Computational Fluid Dynamics Modelling of Airflow and Heat Transfer in Forced-Air Cooling Systems for Fresh Produce in Nigeria

This study applies computational fluid dynamics modelling to analyse airflow patterns and heat transfer characteristics in forced-air pre-cooling systems designed for fresh produce handling in Nigerian post-harvest facilities. Forced-air pre-cooling is the most effective method for rapidly removing field heat from fresh horticultural produce after harvest, but cooling system performance is highly sensitive to airflow distribution uniformity across the produce bulk. CFD modelling enables optimisation of cooling room geometry, vent configuration, and stacking patterns before costly physical prototyping. This study develops CFD models using ANSYS Fluent for three representative cooling room configurations relevant to Nigerian agro-processing scales: a small 3-tonne room for cooperative-scale facilities, a medium 15-tonne commercial room, and a large 50-tonne centralised facility. Boundary conditions are set using measured Nigerian ambient temperature and humidity data from Lagos, Kano, and Enugu as representative locations. Model validation uses temperature measurements from an instrumented prototype cooling room at the University of Agriculture Abeokuta. Findings reveal significant airflow non-uniformity in the standard container-based cooling room configuration commonly used in Nigeria, with temperature differences of 8 to 12 degrees Celsius between high- and low-airflow zones. Optimised vent positioning and baffle designs reduce maximum temperature non-uniformity to below 3 degrees Celsius. The study contributes validated CFD modelling capability for Nigerian post-harvest cooling system design and recommends adoption of CFD analysis as a standard design tool for Nigerian cold room engineers.

Keywords: computational fluid dynamics, forced-air cooling, fresh produce, post-harvest, Nigeria.