Title: Experimental exergy analysis of low-GWP R290 refrigerant and derivation of exergetic performance equations with regression algorithms

Authors: Oguzhan Pektezel; Mehmet Das; Halil Ibrahim Acar

Addresses: Department of Mechanical Engineering, Faculty of Engineering and Architecture, Tokat Gaziosmanpasa University, Tokat, Türkiye ' Department of Mechatronics Engineering, Faculty of Engineering, Firat University, Elazig, Türkiye ' Department of Mechanical Engineering, Faculty of Engineering, Sivas Cumhuriyet University, Sivas, Türkiye

Abstract: This study analyses the derivation of performance equations for a refrigeration system operating with R290 and R404A refrigerants using different regression models. Results of pace regression for coefficient of performance (COP), second law efficiency, and total exergy destruction showed mean absolute error (MAE) are 0.0993, 0.0159, and 0.0066, respectively. In all cases, the pace regression model made better predictions than elastic net regression. It was concluded that predictions made with regression models showed a good agreement with the actual experimental results. The derived equations can be utilised for refrigerants working in similar operational ranges.

Keywords: exergy analysis; machine learning; equation derivation; GWP; R290; R404A.

DOI: 10.1504/IJEX.2023.130371

International Journal of Exergy, 2023 Vol.40 No.4, pp.467 - 482

Received: 15 Aug 2022
Received in revised form: 03 Nov 2022
Accepted: 03 Nov 2022
Published online: 18 Apr 2023 *

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