Improvement of Environmental Uniformity in a Seedling Plant Factory with Porous Panels Using Computational Fluid Dynamics

Abstract

A seedling plant factory requires precise environmental control to ensure uniform growth within a limited cultivation period. A porous panel exhaust system was installed to maintain a stable and uniform internal environment. To provide optimal temperature, humidity, and airflow, it is necessary to interpret the internal aerodynamics. However, field monitoring has limitations in analyzing the invisible flow patterns. To overcome this limitation, CFD simulations can be utilized to understand internal environmental conditions and uniformity. The objective of this paper is to develop and validate a CFD model of a seedling plant factory with a porous panel for improving the uniformity of the internal environment. Multiple data loggers were evenly installed at various locations inside the seedling plant factory, and 24 h field monitoring was conducted. The average temperature and humidity during the 16 h light period and 8 h dark period were maintained within 1% of the set values, while the regional temperature deviation had an average of 1.65 °C and a maximum of 2.63 °C. The regional humidity deviation had an average of 14.1% and a maximum of 23.8%. The CFD model was designed to analyze the internal environmental uniformity after validation by comparing it with the field monitoring data. The Realizable k-ε turbulence model, which exhibited an error of 4.0% in comparison with the field data, was selected through a validation test among four different turbulence models with the same configuration of the seedling plant factory. The CFD simulation results were interpreted quantitatively and qualitatively, focusing on the airflow, temperature, and humidity distributions caused by the air conditioner and humidifier. Variations in the average temperature of up to 0.5 degrees and velocity differences of 0.28 m/s were observed depending on the location of the cultivation shelves. The locations and causes of stagnant regions resulting from the airflow patterns were identified through the simulations.