Nonlinear simulation for coupling modeling of air humidity and vent opening in Chinese solar greenhouse based on CFD

The Chinese solar greenhouse (CSG) ensures farming activities to continue and allow the harvest timing to be manipulated and become an important part of Chinese agricultural facilities. Effective control of the solar greenhouse environment is critical for the well-being of crops and is Important for the entire Eco-agricultural System. The rapid exchange of energy and materials in the CSG with the external environment are achieved through the natural ventilation of the upper vent and the lower vent. However, there is lack of relevant research that addresses the vent opening. In this study, the effect that the vent opening has on the CSG was studied through Computational Fluid Dynamics (CFD) simulation. The ventilation of a real solar greenhouse was simulated by establishing a 3D simulation model of the solar greenhouse with various vent openings. The main focus was the relationship between the vent opening and the air humidity changes in the CSG. This study presents a coupling between an energy balance model and a CFD model to study relationships between ventilation and humidity in a CSG. The simulation results demonstrated that natural ventilation increased along with the increasing of vent openings, which caused to a drop of air humidity and temperature in the solar greenhouse. This reduction was not a linear change in the traditional cognitive paradigm, but showed nonlinear changes through the simulation results. The requirements for the verification of simulation results were used to conduct a scale model to verify the results of the CFD experiments. The practical value and the significance of the research aims to provide basic reference for controlling the indoor air temperature and the air humidity by the natural ventilation of vents. The outcome could result in a reduction in energy consumption and GHG emissions in the greenhouse operations, which contributed to the improvement of resource efficiency and a cleaner production. These results have strong practical significance for the follow-up automation and intelligent control of CSG environments.