The performance prediction of the mixed convection in an inclined circular tube filled porous media based on an intelligent control

الملخص EN

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 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.