A generalized moving-boundary algorithm to predict the heat transfer rate of transcritical CO2 gas coolers. (October 2020)

• Record Type: Journal Article
• Authors: Bahman, Ammar M.; Ziviani, Davide; Groll, Eckhard A.
• Is Part Of: International journal of refrigeration. Volume 118(2020)
• Page Start: 491
• Page End: 503
• Publication Date: 2020-10
• Subjects: CO2 -- Transcritical -- Gas cooler -- Moving-boundary method -- Modeling -- Validation; CO2 -- Transcritique -- Refroidisseur de gaz -- Méthode de la frontière mobile -- Modélisation -- Validation; Refrigeration and refrigerating machinery -- Periodicals; 621.56
• DOI: 10.1016/j.ijrefrig.2020.05.021
• Languages: English
• ISSNs: 0140-7007

Abstract

Highlights: Generalized method presented to predict heat transfer rate and refrigerant temperature of transcritical gas coolers. Based on the moving-boundary approach to separate supercritical and supercritical liquid regions. New method shows higher accuracy in the predictions with extremely low computational efforts. New model presents improved predictions for micro-channel type gas coolers compared to fin-and tube ones. Source code of the method is provided in Python programming language as an appendix. Abstract: This paper presents the development of a CO2 gas cooler model using the moving-boundary (MB) method. The model aims to separate the gas cooler into two regions, supercritical and supercritical liquid, to predict the steady-state thermal heat transfer rate for air-type CO2 heat exchanger. The model uses the latest correlations for refrigerant and air-side heat transfer coefficients and pressure drops. The experimental results of fin-and-tube type and micro-channel type gas coolers were used for model validation. The mean absolute error (MAE) of the gas cooler heating capacity predictions was approximately 4%, while the predictions of the outlet temperature of the refrigerant side were within ± 3 K. The present MB model also showed an improved computational time of up to 10 times faster compared to a discretized model, which can reduce the overall computational effort in the simulation of detailed transcritical cycle model.