A novel numerical methodology for modelling simple vapour compression refrigeration system. (25th March 2017)

• Record Type: Journal Article
• Authors: Zsembinszki, Gabriel; de Gracia, Alvaro; Moreno, Pere; Rovira, Ricard; Ángel González, Miguel; Cabeza, Luisa F.
• Is Part Of: Applied thermal engineering. Volume 115(2017)
• Page Start: 188
• Page End: 200
• Publication Date: 2017-03-25
• Subjects: Numerical simulation -- Compression refrigeration system -- Experimental validation; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2016.12.059
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: Modelling of a steady-state simple vapour mechanical compression refrigeration system. Empirical correlations for some of the system components are determined. System-dependent methodology that can be adapted to any similar refrigeration systems. Model validation using experimental data in a walk-in freezer, achieving good accuracy of the predictions. The methodology can be applied for the detection of system malfunctions. Abstract: The extended use of cooling and refrigeration systems in industrial, building and transport sectors may have a negative impact on the climate change and ozone depletion. Thus, important aspects related to these systems, such as refrigerant charge level, malfunction, or refrigerant leakage, must be taken into account. In this sense, the study of refrigeration system performance under different conditions can be very useful. In this paper, a novel methodology for modelling a simple compression refrigeration system is described. Starting from three input parameters, i.e. the ambient air temperature, the cold room air temperature, and the degree of superheating, a calculation algorithm based on iterative loops is used in the model to determine the operating point of the system. An experimental set-up consisting of a walk-in freezer unit was used for the development and validation of the model. The model is system dependent, i.e. empirical correlations must be derived for determining some of the features of system components. The numerical results are in good agreement with the experiment, therefore the model can be a reliable tool for the detection of a system malfunction.