title: Impact of turbulence anisotropy near walls in room airflow.
abstract: The influence of different turbulence models used in computational fluid dynamics predictions is studied in connection with room air movement. The turbulence models used are the high Re-number kappa-epsilon model and the high Re-number Reynolds stress model (RSM). The three-dimensional wall jet is selected for the work. The growth rate parallel to the wall in a three-dimensional wall jet is large compared with the growth rate perpendicular to the wall, and it is large compared with the growth rate in a free circular jet. It is shown that it is not possible to predict the high growth rate parallel with a surface in a three-dimensional wall jet by the kappa-epsilon turbulence model. Furthermore, it is shown that the growth rate can be predicted to a certain extent by the RSM with wall reflection terms. The flow in a deep room can be strongly influenced by details as the growth rate of a three-dimensional wall jet. Predictions by a kappa-epsilon model and RSM show large deviations in the occupied zone. Measurements and observations of streamline patterns in model experiments indicate that a reasonable solution is obtained by the RSM compared with the solution obtained by the kappa-epsilon model.
  
  
  CONCLUSIONS
  Computational fluid dynamics (CFD) is often used for the prediction of air distribution in rooms and for the evaluation of thermal comfort and indoor air quality. The most used turbulence model in CFD is the kappa-epsilon model. This model often produces good results; however, some cases require more sophisticated models. The prediction of a three-dimensional wall jet is improved if it is made by a Reynolds stress model (RSM). This model improves the prediction of the velocity level in the jet and in some special cases it may influence the entire flow in the occupied zone.
authors.affiliation: Air Flow Consulting, Zurich, Switzerland.
authors.forename: A
authors.initials: A
authors.lastname: Schälin
authors.forename: P V
authors.initials: PV
authors.lastname: Nielsen
mesh_terms: D000392:Air Movements; D016902:Air Pollution, Indoor / Q000032:analysis; D005544:Forecasting; D008962:Models, Theoretical; D013696:Temperature