Experimental and Numerical Approaches: Performance Optimization of a Baffled Solar Cabinet Dryer for Mango Slices

Abstract

During peak seasons, postharvest loss of mangoes remains a significant challenge for smallholder farmers in Ethiopia, driven by high production volumes, limited market access, and a lack of preservation methods. The objective of this research was to develop and enhance the performance of a solar cabinet dryer for mango slices through Computational Fluid Dynamics (CFD) simulations. A solar cabinet dryer incorporating a rectangular baffle solar collector was developed, built, and experimentally validated. The CFD simulation results showed a temperature difference of 4.35% and a relative humidity deviation of 7.8%, indicating good agreement with the experimental data. The model optimized the baffle design and inlet air velocity to maximize outlet temperature and minimize pressure drop. The optimal design was identified using Response Surface Methodology (RSM) in conjunction with ANSYS software. The best-performing configuration featured four baffles with 25% cut openings and an inlet air velocity of 1 m/s. The porous domain of mango slices was incorporated into the model to predict moisture transport with experimental effective diffusivity of (5.224 × 10⁻⁷ m²/s). Results showed that the designed dryer achieved uniform temperature and moisture distribution, with higher drying rates observed near the lower trays. .The moisture content in mango slices was reduced from 45942.17 mol/m³ to 2,677 mol/m³ within two hours of drying. The CFD model showed strong predictive accuracy with only minor discrepancies observed in the simulation of temperature, relative humidity, and moisture movement. The developed dryer provides a sustainable and cost-effective solution to reduce postharvest mango losses with an efficient design that enhances food security and farmer livelihoods.

Keywords: CFD modeling, heat and mass transfer, mango slices, postharvest loss, solar dryer