Abstract:
The application of the Adomian decomposition method (ADM) is extended to study a conductive–convective and radiating moving fin having variable thermal conductivity. Next, through an inverse approach,
ADM in conjunction with a binary-coded genetic algorithm (GA) is also applied for estimation of
unknown properties in order to satisfy a given temperature distribution. ADM being one of the
widely-used numerical methods for solving non-linear equations, the required temperature field has
been obtained using a forward method involving ADM. In the forward problem, the temperature field
and efficiency are investigated for various parameters such as convection–conduction parameter, radiation–conduction parameter, Peclet number, convection sink temperature, radiation sink temperature,
and dimensionless thermal conductivity. Additionally, in the inverse problem, the effect of random measurement errors, iterative variation of parameters, sensitivity coefficients of unknown parameters are
investigated. The performance of GA is compared with few other optimization methods as well as with
different temperature measurement points. It is found from the present study that the results obtained
from ADM are in good agreement with the results of the differential transformation method available in
the literature. It is also observed that for satisfactory reconstruction of the temperature field, the measurement error should be within 8% and the temperature field is strongly dependent on the speed than
thermal parameters of the moving fin.
