An analysis of computational fluid dynamics in a small-scale solar chimney system

The demand for energy has increased significantly due to the increasing world population and technological advancements. Interest in renewable energy has also increased to prevent and reduce environmental pollution. The trend towards solar energy, a renewable energy source, has also increased significantly in recent years. In this study, research was conducted on the solar chimney system existing at the Department of Mechanical Engineering, Faculty of Engineering and Natural Sciences, Konya Technical University. Using the monthly average meteorological data for Konya province for 2024, the temperature difference created by the air flow velocity in the collector was examined; in this context, both the collector efficiency and the solar chimney system efficiency were analysed. Based on the annual and long-term data, theoretical analyses, calculations, and modeling were performed using Computational Fluid Dynamics (CFD) simulations. With the monthly average meteorological data for May 2024, the collector inlet velocity was 0.53 m/s, while the collector efficiency was 68.3% and the system efficiency was 1.85%, the highest values were obtained. The analysis results were compared with the simulation outputs, and the accuracy and consistency of the findings were evaluated. Furthermore, theoretical analyses were conducted with air flow velocities at the chimney inlet set to 1 m/s, 2 m/s, 3 m/s, 4 m/s, and 5 m/s; these results were compared with HAD (Fluent) analyses, and it was observed that the obtained results were close to each other. Consequently, a certain agreement was observed between the theoretical analyses and CFD simulations. These results demonstrate that CFD-based analysis techniques are a reliable method for fluid mechanics and meteorological data. The obtained results are also consistent with those reported in the literature. Keywords: Renewable energy, Solar chimney, Meteorology, Collector, Computational Fluid Dynamics (CFD) Fluent, Weather data.