TY - JOUR
T1 - Evaluation of exergy destructions of different refrigerants in a vaccine cooling system with artificial intelligence
AU - Kahriman, Elif Altıntaş
AU - Gönül, Alişan
AU - Köse, Ali
AU - Parmaksızoğlu, İsmail Cem
N1 - Publisher Copyright:
Copyright © 2024 Inderscience Enterprises Ltd.
PY - 2024
Y1 - 2024
N2 - Nowadays, low-temperature storage and distribution of many vaccines are as important as their production. In this study, the performance of a storage device operating in a vapour compression refrigeration cycle designed to provide low-temperature cooling between 201 K and 275 K using R134a, R1234yf, R502, and R717 fluids is evaluated by both thermodynamic and artificial neural network (ANN) methods. Levenberg-Marquardt, Bayesian regularisation, and scaled conjugate gradient algorithms are compared with thermodynamical calculations to predict the energy efficiency and exergy destruction of the cooling system. All the considered artificial intelligence algorithms are found to accurately predict the expected outputs with R2 values greater than 0.9.
AB - Nowadays, low-temperature storage and distribution of many vaccines are as important as their production. In this study, the performance of a storage device operating in a vapour compression refrigeration cycle designed to provide low-temperature cooling between 201 K and 275 K using R134a, R1234yf, R502, and R717 fluids is evaluated by both thermodynamic and artificial neural network (ANN) methods. Levenberg-Marquardt, Bayesian regularisation, and scaled conjugate gradient algorithms are compared with thermodynamical calculations to predict the energy efficiency and exergy destruction of the cooling system. All the considered artificial intelligence algorithms are found to accurately predict the expected outputs with R2 values greater than 0.9.
KW - ANN
KW - artificial intelligence
KW - artificial neural network
KW - exergy analysis
KW - low temperature cooling
KW - vaccine storage unit
UR - http://www.scopus.com/inward/record.url?scp=85200229099&partnerID=8YFLogxK
U2 - 10.1504/IJEX.2024.140174
DO - 10.1504/IJEX.2024.140174
M3 - Article
AN - SCOPUS:85200229099
SN - 1742-8297
VL - 44
SP - 244
EP - 260
JO - International Journal of Exergy
JF - International Journal of Exergy
IS - 3-4
ER -