Modeling Airflow and Temperature in a Sealed Cold Storage System for Medicinal Plant Cultivation Using Computational Fluid Dynamics (CFD)

Abstract

Effective air circulation is crucial for plant growth, requiring adequate airflow and environmental stability. This study utilized Computational Fluid Dynamics (CFD) to analyze airflow patterns in a controlled testing chamber, focusing on how miniature fan placement affects airflow direction and temperature distribution. Ten case studies were conducted, with the CFD model validated against experimental data collected from six monitoring locations on the plant growth table. Model validation was performed using statistical analyses including coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The validation results showed strong agreement between simulated and experimental data, with R2 values of 0.92 for temperature and 0.89 for airflow velocity. Statistical analysis showed significant differences in both airflow and temperature models at the 0.05 level, with the CFD model validation yielding an RMSE of 2.02 and an average absolute error of 1.17. Among the tested configurations, case M1 achieved the highest air velocity (0.317 m/s) and lowest temperature (27.03 °C), compared to M2 (0.255 m/s, 27.17 °C) and M3 (0.164 m/s, 27.18 °C). The temperature variations between cases significantly impacted cold storage efficiency, with case M1’s superior airflow distribution providing more uniform cooling. These findings offer practical guidelines for optimizing ventilation system design in medicinal plant cultivation facilities, particularly in maintaining ideal storage conditions through strategic fan placement and airflow management.