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High-density controlled environment agriculture (CEA-HD) air distribution optimization using computational fluid dynamics (CFD).
- Source :
-
Engineering Applications of Computational Fluid Mechanics . Dec2024, Vol. 18 Issue 1, p1-17. 17p. - Publication Year :
- 2024
-
Abstract
- In this paper, the indoor environment of a small-scale high-density controlled environment agriculture (CEA-HD) space was simulated using computational fluid dynamics. Spatial modelling of the indoor environment considering the influential phenomena (e.g. transpiration and photosynthesis) over the indoor temperature, relative humidity, carbon dioxide (CO2) concentration, and airflow velocity is still challenging. These indoor environment conditions were computed for a 3D model of a CEA-HD experimental space while simultaneously modelling crop airflow impingement, transpiration and photosynthesis. The crops being grown were represented in the model as porous media zones and their exchanges with the indoor air were modelled using user defined functions. The air distribution parameters and configuration were optimized using a simplified 2D model to overcome the steep computational time, and associated cost, of 3D simulation. The objective function of the optimization problem relied on a correlation analysis of the simulation output. The optimization of the 2D model yielded an airfoil configuration that reduced the mean airflow speed and relative humidity variations between the cultivation tiers while achieving higher mean velocities (≈1.9 m⋅s-1) at a lower inlet speed (8 m⋅s-1). The proposed modelling and optimization approach is a small step forward towards model-based design and operation of CEA-HD production spaces. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19942060
- Volume :
- 18
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Engineering Applications of Computational Fluid Mechanics
- Publication Type :
- Academic Journal
- Accession number :
- 178730776
- Full Text :
- https://doi.org/10.1080/19942060.2023.2297027