A different approach for the analysis of a double-effect sorption refrigeration system operating with LiBr + LiNO 3 + LiI + LiCl / H 2O LiBr + LiNO 3 + LiI + LiCl / H 2O i̇le çalişan çi̇ft etki̇li̇ bi̇r soǧurmali soǧutma si̇stemi̇ni̇n anali̇i̇ i̇çi̇n farkli bi̇r yaklaşim

ŞENCAN ŞAHİN A.

Journal of the Faculty of Engineering and Architecture of Gazi University, cilt.21, sa.3, ss.467-472, 2006 (Scopus, TRDizin) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 21 Sayı: 3
  • Basım Tarihi: 2006
  • Dergi Adı: Journal of the Faculty of Engineering and Architecture of Gazi University
  • Derginin Tarandığı İndeksler: Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.467-472
  • Anahtar Kelimeler: Artificial neural network, COP, LiBr, LiCl, LiNO 3,iI, Sorption, Thermodynamic properties
  • Isparta Uygulamalı Bilimler Üniversitesi Adresli: Hayır

Özet

Thermodynamic analysis of the sorption refrigeration systems is too complex because of analytic functions calculating thermodynamic properties of fluid couples. This paper presents a new approach to performance analysis of double-effect sorption refrigeration systems. Fluid couple LiBr + LiNO 3+ LiI+ LiCl / H 2O (mole ratio LiBr:LiNO:LiI:LiCl = 5:1:1:2, respectively) which do not cause ozone depletion in the system was used. The Coefficient of Performance (COP) of system depending on evaporator, absorber, condenser and generator temperatures was predicted with Artificial Neural Network (ANN) model. The back-propagation learning algorithm with two different variants and logistic sigmoid transfer function were used in the ANN. In order to train the neural network, limited literature data were used. In order to determine COP of system, a new formulation was derived by very well trained ANN model (R 2=0,9939) in the study.