Evaluation, Monitoring, and Improving the Airflow and Heat Transfer in a Cold Storage of Foodstuffs, CFD Simulation and Experimental Investigation

Abstract

Freshness and quality of fruits and vegetables as well as product saleable weight depend on heat and moisture transfer rate during air-cooling in the cool storages. The main objective of this study was to evaluate and develop a validated CFD model for predicting the temperature and velocity fields in a cold storage. In this study the air temperature, velocity, and non-uniform airflow in cold storage have been studied experimentally and numerically. Experimental and numerical models were employed to investigate cold storage's airflow field, flow pattern, and temperature field. The temperature and the velocity fields were measured in the cold storage filled with two potato pallets by using a hot wire anemometer and thermocouple with a programmable data logger computer. The experimental data was recorded at 60 points of temperature, and 27 points of velocity from three levels; high, middle, and bottom. Numerically the SB (Solid Block) technique was used to assess four turbulence models (Standard k-ε, Realizable k-ε, Standard k-ω, and SST k-ω) to compare with the experimental results for validation. The results of the validation were agreed with the experimental. The comparisons between the numerical results and experimental results revealed that the Shear Stress Transport (SST k-ω) model shows the best performance with the smallest absolute errors for temperature and velocity respectively. As well as the results revealed that the bottom and the top of the room was subjected to fresher and cooler air with relatively higher velocity. According to the study validation and finding, using the SST k-ω model is the best model for investigation in a cold storage, and for the improvement and evaluation of more complex cold storage, to achieve the balance distributions of air velocity, air temperature, and other heat transfer phenomena.