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The present study aims to perform inverse analysis of a conjugate heat transfer problem including conduction and forced convection via the quasi-Newton method. The inverse analysis is defined for a heat source that is surrounded by a solid medium which is exposed to a free stream in external flow.

The objective of the inverse design problem is finding temperature distribution of the heat source as thermal boundary condition to establish a prescribed temperature along the interface of solid body and fluid. This problem is a simplified version of thermal-based ice protection systems in which the formation of ice is avoided by maintaining the interface of fluid and solid at a specified temperature.

The effects of the different pertinent parameters such as Reynolds number, interface temperature and thermal conductivity ratio of fluid and solid mediums are analyzed.

This paper fulfils the analysis to study how thermal based anti-icing system can be used with different heat source shapes.

This paper aims to investigate the two-dimensional numerical modeling of fluid flow and heat transfer in a fluid channel.

The channel is filled with the CuO-water nanofluid. The KKL model is used to estimate the dynamic viscosity and considering Brownian motion. On the other hand, the influence of CuO nanoparticles’ shapes on the heat transfer rate is taken account in the simulations. The channel is included with several active pipes with hot and cold temperatures. Furthermore, the external curved and sinusoidal walls have cold and hot temperatures, respectively.

Three different tilt angles are considered with similar boundary and operating conditions. The Rayleigh numbers, solid volume fraction of CuO nanoparticles in the pure water and the tilt angles are the governing parameters. Different cases studies, such as streamlines, heat transfer rate, local and total entropy generation and heatlines, are analysed under influences of these governing parameters.

The originality of this work is investigation of fluid flow, heat transfer and entropy generation within a nanofluid filled channel using FVM.