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.

在本文中，首次展示了一种逆方法，用于使用表面温度响应同时预测径向多孔翅片中的内部发热和磁场强度。系统的运行是在外加磁场和所有传热模式下考虑的。最初，获得经过验证的直接解来计算温度场，然后使用人工蜂群 (ABC) 算法辅助的逆方法估计未知数。进行数值案例研究以找到给定未知数之间的适当关系。目前的分析强调，虽然存在许多满足给定热分布的可能组合，但是，对于给定的温度分布，磁场强度和发热始终呈线性变化。即使在随机噪声的影响下，ABC辅助算法也能准确重构可用条件，并以2%以内的精度出色地建立参数之间的相互关系。为了从多孔翅片进行所需的热传递，得出的结论是，本方法有利于准确控制磁场以对抗未知的内部发热条件。