Modeling of lubricant retention in suction lines with R32/PVE oil mixture
•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-patte...
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Veröffentlicht in: | International journal of refrigeration 2022-02, Vol.134, p.146-158 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •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. |
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ISSN: | 0140-7007 1879-2081 |
DOI: | 10.1016/j.ijrefrig.2021.11.010 |