Investigation of thermodynamic properties of refrigerant/absorbent couples using artificial neural networks
Yükleniyor...
Tarih
2004
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Science Sa
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper presents a new approach to determine the properties of liquid and two phase boiling and condensing of two alternative refrigerant/absorbent couples (methanol-LiBr and methanol-LiCl), which do not cause ozone depletion for absorption thermal systems (ATSs) using artificial neural networks (ANNs). The back-propagation learning algorithm with three different variants and logistic sigmoid transfer function were used in the network. In order to train the neural network, limited experimental measurements were used as training and test data. In input layer, there are temperatures in the range of 298-498 K (with 25 K increase), pressures (0.1-40 MPa) and concentrations of 2, 7, and 12% of the couples; specific volume is in output layer. After training, it is found that maximum error is less than 3%, average error is about 1% and R-2 values are 99.999%. As seen from the results obtained the thermodynamic properties have been obviously predicted within acceptable errors. This paper shows that values predicted with ANN can be used to define the thermodynamic properties instead of approximate and complex analytic equations. (C) 2004 Elsevier B.V. All rights reserved.
Açıklama
ARCAKLIOGLU, Erol/0000-0001-8073-5207
Anahtar Kelimeler
artificial neural network, thermodynamic properties, ozone safe refrigerants, methanol-liar, methanol-LiCl
Kaynak
Chemical Engineering And Processing-Process Intensification
WoS Q Değeri
N/A
Scopus Q Değeri
Q1
Cilt
43
Sayı
10
Künye
closedAccess
