Cooling System In Greenhouse CFD Simulation, ANSYS Fluent Training
Cooling System In Greenhouse CFD Simulation, ANSYS Fluent Training
- Upon ordering this product, you will be provided with a geometry file, a mesh file, and an in-depth Training Video that offers a step-by-step training on the simulation process.
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€155.00 Original price was: €155.00.€85.00Current price is: €85.00.
A greenhouse needs a cooling system to keep growing conditions as ideal as possible. This technology ensures that plants grow in a comfortable environment by regulating temperature and humidity levels. The cooling system helps ensure that a wide range of crops are successfully cultivated by preventing overheating. This CFD study is conducted based on the reference paper “ Modeling and optimal design of evaporative cooling system in controlled environment greenhouse “.
Figure 1: Schematic of the greenhouse
Simulation Process
As illustrated in Figure 1, the central height is 3m, and the heights of the north and south walls are 3m and 2m, respectively. To cool the greenhouse during the summer, a cooling pad is installed on the west wall, and two fans are placed on the east wall. It is provided a smooth cold flow that transmit through a porous system. The greenhouse is placed in a specific geographical coordination that is defined in Solar Ray Tracing properties. The enable of this module needs use of Discrete Ordinates (DO) radiation model. The convective heat transfer with the hot outdoor surroundings is included.
Post-processing
Despite the hot outdoor temperature (307K), the cooling system can provide 286K cold flow and cold down the greenhouse indoors. Undoubtedly, the higher air change per hour (ACH) results in better ventilation. However, the sensitive vegetation is one of the main limitations in cooling system design. On balance, the indoor volume average temperature reaches 296.7K in steady-state conditions, showcasing a 10-degree decrement compared to the ambient.
We pride ourselves on presenting unique products at CFDLAND. We stand out for our scientific rigor and validity. Our products are not based on guesswork or theoretical assumptions like many others. Instead, most of our products are validated using experimental or numerical data from valued scientific journals. Even if direct validation isn’t possible, we build our models and assumptions on the latest research, typically using reference articles to approximate reality.
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