Application of genetic algorithm for unknown parameter estimations in cylindrical fin

This article deals with the application of the genetic algorithm (GA) for optimizing an inverse problem and retrieving unknown parameters in cylindrical fin geometry. Parameters such as the thermal conductivity and the heat transfer coefficient are attempted for estimation in order to satisfy a desired temperature field in the medium. The study is done for single-parameter and simultaneous two-parameter retrievals. The temperature field is calculated from a forward problem using the finite difference method using some known values of the properties. These properties are ultimately retrieved by an inverse approach using the GA. The study is done for different controlling parameters such as the number of generations, measurement errors and number of measurement locations. For two parameter simultaneous estimation, many combination of unknown parameters are observed to satisfy a given temperature field, and their ratio is only found to be successfully estimated. The present work is proposed to be useful for selecting the thermal properties which are required to satisfy a given temperature field.

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► Radial fin geometry where temperature distribution is available but some thermal properties are unknown.
► Inverse problem is solved for estimating the unknowns and optimizing the reference temperature field.
► Parameters are found to be correlated and multiple combinations of unknowns are found to exist.
► Genetic algorithm (GA) is used to solve the problem and effects of controlling parameters are investigated in detail.
► Number of temperature measurement locations on the accuracy of estimation is also studied.