Enhancing solar dryer performance through computational fluid dynamics in forced convection conditions

Abstract Solar drying technology has emerged as a pivotal contributor to sustainability in agriculture and various industrial sectors by harnessing solar energy for energy-efficient product dehydration. This research paper explores the effectiveness of Computational Fluid Dynamics (CFD) simulations in enhancing the design and operation of solar dryers, with a particular focus on scenarios involving forced convection. Solar dryers find versatile applications in agriculture, food processing, and industrial operations, propelling the expansion of research in this field. The core objective of this study is to computationally predict critical parameters within solar dryers operating under forced convection, including temperature distribution, velocity distribution, heat transfer coefficient variations, and humidity distribution. By leveraging CFD, this research seeks to shed light on the specific impacts of key variables, notably the solar dryer’s aspect ratio and the application of forced convection. The ultimate goal is to determine the optimal combination of these variables to maximize solar dryer performance. The findings of this study are expected to advance our understanding of how CFD simulations can be employed to enhance energy efficiency and product quality in solar drying processes. Furthermore, this research contributes to the ongoing efforts to develop sustainable and eco-friendly solutions for product dehydration in agriculture and industry, aligning with the global pursuit of a greener and more efficient future.