Optimization of Nusselt number and friction coefficient for double pass solar heater with aluminum V-Ribs as roughness on GI material sheet using genetic algorithm

Abstract

In this era, alternative energy fronts in areas such as solar energy are driven by needs. Due to the less efficient collector (solar based), various structures and techniques have been implemented to improve their efficiency. In this work, we formulated a genetic algorithm is applied to obtain an optimized set of operating parameters for a two-cycle solar collector with aluminum V-shaped ribs as an roughness material so that thermal performance can be optimized. Then obtained results using GA (Galvanized Iron) are compared against the experimental results. Thermal performance which is related to rate heat transfer which in turn is affected by different parameters and the range of these parameters which are considered in this work are; Reynolds number (Re) 800 to 12000, angle of attack (α) 25° to 80°, relative roughness spacing (p/e) 15 to 25 and relative roughness height (e/Dh) is 0.025 to 0.045. A set of optimized values of these parameters which affects heat transfer rate is thus obtained by genetic algorithm is then compared against the experimental ones. In the study of comparison, we get that the Nusselt number (Nu) is 1.08 times compared to the experimental one, and the friction factor (f) is 0.97 times compared to the experimental one.