Refrigerant desorption and foaming in mixtures of HFC-134a and HFO-1234yf and a polyol ester lubricating oil

This paper presents a study of refrigerant desorption leading to foam formation in refrigerant-oil mixtures undergoing controlled depressurization. An experimental apparatus was designed and constructed to allow measurements of the depressurization rate, foam height and refrigerant gas mass flux resulting from expansion and desorption from a saturated liquid mixture. Quantitative data and high-speed video analyses were used to identify the main physical mechanisms in the foaming process, namely, bubble cavitation and growth, foam growth and foam decay. The experimental results for the maximum foam height, foam lifetime and liquid supersaturation during desorption were explored as a function of the overall initial refrigerant mass fraction and system temperature. A mathematical model based on integral mass balances was proposed and compared with the experimental data with deviations smaller than 20%.     

Thermodynamic properties of 1,1,1,2-tetrafluoroethane (R-134a) + 2,3,3,3-tetrafluoropropene (R-1234yf) mixtures: Measurements of the critical parameters and a mixture model based on the multi-fluid approximation

Thermodynamic properties are discussed for 1,1,1,2-tetrafluoroethane (R-134a) + 2,3,3,3-tetrafluoropropene (R-1234yf) mixtures. The critical temperatures, densities, and pressures experimentally determined are first presented with their uncertainties. Subsequently a mixture model for calculations of thermodynamic properties is formulated using the multi-fluid approximation. Comparisons to experimental data show that the mixture model calculates the vapor–liquid equilibrium and densities of the mixtures with reasonable accuracies. The critical parameters are also well represented by the mixture model.     

Development and validation of a micro-fin tubes evaporator model using R134a and R1234yf as working fluids

This paper presents a model of shell and tube evaporator with micro-fin tubes using R1234yf and R134a. The model developed for this evaporator uses the ε-NTU method to predict the evaporating pressure, the refrigerant outlet enthalpy and the outlet temperature of the secondary fluid. The model accuracy is evaluated using different two-phase flow boiling correlations for micro-fin tubes and comparing predicted and experimental data. The experimental tests were carried out for a wide range of operating conditions using R134a and R1234yf as working fluids. The predicted parameter with maximum deviations, between the predicted and experimental data, is the evaporating pressure. The correlation of Akhavan– Behabadi et al. was used to predict flow boiling heat transfer, with an error on cooling capacity prediction below 5%. Simulations, carried out with this validated model, show that the overall heat transfer coefficient of R1234yf has a maximum decrease of 10% compared with R134a.     

Solubility, density and viscosity of a mixture of R-600a and polyol ester oil

Experimental data on solubility, liquid phase density and viscosity of a mixture of R-600a and a POE ISO 7 lubricant oil are presented. A specially designed experimental facility for simultaneous measurements of the physical properties was used in the experiments at temperatures ranging from 10 to 60 °C. The VLE data were correlated with the Heil–Prausnitz and Flory–Huggins activity models and the Peng–Robinson equation of state (EoS). Liquid density was correlated with the Peng–Robinson EoS and with a first-order Redlich–Kister expansion for the excess molar volume. Liquid viscosity was correlated with an excess-property approach based on the classical Eyring liquid viscosity model. Satisfactory agreement was obtained between models and experiments; maximum root mean square (RMS) deviations of models used in the VLE, density and viscosity predictions were 1.1% (VLE EoS), 0.2% (Redlich–Kister) and 3.0% (Grunberg–Nissan), respectively.     

A proposed combination model for predicting surface tension and surface properties of binary refrigerant mixtures

A combination model is proposed to describe the surface tension and surface properties of binary refrigerant mixtures combining the Laaksonen and Kulmala equation with the phase equilibrium between the bulk liquid and surface phases to predict the surface tension, surface composition and surface mole density of the binary refrigerant mixtures. Also, the present model is combined with the volume-translated Peng–Robinson (VTPR) equation of state to describe the fugacity coefficients of the components and molar volumes of the bulk and surface phases. This proposed combination model is subsequently applied for 13 binary refrigerant mixtures and compared with the gradient theory. The results of this model show that the surface tensions predicted by this model agree well with experimental data for these mixtures (overall AAD ∼4.35). Compared with the gradient theory (overall AAD ∼5.67 and 3.94 for density and temperature dependant influence parameter), the proposed combination model performs well.     

Effect of concentration on R134a/Al2O3 nanolubricant mixture boiling on a reentrant cavity surface

This paper quantifies the influence of Al₂O₃ nanoparticles on the pool boiling performance of R134a/polyolester mixtures on a Turbo-BII-HP boiling surface. Nanolubricants with 10 nm diameter Al₂O₃ nanoparticles of various volume fractions (1.6%, 2.3%, and 5.1%) in the base polyolester lubricant were mixed with R134a at two different mass fractions (0.5% and 1%). The study showed that nanolubricants can improve R134a boiling on a reentrant cavity surface as long as the nanoparticles remain well dispersed in the lubricant and are at sufficiently large concentration. For example, three of the refrigerant/nanolubricant mixtures with the smallest nanoparticle mass fraction exhibited average enhancements over the entire heat flux range of approximately 10%. However, when the nanoparticle mass fraction was increased to a point that likely encouraged agglomeration, an average heat transfer degradation of approximately 14% resulted. An existing model was used to predict the boiling heat transfer.