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STEAM CONDENER PERFOMANCE EVALIATION BYUSING NEURAL NETWORK
تقييم اداء مكثف بخاري بأستخدام الشبكة العصبية

Author: Hisham Hassan Jasim
Journal: Iraqi journal of mechanical and material engineering المجلة العراقية للهندسة الميكانيكية وهندسة المواد ISSN: 20761819 Year: 2012 Volume: 12 Issue: 2 Pages: 319-333
Publisher: Babylon University جامعة بابل

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Abstract

This work applied Artificial Neural Network (ANN) for performance evaluation of steam condensers which are widely used in power plants and refineries. Twocondensers were experimentally investigated. Experimental data was obtained by useunit steam power from G.U.N.T Company and industrial condenser operates in Durarefinery. The commonly used Back Propagation (BP) algorithm was used to train andtest network. Input of neural network include inlet water temperature, water flow rate,steam temperature and enthalpy difference. The exit water temperature representedoutput of the neural network. The maximum deviation between the predicted resultsand experimental data was less than 1%. It is recommended the (ANN) can be used topredicate the performance of thermal system in engineering applications, such asmodeling condenser for heat transfer analysis. Afterwards, ANN resulted used to findthermal parameters (convection heat transfer coefficient of water side and steamflow rate ) based on software program built by Matlab language. Comparing the resulted from modeling with experimental data reveals a good agreement (-3% to3%). smhw

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