4.5 Article

A new design method for two-phase nozzles in high efficiency heat pumps

Journal

INTERNATIONAL JOURNAL OF REFRIGERATION
Volume 127, Issue -, Pages 148-156

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.ijrefrig.2021.02.023

Keywords

Nozzle design; Two-phase; Critical value; Slip velocity; Turbine

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In this paper, an industrially established 1D model for two-phase nozzles design and analysis has been extended and validated with a wider range of experimental data, focusing on single-component two-phase fluid expansion. The upgraded model has shown accurate results under subcritical conditions (Ma < 1) in the converging nozzle tests.
In this paper an industrially established 1D model for two-phase nozzles design and analysis (Elliott, 1968) has been extended and validated with a wider range of experimental data, focusing on single component two-phase fluid expansion from initial quality in the 0%-25% range. The Authors focused on the correlations of the gas-liquid slip velocity and wall friction for two-flow regimes. The upgraded model has been tested on a converging nozzle showing accurate results under subcritical conditions (Ma < 1). Furthermore, simulations have also been carried out on a convergent-divergent nozzle, concentrating on the diverging part at Ma > 1, demonstrating that the new model obtained a significant reduction in error compared to the original Elliott model and to the well-known isentropic homogeneous approach (IHE). The extended model was also tested on a convergent-divergent nozzle produced by Carrier Corporation for the 19-XRT chiller, obtaining a satisfactory performance prediction. The validation process allowed to assess the limits of validity of the new model, which can be effectively used as design tool for subsonic or supersonic two-phase nozzles. In particular, the model capability to identify critical mass flow and critical expansion ratio has been investigated, showing good match for the critical expansion ratio, while margins of improvement remain for the critical mass flow prediction. (c) 2021 Elsevier Ltd and IIR. All rights reserved.

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