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A modeling study for prediction of oil retention in compressor suction lines is presented in this article. A new flow-pattern-based analytical model called the double-circle model (DCM) was developed to evaluate the oil retention amount in suction lines. A new consolidated oil retention database was established to develop interfacial friction factor correlation. Parametric study was conducted by means of force balance analysis to determine the influence factors of oil transport. The DCM and parametric study were validated by the database, and the results showed that they display reliable accuracy. Finally, a hybrid artificial neural network (ANN) approach was proposed, which used the DCM and parametric study to produce extrapolation data and determine the input parameters, respectively. The hybrid ANN was optimized for the 6-13-1 configuration with logarithmic sigmoid (logsig) transfer function and the Lavenberg–Marquardt (L-M) algorithm. The hybrid ANN model prediction yields a mean relative error (MRE) and R2 of 6.25% and 96.86%, respectively. [ABSTRACT FROM AUTHOR]

• Three different models were developed to predict the oil retention amount in suction line. • Double circle model was proposed to describe the interface behavior of stratified-wavy flow and annular flow. • New correlations of interfacial friction factor and void fraction were established. • The flow-pattern based method displayed MAE of 9.35% and captured 87.83% of data within ±20% deviation. • Two models were utilized to evaluate minimum refrigerant mass flux, which guarantee that oil can successfully return back to compressor. Modeling study for predictions of oil retention and critical refrigerant mass flux in compressor suction line was presented in the current work. Three approaches were developed for prediction of oil retention amount in suction line, namely, annular flow model, flow-pattern based method and empirical void fraction model. The annular flow model assumed that annular flow exists as the flow pattern, while the flow-pattern based method described the flow behavior of refrigerant/oil mixture by the flow pattern classifications and double circle model. Based on the proposed models, new correlations of interfacial friction factor and void fraction were established. The experimental data for R32 with coexistence oil PVE68 inside horizontal, vertical and inclined suction lines were used as the foundation and validation of the models. The results showed that all the models display satisfying prediction for oil retention. The flow-pattern based method exhibited the best results, which yielded the mean absolute deviation of 9.35% and captured 87.83% of the data within ±20% error bands. Moreover, two models for prediction of minimum refrigerant mass flux were recommended in order to ensure successful oil return. These models could serve as tools for operation optimization incorporating the lubricant oil effect. [ABSTRACT FROM AUTHOR]