How to Simulate Thermal and Fluid Dynamical Processes in Closed Greenhouses including Water Interactions between Plants and Air P. Jochum and M. Buchholz Technical University of Berlin, Faculty of Architecture Straße des 17. Juni 135, 10623 Berlin Germany Keywords: CFD, closed greenhouse, natural ventilation, simulation, Smile, thermal and pressure node model, water treatment Abstract A new type of greenhouse is presented. It is a closed system using buoyancy as driving force for ventilation. The greenhouse is equipped with a tower in which the air is cooled or heated to maintain the inner temperatures in the required band and then conducted back to the plants. During the cooling process the water in the humid air condenses and can be reused. The subject of this article is the way of prediction of the thermal behaviour of closed greenhouses by means of dynamic simulations. Several model approaches are discussed. The simulation environment Smile is presented as a flexible program for this purpose. INTRODUCTION Closed greenhouses were designed hoping for various advantages. First the possibility of injecting CO2 without important losses for increased fruit production, second the reduction of water losses by the absence of wind and the potential of reusing water from condensation processes, and third the use of the greenhouse as a solar collector extracting excess energy during hot days for heating purposes in cold periods thus stretching its operation time without external energy supply. The main disadvantage of closed greenhouses in contrast is the non trivial thermal and humidity behaviour of the combined system consisting of greenhouse cover, air, plants, soil, and heating/cooling facilities. Therefore an EU funded research project, named Watergy, has been created (Buchholz et al., 2005). In this paper the chosen approach to the simulation of the investigated systems will be shown. WATERGY The objective of Watergy is the development of a closed humid air solar collector (Fig. 1) driven by natural convection forces due to buoyancy. The solar collector could be either a solitary greenhouse or an attached greenhouse in front of a building. The buoyancy resulting from the warmed up plant region causes an air flow to the top of the collector. From there the air will be conducted back to the plants through a colder heat exchanger which is installed in a return duct. The cooled air flows back to the plant region where the cycle restarts. During the circulation of the air the moisture content varies in a wide range. The air will be humidified by the transpiration of the plants and the evaporation from the soil. Furthermore the air is additionally humidified with grey or salty water. To prevent contact of this water with the plants, an extra so called inner roof has been installed collecting the remaining drain water that is not evaporated. In the cold heat exchanger the water vapour will condense and can be collected for irrigation or other purposes (Fig. 2). Through the humidification of the air by evapo-transpiration and the additional sprinkler system the air temperature can be kept relatively cold. This results in smaller heat losses to the environment. A heat storage is needed to extract the heat from the collector and supply the heat exchanger with cold water. Cold water can be obtained by heating the greenhouse with the same heat exchanger during colder periods, in the case of diurnal storage during the night or in the case of a seasonal storage during the colder season. Proc. IC on Greensys Eds.: G. van Straten et al. Acta Hort. 691, ISHS 2005 553 To acquire realistic results regarding the behaviour of the described humid air collector, the system is analytically and experimentally studied (Buchholz et al., 2005). For the experimental investigations two prototypes will be erected. The first prototype, a greenhouse with diurnal storage, has been built in the south of Spain (Almeria), measurements (Janssen et al., 2005) starting in July 2004. The second prototype is an office building connected to a greenhouse with a seasonal storage. Constructions are going to start in March 2005. MOTIVATION FOR SIMULATION The idea of creating free air circulation in a building driven by the combination of buoyancy of heated and fall-off by cooled air is a new application. The dimensioning of all air leading parts in the greenhouse or building, especially height and diameter of the tower, and the design of the heating and cooling system, mainly consisting of the heat exchanger and the heat storage, are non trivial due to the complicated network of thermal interactions, that characterizes the system. Some examples: – The efficiency of the heat exchanger has an important influence on the temperature difference of the air between bottom and top, thus on the air flow in the greenhouse. – Increasing heat transfer in the heat exchanger enlarges the contact surface for the air that causes higher pressure losses and a reduction of air mass flow. – High relative humidity reduces heat losses by lowering the air temperature but can decrease the air flow due to lower temperature differences between top and bottom. – Solar energy can be used to increase the sensible or the latent heat of the air (or both). High temperature and low relative humidity result in high thermal losses and increased air mass flow with lower water content in the air. – Increasing greenhouse temperatures result in increasing storage temperatures which permit a smaller storage volume. In addition the optimum air conditions for fruit production must be considered and have a strong impact on the design of the heating and cooling system. Furthermore the economical optimum between the value of the harvest over a year and of the value of the saved water as well as the necessary investment costs must be accomplished. SIMULATION APPROACHES There were many different investigations in the development of simulation tools. Most of them are based on a mathematical representation of real systems using physical rules. Models can become very large, particularly when local discretisation is used, depending on the complexity of the represented system. Another program type is based on experimental data. They determine the future system behaviour applying knowledge of past behaviour. The advantage of these data based models is the mostly less complicated structure, but in return they offer no insight into the system. The influence of modifications in the construction of a real system or in the included technical devices can not be determined. The intent to develop a planning tool is the reason for the concentration on physically based models in this study. Programs that can be used in this context have to accomplish five basic specifications. These are: – the calculation of the air flow in the greenhouse, – the thermal analysis of the construction and the enclosed air, – the water balance including evapo-transpiration, air humidification, and condensation, – the possibility of simulating the thermal dynamic of the technical equipment, – and the ability to be adapted to unusual greenhouse geometries. The investigations concerning existing simulation programs lead to a classification of the existing or available programs (Fig. 3). Most of them do not cover all five abilities described, but include very helpful details in modelling specific aspects. Computational Fluid Dynamics Computational fluid dynamics (CFD) has been applied in various fields. It is used to predict air flows in room, towers, greenhouses etc. (e.g. Lee et al., 2003). Primarily 554 used programs are FLUENT, Star-CD and CFX. The principle of CFD is the solution of a set of non-linear partial differential equations which represents the fundamental physical laws of the conservation of mass, momentum, and energy. Additionally the consideration of turbulences that normally exist in most practical cases complicates matters considerably. A common approach is the use of the Reynolds averaged form of the Navier-Stokes equations, where the instantaneous air flow is assumed to be the sum of a mean and a fluctuating component. Thermal Analysis Thermal analysis programs often originate from the simulation of buildings or systems for heating, ventilation, and air conditioning (HVAC). A wide range of building simulation programs is available, the most known are BLAST, DOE-2, TRNSYS, ESP or TAS. A very informative site can be found at www.eere.energy.gov. Most of them use non-geometrical models and concentrated parameters for the included issues like walls, windows, air etc. Programs for the simulation of HVAC systems including solar heating and cooling are very often developed for the simulation of specific systems. But there are also modular and flexible HVAC programs which provide a library of reusable components, the most known are TRSNYS and Smile (Nytsch-Geusen, 2001). Both programs include an extensive library with models for buildings and HVAC systems. Their common origin is the simulation of thermal solar systems that has evolved to the current main application, the simulation of buildings. Greenhouse Simulation and Plant Modelling The simulation of greenhouses including plants can be done by means of steady state models. The dynamical thermal effects like they are known in buildings or heat storages are normally negligible here. There are many approaches to simulate greenhouses, e.g. HORTITRANS (Jolliet, 1994) and HORTICERN (Jolliet et al., 1991). An impressive overview on modelling solar energy input in greenhouses is given in (Pieters and Deltour, 1999). Aspects of the convective heat transfer in greenhouses are described in (Roy et al., 2002). Pressure Node Models Besides the more known method for the solution of the partial differential equation system for the 2- or 3-dimensional flow used in CFD, the air flow can also be determined by a much easier but less adequate method, the pressure node model. In this kind of model the flow distribution inside a zone is not analysed, only the outgoing and incoming flows at the borders of the homogeneous zone are calculated. This reduces the equation system to a one-dimensional system. The state variables of the air in every zone, like temperature, humidity, pressure, and pollutant concentration, are calculated by a model using lumped parameters. Through defined air paths, e.g. windows, doors, cracks in walls or windows, air change can occur. The air movement between the zones is calculated by pressure balances for every zone considering the pressure drop passing the air path resistance. Using air mass conservation for the complete network of pressure nodes, a system of non linear equations is built and solved. A not very new but excellent survey of airflow models in multi-zone structures is given in (Feustel and Dieris, 1992). More recent analyses are described in (Dorer et al., 2001) and in (Nytsch-Geusen, 2001). Aspects of Coupling CFD and Thermal Analysis The use of CFD requires the proper definition of the boundary conditions of the examined volume, including all interior wall temperatures, heat flows through the outer areas and the incoming or outgoing air flows. These boundary conditions are extrapolated into the cell grid in the investigated volume to solve the transport equations. Erroneous boundary conditions lead to incorrect flow predictions. Considering the changing thermal situations the boundary conditions have to be recalculated and the CFD analysis has to be 555 redone for the new situation. This produces long term analyses and is, until now, not suitable as a design tool in the sense it is needed here. Nevertheless there are some investigations (Negrao, 1995; Nytsch-Geusen et al., 2003) to connect thermal analysis programs with CFD programs. Basically two different coupling mechanisms are used. They differ in the coupling mechanism in one direction (from thermal analysis to CFD) and in two directions (boundary conditions to CFD and flow conditions back to thermal analysis). Depending on the time step in the thermal analysis or the fact of appreciable changes in the inner surface conditions this can be done related to special handshake schedule (Beausoleil-Morrison, 2000). The known investigations achieved interesting results, but related to model limitations, inconvenient use of programs and extensive calculation times they could not yet establish new applicable standards. IMPLEMENTATION OF THE WATERY GREENHOUSES IN SMILE The simulation environment Smile (Ernst et al., 1997; Ernst et al., 2000) has been chosen for the Watergy project. Smile has been developed by the Technical University Berlin and the Fraunhofer Institute for Computer Architecture and Software Technology since 1990. It is an universal simulation environment for time continuous and discrete system modeling and is characterized by the following fundamental properties: equation and object oriented modelling language, open and expandable, large model library, and interchangeable numerical solvers with variable time steps. The model specifications were written in the Smile modelling language. The Smile model compiler translates this code into Objective-C and another C-compiler into an executable program code. The model library contains a set of basic model classes for building elements (walls, windows, roof, etc.), and for HVAC technical equipment (solar collector, heat storage, heat exchanger, pumps, etc.). These models allow the configuretion of complex building models using three object oriented paradigmas encapsulation, inheritance and aggregation. Besides the capacity of thermal building simulation the building model can determine the interzonal air and moisture change through pressure networks. Every zone can be equipped with a thermal, radiative and a pressure node. Combining all zones to the simulation model allows to solve the resulting equation system. Before Smile was applicable for the simulation of the Watergy greenhouse (prototype I) some model adjustments had to be done. Exemplary Model Adaptions 1. Short Wave Radiation. The building elements in the model library were originally developed for the modelling of „normal“ buildings with normally sized windows. For this reason the window model code contains a complete transformation of direct radiation into diffuse radiation. The diffuse radiation hits the inner surfaces (walls, roof, etc.) according to their areas and absorption coefficients. This produces a negligible error in „normal“ buildings especially if the thermal inertia is high. In the case of greenhouses and particularly in the Watergy situation where even two transparent layers have to be passed sequentially, this assumption is no longer true. Considering in reality the existence of direct short wave radiation inside the zone, the model had to be changed by the introduction of a weighting factor which allocates a main direction to the „diffuse“ radiation. 2. Long Wave Radiation. The models for windows normally assume glass as transparent material. Unlike plastic foils glass is a (almost) perfect barrier for long wave radiation. As it is very common to use plastic foils for the transparent cover of greenhouses the window model had to be changed to include the transmission of long wave radiation. Vegetation. For the plant model a new Smile class had to be defined. The mathematical base has been adapted from the FAO Irrigation and Drainage Paper, No. 56. Using the inheritance feature of Smile additional crop models can easily be added. Air humidifier. As mentioned before the moving air is going to be humidified above the inner roof using sprinklers. The required model is very sensitive for the 556 unknown droplet size in the sprays. This is why the model will have to be based on empirical data after the measurements. For the simulation of the prototype 6 zones were chosen (Fig. 4). The bottom zone with the plant area, the top zone between the two roofs, the tower zone outside the chimney and three further zones inside the chimney including the heat exchanger. Fig. 5 shows the used surfaces for the definition of the bottom zone as an exemplary development view. The areas in use are defined by their physical properties and their orientation. of the greenhouse. RESULTS AND DISCUSSION The forgoing provides an insight into the difficulties of simulating closed greenhouses with natural convection and facilities for heating and cooling. There are various approaches for parts of the in this case examined systems, speaking of greenhouses, plants, air movements or the technical equipment like heat exchanger and storage. However for the prediction of the behaviour of a combined apparatus in the sense it is described here it is essential to implement the complete system because of the strong interactions between the different elements. Closed systems with natural ventilation suggest a system analysis with CFD methods. But in the context of the development of a design and planning tool long term simulations must be considered that cannot be done with CFD. One approach to combine fluid dynamic analyses with thermal simulations consists of using of so called pressure node models. These models simplify the air flow to a 1-dimensional problem at the connections between two different zones of the model. The ability to determine the air flow with the pressure node method, the thermal behaviour of the building including plants, and the HVAC system could be found in the simulation environment Smile. The existing model library could be adapted and extended. The first evaluation of the measurements are expected April/May 2005. At that point a comparison of calculated and real data can begin. ACKNOWLEDGEMENTS This research is funded by EESD, the EC 5th Framework Programme promoting Energy, Environment and Sustainable Development (Project Number NNE5-2001-683). Literature Cited Beausoleil-Morrison, I. 2000. The Adaptive Coupling of Heat and Air Flow Modelling within Dynamic Whole-Building Simulation. PhD Thesis. University of Strathclyde. Glasgow, UK. Buchholz, M., Jochum, P. and Zaragoza, G. 2005. Concept for Water, Heat and Food Supply from a Closed Greenhouse - The Watergy Project. Acta Hort. 691:509-516. Dorer, V., Haas, A., Keilholz, W., Pelletret, R. and Weber, A. 2001. COMIS simulation environment for multizone air flow and pollutant transport modelling. Seventh International IBPSA Conference. Rio de Janeiro, Brazil 13-15 August. p. 403-410. Ernst, T., Jähnichen, S. and Klose, M. 1997. The architecture of the SMILE/M simulation environment.15th World Conference on Science Computation, Modelling and Applied Mathematics. Berlin. Ernst, T., Klein-Robbenhaar, C., Nordwig, A. and Schrag, T. 2000. Modeling and simulation of hybrid systems with SMILE. Informatik, Forschung und Entwicklung.15: 33– 55. Feustel, H.E. and Dieris, J. 1992. A survey of airflow models for multizone Structures. Energy and Buildings. 18: 79-100. Janssen, H.J.J., Speetjens, B., Stigter, H., van Straten, G. and Gieling, Th.H. 2005. Watergy, Infrastructure for Process Control in Semi-arid Regions. Acta Hort. 691:821828. Jolliet, O. 1994. HORTITRANS, A Model for Predicting and Optimizing Humidity and Transpiration in Greenhouses. J. Agric. Eng. Res. 57: 23-37. 557 Jolliet, O., Danloy, L., Gay, J.-B., Munday, G.L. and Reist, A. 1991. HORTICERN. An improved static model for predicting the energy consumption of a greenhouse. Agricultural and Forest Meteorology. 55:265-294 Lee, I., Kang, C., Yun, J., Jeun, J. and Kim, G. 2003. A Study of Aerodynamics in Agriculture. Forum on Bioproduction in East Asia: Technology Development and Opportunities. ASAE Annual Meeting. LasVegas, USA. 27 July. Negrao, C.O.R. 1995. Conflation of Computational Fluid Dynamics and Building Thermal Simulation. PhD Thesis. University of Strathclyde. Glasgow, UK. Nytsch-Geusen, C., Klempin, C., Nunez v. Voigt, J. and Rädler, J. 2003. Integration of CAAD, thermal building simulation and CFD by using the IFC data exchange format. 8th International IBPSA Conference. Eindhoven, NL, p. 967-973 Nytsch-Geusen, C. 2001. Calculation and optimization of the energy efficiency of buildings and their energy within an object oriented simulation environment. PhD thesis, University of Technology Berlin, Germany. Pieters, J.G. and Deltour, J.M. 1999. Modelling solar energy input in greenhouses. Solar Energy. 67(2). Roy, J.C., Boulard, T., Kittas, C. and Wang, S. 2002. Convective and Ventilation Transfers in Greenhouses, Biosystems Engineering. 83(1): 1-20. Figurese Fig. 1. Energy flow in the humid air collector (1: greenhouse, 2: tower for buoyancy, 3: cooling duct, 4: diurnal heat storage, 5:building, 6: seasonal heat storage). 558 4 5 Fig. 2. Water cycle in the humid air collector (1: collected water , 2: irrigation water, 3: water buffer, 4: additional humidification, 5: water use in the building). Fig. 3. Capacities of existing simulation programs to predict the overall behaviour of closed greenhouses or parts of it. 559 Division of the Greenhouse in Zones zone 3 zone 4, 5 and 6 inside the returning duct with the heat exchanger zone 2 zone 1 Fig. 4. The greenhouse is divided in 6 zones. Every zone has its own nodes for temperature, radiation and pressure. soil/plants door (air path) 6) wall 2 tower (air path to zone window 3 window 2 window 1 shading inner roof wall 1 window 4 wall 3 zone 2 (air path) (complete roof) wall 4 Fig. 5. Building elements of the plant zone as a developed view. For every element the material and surface temperatures were calculated and their influence on the enclosed air determined. Due to the non geometric model the location of an element has no influence on the inner air temperature. “Walls” represent the steel construction of the greenhouse. 560