Abstract

In this paper, simultaneous inverse prediction of two parameters such as the porosity and thermal diffusivity of the fluid in a porous fin is done for satisfying a given temperature distribution. Only three temperature measurements are assumed to be available on the surface of the fin and prediction of the parameters is accomplished by using the differential evolution (DE)-based optimization technique. It is shown that the present problem is inherently ill-posed in terms of the retrieval of the value of fluid thermal diffusivity for which many possible solutions exist, which is expected to adapt the fin under different conditions. In the present work, two numerical examples provide engineering insight into the problem of designing porous fins using good thermal conductors like aluminum and copper along with the working of DE. Finally, the efficacy of DE for the present problem is also shown by comparing its performance with few other optimization methods.

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