables, notably, operational parameters and thermophysical properti...

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Bibliographic Details
Published in:Journal of molecular liquids 2020-11, Vol.318, p.113938, Article 113938
Main Authors: Sanson Portella Carvalho, José Eduardo, Ortega Sotomayor, Paul, Reis Parise, José Alberto, Pradelle, Florian
Format: Article
Language:English
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Summary:In recent years, researchers have proposed the use of nanoparticles suspended in the working fluid (nanorefrigerants) of vapour compression refrigeration cycles so as to increase the efficiency of the system. It takes a number of variables, notably, operational parameters and thermophysical properties to make such a system to work with an advantageous performance. In this regard, near-critical properties of nanorefrigerants are of particular importance, yet they are scarce in the literature. The aim of this study is to investigate models that predict the critical temperature and density of nanorefrigerants, based on the isomorphism (corresponding states) principle. These variables were estimated using two correlations available in the literature and a third one, proposed here. As there are no experimental data to validate the model, its robustness was assessed by means of its ability to recover the properties of the base fluid (F) from critical properties of the nanofluid (N). This path is defined as N-F method, which is carried out after assessing the impact of the nanoparticles on these two parameters by isomorphism of the base fluid behaviour, named F-N method. Thermophysical properties of the base fluids were calculated using REFPROP (NIST Reference Fluid Thermodynamic and Transport Properties Database) and model calculations were performed with computing platform Matlab. The best of the three models was defined after studying data from R717, R744 and R600a mixed with seven different nanoparticle materials in the range of 1 to 5% in volume basis. Then, refrigerants R744, R410A, R134a, and R1234ze were mixed with CNT, diamond and zinc oxide nanoparticles with concentrations ranging from 1 to 5% in volume basis to study the sensitivity of the model to the saturation lines (liquid or vapour and bubble or dew points lines for nonazeotropic refrigerant mixtures) and nanoparticles' content. Results have shown that data from the liquid lines should be used, since the use of the vapour saturation line results in overestimated values of the critical parameters. Such behaviour was intensified with the nanoparticle density. A maximum concentration around 2% of nanoparticles is also suggested to guaranty the highest robustness of the model. The proposed method showed the departure of the critical parameters as a function of the quantity of carbon for linear alkanes. The shift of the critical parameters seems to have a linear relation for both the number of carbons
ISSN:0167-7322
1873-3166
DOI:10.1016/j.molliq.2020.113938