Lee, S.-W.; Seo, I.-H.; An, S.-W.; Na, H.-Y. Improvement of Environmental Uniformity in a Seedling Plant Factory with Porous Panels Using Computational Fluid Dynamics. Horticulturae2023, 9, 1027.
Lee, S.-W.; Seo, I.-H.; An, S.-W.; Na, H.-Y. Improvement of Environmental Uniformity in a Seedling Plant Factory with Porous Panels Using Computational Fluid Dynamics. Horticulturae 2023, 9, 1027.
Lee, S.-W.; Seo, I.-H.; An, S.-W.; Na, H.-Y. Improvement of Environmental Uniformity in a Seedling Plant Factory with Porous Panels Using Computational Fluid Dynamics. Horticulturae2023, 9, 1027.
Lee, S.-W.; Seo, I.-H.; An, S.-W.; Na, H.-Y. Improvement of Environmental Uniformity in a Seedling Plant Factory with Porous Panels Using Computational Fluid Dynamics. Horticulturae 2023, 9, 1027.
Abstract
The seedling plant factory requires precise environmental control to ensure uniform growth within a short time cultivation period. To provide optimal temperature, humidity, and airflow, it is necessary to interpret the internal aerodynamics. However, the analysis based on field experiments has limitations in interpreting the invisible flow patterns. To overcome this limitation, CFD simulations were employed. The objective of this study was to develop and validate a CFD model of the seedling plant factory with the porous panel for improving the internal environment and to identify the fluid dynamics issues using the validated model. Based on the field monitoring data obtained by 90 data loggers, the average temperature and humidity during the 16-hour light period and 8-hour dark period were maintained within 1% of the set values. However, regional differences occurred, which led to the design of a CFD model incorporating the porous panel to simulate these variations. The Realizable k-ε turbulence model, which exhibited an error of 4.0% in comparison with the field data, was selected through 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 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.
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