The Performance Prediction of The Mixed Convection In an Inclined Circular Tube Filled Porous Media Based on an Intelligent Control

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Musa Mustafa Weis

Abstract

The porous media has a significant impact on the heat transfer and storage properties. The present study focuses on the heat transfer of the mixed convection through a circular tube that filled with a porous media at different angles using a neural network. An experiment had been performed for the Rayleigh number range from 108.54 to 907.73 and the Peclet number range 30.3.-510 using three tests for the heat flux. The result shows the mean relative error about 7.913% and the coloration coefficient (R2) Is 99.18% for the train data. The mean relative error about 6.641% and the R2 is 99.46%, for the test data. The results showed that effectiveness of ANN in the predicted thermal performance in thermal engineering applications such as heat transfer modeling using porous media with airflow.

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