Performance predictions for oil contaminated supercritical carbon dioxide gas cooling
Abstract
The international movement towards using natural refrigerants has resulted in the reinvestigation of trans-critical heat pump cycles using carbon dioxide. Subsequently, a need to predict the heat transfer of oil-contaminated supercritical carbon dioxide inside the gas cooler was identified. A literature survey revealed that numerous correlations exist for the calculation of the Nusselt number of supercritical carbon dioxide during cooling, but only a limited number of correlations that take the effects of oil contamination into consideration were found. The complexity of the heat transfer prediction was increased by the large variations in the physical and transport properties at the pseudocritical temperature, which became even more complex with the introduction of oil to the fluid. In this study, a correlation for calculating the Nusselt number of oil-contaminated supercritical carbon dioxide during cooling, was evaluated by comparing it to an independent published data set as well as to the results obtained by the authors' using their own data. It predicted 90% of the convection coefficients of the authors' data with an absolute error less than 20%, whilst only 39.7% of the coefficients were predicted for the independent data within this range. The oil concentrations in the independent data set was much higher than the oil percentages used to develop the correlation and might be the cause for the lower accuracy. It was concluded that this correlation's accuracy was not consistent between the two data sets. Based on this, a new correlation to improve on the performance consistency to predict the heat transfer in the gas cooler, whilst having a less complex form and not foregoing on accuracy, should then be investigated. Due to a limited number of existing correlations found for the cooling of oil-contaminated supercritical carbon dioxide, different correlations for oil-free conditions were then firstly investigated. Dittus & Boelter (1930) was the most accurate among the correlations and improved on the performance consistency of the published correlation for oil-contaminated conditions. It predicted 59.5% of the data from the published correlation' authors with an error less than 20% and 44.4% for the independent data. It was then decided to investigate the enhancement of Dittus & Boelter (1930) to take the effect of oil into account and further improving on the accuracy consistency. A new correlation was developed based on Dittus & Boelter and enhanced to take the effect of oil contamination into account. This correlation was developed using the independent data set, whilst keeping the data from the authors of the published correlation for oil contaminated supercritical carbon dioxide in cooling as a set for verification. Compared to Dittus & Boelter, the new correlation's accuracy was reported to be more consistent between the data sets. On the data from the published correlation's authors, it predicted 49.4% of the results with an error less than 20% and 47.1% for the independent data set. It was noted that Dittus & Boelter was more accurate at lower oil concentrations, such as in the data from the published correlation's authors, compared to the new correlations. However, when the oil increases to higher values (as in the independent data) Dittus & Boelter became inaccurate, whilst the new correlation was consistently accurate. In addition, this new correlation is less complex than the published correlation for oil-contaminated supercritical carbon dioxide in cooling. A more simplified correlation eases the calculation process and typically reduces the calculation times of large simulations. A less complex correlation is often also more applicable to a wider range of applications.
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