Building a reduced order model from CFD data on leaves to evaluate optimal climate conditions

Climate control in vertical farms or greenhouses is crucial in order to have the optimal climate for the plants. This climate can be simulated using Computational Fluid Dynamics (CFD). This way, different ventilation methods can for example be compared. Previously, plants were modeled as a porous zone, in which additional source terms are added to the energy or transpiration transport equation. In this study, ten different leaves under different orientations are studied. The heat and mass balance for each leaf is solved and the boundary layer is adequately resolved. Different leaf orientations and positions to the flow are used, so that each leaf has its own distinct boundary layer. Leaf temperature and humidity are a function of the incoming flow, but also of the incoming temperature, humidity and stomatal resistance. In order to be able to quickly assess the effects of changing boundary conditions, on the temperature and humidity of the leaves, a Reduced Order Model (ROM) is made from the CFD-data. This method allows to quickly assess the effects of a stomatal resistance, the incoming radiation or a changing inlet temperature or humidity. A ROM was built using the data from one simulation. In order to see whether the ROM is able to predict other configurations, two additional cases were solved in CFD and were compared to the ROM. Leaf temperatures and humidities only differed maximally 3.14% and were quite good at predicting this. Predicted leaf transpiration rates differed slightly more, as these differed maximally 10.5%. Overall, the ROM has proven to be a valuable and numerically cost-effective tool to predict overall leaf climate and can be a good tool when later the climate of a full plant is simulated.