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BELLIVIER, Axel et al. Low cost simulation as a tool for indoor comfort design. In:CONFERENCE ON PASSIVE AND LOW ENERGY ARCHITECTURE, 20., 2003, Santiago. Anais... Santiago: PLEA, 2003. p. 1 - 6.
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Abstract

 The knowledge and the prediction of the behaviour of heating, ventilation or cooling systems is an important technical and commercial stake. The many different configurations of use for those systems (size of room, functioning restraint, wall types, external conditions ...) often make the experimental caracterization unsuited for such studies. It’s one more field where the numerical simulation can solve many problems. Our aim is to propose a tool craft for architectural design, based on the CFD (Computational Fluid Dynamics) approach. The use of CFD has a strong interest because it gives many informations: airflow patterns, contam- inant transport, temperature distribution, room pressurisation ... On the other hand, it needs strong computers and time ressources. To use it in parametric studies, it is necessary to reduce this calcu- lation cost.There are two complementary ways: the first one is to unrefine the mesh and the second one is to use a simpler turbulence model. Such an approach as already been used for internal studies at ´ Electricit ´ e de France (EDF) with the ESTET code. We generalize this macroscopic CFD approach with a more recent EDF code. In CFD modelisation, a cell is an elementary object. Inside it, quantities are homogeneous. The smaller this object is the more precise and costly the modelisation is. Increasing the cell size is very interesting because it decreases the number of cells and brings larger time steps, decreasing by the way the total simulation time. On the other hand, it looses information about the flow nature inside the cell. One way to make up this loss of information is to use a turbulence model. We use the simpler we can by setting a specific value of the laminar viscosity. It allows to predict average flows in buildings. This is a first step. Our Macroscopic CFD modelling will be improved by the coupling of the zonal models driving flows.
 
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