Performance prediction for non-adiabatic capillary tube suction line heat exchanger: an artificial neural network approach


Islamoglu Y., Kurt A., Parmaksizoglu C.

ENERGY CONVERSION AND MANAGEMENT, vol.46, pp.223-232, 2005 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 46 Issue: 2
  • Publication Date: 2005
  • Doi Number: 10.1016/j.enconman.2004.02.015
  • Title of Journal : ENERGY CONVERSION AND MANAGEMENT
  • Page Numbers: pp.223-232

Abstract

This study presents an application of the artificial neural network (ANN) model using the back propagation (BP) learning algorithm to predict the performance (suction line outlet temperature and mass flow rate) of a non-adiabatic capillary tube suction line heat exchanger, basically used as a throttling device in small household refrigeration systems. Comparative studies were made by using an ANN model, experimental results and correlations to predict the performance. These studies showed that the proposed approach could successfully be used for performance prediction for the exchanger. (C) 2004 Elsevier Ltd. All rights reserved.