Optimum loss models for performance prediction of supercritical CO2 centrifugal compressor
•The paper provides additional test data of S-CO2 centrifugal compressor performances.•The best set of loss models for the supercritical CO2 compressor design is proposed.•The predicted results show good agreement with all experimental data. Due to the lack of test data of a supercritical CO2 compre...
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Veröffentlicht in: | Applied thermal engineering 2021-02, Vol.184, p.116255, Article 116255 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •The paper provides additional test data of S-CO2 centrifugal compressor performances.•The best set of loss models for the supercritical CO2 compressor design is proposed.•The predicted results show good agreement with all experimental data.
Due to the lack of test data of a supercritical CO2 compressor operating under supercritical CO2 conditions, the work of loss model validation for supercritical CO2 compressor could not be conducted successfully before. Therefore, as the first step, this study gathers the existing accessible experiment data as much as possible while conducting additional supercritical CO2 compressor performance experiments to validate the loss models for the supercritical CO2 compressor. To evaluate the reliability of test results, the measurement uncertainty is estimated from the experiment data. Then, three different combinations of loss models based on the mean streamline method are compared with six available experimental cases to find the most suitable combination of loss models for the supercritical CO2 compressor design and analysis. The combination of loss models proposed by Lee was found to predict pressure ratio and isentropic efficiency of supercritical CO2 compressors operating both on-design and off-design conditions successfully. It is expected that the set of loss models presented herein can be utilized as a conceptual design tool in the preliminary design stage of supercritical CO2 compressors. |
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ISSN: | 1359-4311 1873-5606 |
DOI: | 10.1016/j.applthermaleng.2020.116255 |