Generalized Pressure Drop Correlation for Evaporation and Condensation in Smooth and Micro-Fin Tubes

Published

October 1, 2001

Author(s)

J Y. Choi, Mark A. Kedzierski, Piotr A. Domanski

Abstract

This paper presents a pressure drop correlation for evaporation and condensation in smooth and micro-fin tubes. The correlation was developed from a data base consisting of the following pure and mixed refrigerants: R125, R134a, R32, R410A (R32/R125 50/50 % mass), R22, R407C (R32/R125/R134a, 23/25/52 % mass) and R32/R134a (25/75 % mass). The new correlation was obtained by replacing the friction factor and the tube-diameter in Bo Pierre correlation with a friction factor derived from pressure drop data for a micro-fin tube and the hydraulic diameter, respectively. The new correlation predicted the measured micro-fin data to within a mean deviation of 10.8%, and it also predicted the pressure drop in smooth tube to within a mean deviation of 15.0%. In addition, the correlation was used to predict pressure drop data for refrigerant/lubricant mixtures by using a viscosity mixing rule. As a result, the new correlation predicted the measured evaporation and condensation pressure drop data for mixtures of various lubricants with R12, R22, and R134a to within a mean deviation of 19.0%.

Proceedings Title

Proceedings of the International Institute of Refrigeration (IIR). Thermophysical Properties and Transfer Processes of New Refrigerants.

Conference Dates

October 2-5, 2001

Conference Location

Paderborn, 1, GE

Conference Title

International Institute of Refrigeration

Pub Type

Conferences

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Keywords

alternative refrigerants, correlation, friction factor, hydraulic diameter, micro-fin tube, smooth tube, two-phase

Citation

Choi, J. , Kedzierski, M. and Domanski, P. (2001), Generalized Pressure Drop Correlation for Evaporation and Condensation in Smooth and Micro-Fin Tubes, Proceedings of the International Institute of Refrigeration (IIR). Thermophysical Properties and Transfer Processes of New Refrigerants., Paderborn, 1, GE, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=860849 (Accessed October 17, 2025)