Simultaneous estimation of heat generation and magnetic field in a radial porous fin from surface temperature information

In this paper, for the first time an inverse methodology is demonstrated for simultaneously predicting the internal heat generation and magnetic field strength in a radial porous fin using the surface temperature response. The operation of the system is considered under an imposed magnetic field and all modes of heat transfer. Initially, validated direct solutions are acquired for calculating the temperature field, and thereafter the unknowns are estimated using an inverse method assisted by the Artificial Bee Colony (ABC) algorithm. Numerical case studies are done to find an appropriate relationship among the given unknowns. The present analysis highlights that while many possible combinations exist satisfying the given thermal profile, however, the magnetic field strength and heat generation always vary linearly for a given distribution of temperature. Even under the influence of random noise, the ABC assisted algorithm is found to accurately reconstruct the available condition and excellently establish the mutual relationship between the parameters with an accuracy within 2%. For the purpose of a required heat transfer from porous fins, the present methodology is concluded to be beneficial in accurately controlling the magnetic field against an unknown condition of internal heat generation.

Automated summary

This paper demonstrates an inverse methodology for predicting internal heat generation and magnetic field strength in a radial porous fin using the Artificial Bee Colony (ABC) algorithm. The study found a linear relationship between magnetic field strength, heat generation, and temperature distribution. The ABC algorithm accurately reconstructs conditions and establishes relationships between parameters with high accuracy.