Exergy analysis of an ejector-absorption heat transformer using artificial neural network approach
Yükleniyor...
Tarih
2007
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Pergamon-Elsevier Science Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper proposes artificial neural networks (ANNs) technique as a new approach to determine the exergy losses of an ejector-absorption heat transformer (EAHT). Thermodynamic analysis of the EAHT is too complex due to complex differential equations and complex simulations programs. ANN technique facilitates these complicated situations. This study is considered to be helpful in predicting the exergetic performance of components of an EAHT prior to its setting up in a thermal system where the working temperatures are known. The best approach was investigated using different algorithms with developed software. The best statistical coefficient of multiple determinations (R-2-value) for training data equals to 0.999715, 0.995627, 0.999497, and 0.997648 obtained by different algorithms with seven neurons for the non-dimensional exergy losses of evaporator, generator, absorber and condenser, respectively. Similarly these values for testing data are 0.999774, 0.994039, 0.999613 and 0.99938, respectively. The results show that this approach has the advantages of computational speed, low cost for feasibility, rapid turnaround, which is especially important during iterative design phases, and easy of design by operators with little technical experience. (c) 2006 Elsevier Ltd. All rights reserved.
Açıklama
ARCAKLIOGLU, Erol/0000-0001-8073-5207;
Anahtar Kelimeler
absorption, heat transformer, simulation, solar pond, ejector, artificial neural network
Kaynak
Applied Thermal Engineering
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
27
Sayı
2-3
Künye
closedAccess
