Artificial neural network analysis of heat pumps using refrigerant mixtures

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Küçük Resim

Tarih

2004

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Pergamon-Elsevier Science Ltd

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

In this study, we have investigated the performance of a vapor compression heat pump with different ratios of R12/R22 refrigerant mixtures using artificial neural networks (ANN). Experimental studies were completed to obtain training and test data. Mixing ratio, evaporator inlet temperature and condenser pressure were used as input layer, while the outputs are coefficient of performance (COP) and rational efficiency (RE). The back propagation learning algorithm with three different variants and logistic sigmoid transfer function were used in the network. It is shown that the R-2 values are about 0.9999 and the RMS errors are smaller than 0.006. With these results, we believe that the ANN can be used for prediction of COP and RE as an accurate method in a heat pump. (C) 2003 Elsevier Ltd. All rights reserved.

Açıklama

ARCAKLIOGLU, Erol/0000-0001-8073-5207

Anahtar Kelimeler

artificial neural networks, refrigerant mixture, coefficient of performance, heat pumps

Kaynak

Energy Conversion And Management

WoS Q Değeri

Q2

Scopus Q Değeri

Q1

Cilt

45

Sayı

11-12

Künye

closedAccess