Abstract:
This article deals with the prediction of parameters in an annular hyperbolic
fin with temperature-dependent thermal conductivity. Three parameters such
as thermal conductivity, variable conductivity coefficient and the surface heat
transfer coefficient have been predicted for satisfying a prescribed temperature
distribution on the surface of fin. This is achieved by a hybrid differential
evolution-nonlinear programming optimization method. The effect of random
measurement errors is also considered. It is observed from the present inverse
analysis that many feasible materials exist satisfying the given temperature
distribution, thereby providing engineering flexibility in selecting any material
from the available choices. For a given material, this is possible by regulating
the surface heat transfer coefficient.
