Direct numerical simulation and artificial neural network modeling of heat transfer characteristics on natural convection with a sinusoidal cylinder in a long rectangular enclosure

Abstract

In this study, a three-dimensional numerical simulation of the natural convection in a long rectangular enclosure containing a sinusoidal cylinder was conducted. The sinusoidal cylinder was examined to improve the total heat transfer performance in comparison to that of a circular cylinder. The effects of simulation parameters of the sinusoidal cylinder were compared with the results of a circular cylinder in the Rayleigh number range of 104≤Ra≤106. The key simulation parameters were the mean radius of the cylinder (0.1L≤Rmean≤0.4 L) and its wavelength (or wavenumber (1≤λ≤3)). The heat transfer characteristics at the surfaces of the cylinder and walls of the enclosure were investigated. The effect of the cylinder shape on the heat transfer performance was notable at Rmean=0.4 L, and the performance improved by up to 27%. An artificial neural network (ANN) model was also used for the natural convection heat transfer from the sinusoidal cylinder. The impact of the parameters on the heat transfer performance was quantitatively evaluated. The results show that the Rayleigh number and the mean radius of the cylinder have a great influence on the total heat transfer performance at the cylinder surface and enclosure walls.