Computational Fluid Dynamics-Based Simulation of Crop Canopy Temperature and Humidity in Double-Film Solar Greenhouse

Abstract

The microenvironment of the crop area in a greenhouse is the main factor that affects its growth, quality, and pest control. In this study, we propose a double-layer film solar greenhouse microenvironment testing system based on computational fluid dynamics simulations of a celery canopy with a porous medium. A real greenhouse was examined with a sensor system for soil, air, radiation, and carbon dioxide detection to verify the simulation results. By monitoring the internal environment of celery canopies with heights of 0.8 and 1 m during a period of temperature fluctuations, we found the temperature and humidity of the canopy interior changed spatially and differed greatly from the those in the greenhouse under solar radiation conditions. The temperature and humidity of the celery canopy were 4–14°C lower and 10%–30% higher than those of the surroundings. As the canopy grew, the differences in temperature and humidity between the canopy and other parts of the greenhouse increased. The root mean square errors of the temperature and humidity with the 0.8 m high celery canopy were found to be 0.56 and 2.86 during the day and 0.24 and 0.81 at night, respectively; the corresponding values for the 1 m high celery canopy were found to be 0.51 and 2.26 during the day and 0.26 and 0.78 at night. The porous medium model expressed the temperature and humidity characteristics of the celery crop appropriately, and the simulation method was shown to be effective and feasible. With the simulation method proposed in this study, the production of crops in complex microenvironments in greenhouses can be modeled and digitized.

Contribution to the Sustainability of Agricultural Production in Greenhouses Built on Slope Soils: A Numerical Study of the Microclimatic Behavior of a Typical Colombian Structure

“…The CFD study has allowed the study of almost all existing passive greenhouse models worldwide, and has also been implemented as a tool for the optimization of climate management in greenhouses with active climate control [18][19][20]. There are currently a considerable number of studies applied to agricultural investors that have used CFD simulation to analyze thermal distribution [10,21,22], moisture distribution [5,21,23], efficiency of heating systems [24][25][26], the operation of cooling systems [27][28][29] and the microclimate generated as a function of different ventilation configurations [7,12,[30][31][32]. In the specific case of Colombia, the use of CFD and other modelling techniques to determine the behavior of the main greenhouse structures used has been carried out for the specific conditions of the Bogotá savannah and for a topography of flat soils, which is where the ornamental and cut flower industry is generally developed [33][34][35].…”

Experimental study on indoor environmental factors of double film solar greenhouse and traditional Chinese greenhouse in cold region

“…The results showed that the floor temperature was respectively 5.2°C, 4.6°C and 2.0°C higher than that of the soil in the adjacent reference greenhouse after heat storage in clear, cloudy and overcast sky in winter (Wang et al, 2006). Moreover, the temperature and humidity distribution of the canopy in double film solar greenhouse was studied based on computational hydrodynamics, and the simulation results showed high agreement with the measured values (Jiao et al, 2020). Between double polyethylene films with liquid foam during the day when solar radiation was high.…”

Plant science in the age of simulation intelligence

“…Plant models involve various kinds of physical models, going from molecular and metabolic processes ( Farquhar et al., 1980 ), hydraulic functioning ( De Swaef et al., 2022 ), to soil and atmospheric physics ( Liu et al., 2020b ). Modern (functional-structural) plant modeling involves advanced physics simulation such as ray tracing to assess radiation ( De Visser et al., 2014 ; Bailey, 2018 ; Retkute et al., 2018 ) and computational fluid dynamics ( Bartzanas et al., 2013 ; Jiao et al., 2020 ). The latter are often computationally demanding and might require appropriate tools, such as surrogate modeling (discussed later), to make them feasible for, e.g., greenhouse control.…”