Parametric Optimization of Solar Air Heaters Having Hemispherical Protrusion Roughness in the V-Notch Pattern on the Absorber Plate: A Metaheuristics Optimization Approach

Artificial roughness in the form of protrusions has become a popular technique to improve the thermohydraulic performance of SAHs. So, utmost attention should also be given to determining the suitable parametric values that directly affect the performance of SAHs. Hence, in this work, an attempt has been made to optimize the performance of solar air heaters having hemispherical protrusion roughness in a V-notch pattern on an absorber plate using two different metaheuristic optimization algorithms, i.e., the grey wolf optimization (GWO) algorithm and the dragonfly (DA) algorithm. This study makes use of the correlation equations for the friction factor (ff) and Nusselt number (Nu), which were developed after conducting the experiments. Four independent parameters, namely the Reynolds number (Re = 3600–21,700), relative protrusion height (ep/Dh = 0.027–0.069), relative pitch (p/ep = 6–14), and attack angle (αa = 15°–75°), were considered to obtain the optimal values of Nu and ff. In single-objective optimization, the maximization of Nu and the minimization of ff are two objective functions. The GWO has delivered the best solutions for both objectives with a faster computational rate and less variation. A convergence curve and box plot validated these findings. The maximum value of Nu was found to be 144.567, corresponding to Re = 21,700, ep/Dh = 0.07, p/ep = 8.54, and αa = 750, and the minimum value of ff was found to be 0.012, corresponding to Re = 21,700, ep/Dh = 0.03, p/ep = 14, and αa = 15°. Pareto multi-objective optimization provides compromised solutions that provide flexibility to the decision maker in selecting a parametric setting.