Estimation of Magnetic Field Intensity for the Magnetic Packed Beds Using Artificial Neural Networks

T. Abbasov; M. Yuceer; Z. Yildiz

doi:10.15866/irephy.v11i2.12592

Estimation of Magnetic Field Intensity for the Magnetic Packed Beds Using Artificial Neural Networks

T. Abbasov^(1*), M. Yuceer⁽²⁾, Z. Yildiz⁽³⁾

^(*) Corresponding author

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Abstract

Magnetizing properties of the packed beds that are constructed from the stainless steel balls of various sizes are investigated in order to determine the effect of packing fraction factor, filter length, magnetic strength and diameter of the ball on the magnetizing properties of the bed. In this study, we have investigated the effect of the volumetric packing factor on the magnetizing properties of the magnetic packed bed using artificial neural networks. An ANN model was developed to predict the magnetic intensity. The back-propagation algorithm was employed for training and testing of the network, and the Levenberg Marquardt algorithm was utilized for optimization. The MATLAB 7.0 environment with Neural Network Toolbox was used for coding. Given the associated input parameters such as the external magnetic field strength (H), diameter of the balls (d), filter length (L) and packing fraction factor (γ), the model estimates the effect of the variation of the magnetic field intensity.
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Keywords

ANN; Magnetized Packed Bed; Magnetic Field Intensity

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