Accurate assessment of air-flow in ventilated spaces is of major importance for achieving healthy and comfortable indoor environment conditions. The CFD (Computational Fluid Dynamics) technique is nowadays one of the most used approaches in order to improve the indoor air quality in ventilated environments. Nevertheless, CFD has still two main challenges: turbulence modeling and experimental validation. As a result, the objective of this study is to evaluate the performance of different turbulence models potentially appropriate for the prediction of indoor airflow. Accordingly, results obtained with 6 turbulence models (standard k-ε model, RNG k-ε model, realizable k-ε model, LRN SST k-ω model, transition SST k-ω model and low Reynolds Stress-ω model) are thoroughly validated based on detailed experimental data. The configuration taken into account in this work corresponds to isothermal and anisothermal airflows produced by mixing ventilation systems in small enclosures at low room air changes per hour. In general, the transition SST k-ω model shows the better overall behavior in comparison with measurement values. Consequently, the application of this turbulence model is appropriate for air flows in ventilated spaces, being an interesting option to more sophisticated LES (Large Eddy Simulation) models as it requires less computational resources.
 Hancock, T. (2002). Built Environment (Encyclopedia of Public Health). Retrieved June 19, 2014 from http://www.encyclopedia.com/doc/1G2-3404000130.html
 Rota R., Canossa L. & Nano G. (2001). Ventilation design of industrial premises through CFD modelling. Canadian Journal of Chemical Engineering. 79(1), 80-86.
 Kaji H., Akabayashi S.I. & Sakaguchi J. (2009). CFD analysis for detached house: Study on the ventilation efficiency on constantly ventilated house part 1. Journal of Environmental Engineering. 74(636), 161-168
 Papanikolaou E., Venetsanos A.G., Cerchiara G.M., Carcassi M. & Markatos N. (2011). CFD simulations on small hydrogen releases inside a ventilated facility and assessment of ventilation efficiency. International Journal of Hydrogen Energy. 36(3), 2597-2605
 Kwon K.S., Lee I.B., Han H.T., Shin C.Y., Hwang H.S., Hong S.W., Bitog J.P., Seo I.H. & Han C.P. (2011). Analysing ventilation efficiency in a test chamber using age-of-air concept and CFD technology. Biosystems Engineering. 110(4), 421-433.
 Zhai Z.Q. & Metzger I.D. (2012). Taguchi-Method-Based CFD Study and Optimisation of Personalised Ventilation Systems. Indoor and Built Environment. 21(5), 690-702.
 Yang L., Ye M. & He B.J. (2014). CFD simulation research on residential indoor air quality. Science of the Total Environment.472, 1137-1144.
 Zhuang R., Li X. & Tu J. (2014). CFD study of the effects of furniture layout on indoor air quality under typical office ventilation schemes. Building Simulation. 7(3), 263-275.
 Helmis C.G., Adam E, Tzoutzas J, Flocas H.A., Halios C.H, Stathopoulou O.I., Assimakopoulos V.D., Panis V., Apostolatou M. & Sgouros G. (2007). Indoor air quality in a dentistry clinic. Science of the Total Environment. 377(2), 349-365.
Corgnati S.P. & Perino M. (2013). CFD application to optimise the ventilation strategy of Senate Room at Palazzo Madama in Turin (Italy). Journal of Cultural Heritage. 14(1), 62-69.
 Stathopoulou O. I. & Assimakopoulos V. D. (2008). Numerical Study of the Indoor Environmental Conditions of a Large Athletic Hall Using the CFD Code PHOENICS. Environmental Modeling & Assessment. 13(3), 449-458.
 Yang C., Demokritou P.,Chen Q., Spengler J. & Parsons A. (2000). Ventilation and air quality in indoor ice skating arenas. ASHRAE Transactions, 106, p. 338
 Cheng Y., Niu, J. & Gao N. (2012). Thermal comfort models: A review and numerical investigation. Building and Environment. 47(1), 13-22.
 Lombardi G., Maganzi M., Cannizzo F. & Solinas G. (2009). CFD simulation for the improvement of thermal comfort in cars. Auto Technology. 9(2), 52-56.
 Chen N., Liao S. & Rao Z. (2012). CFD evaluation on the temperature field and thermal comfort of coach in low atmospheric pressure passenger trains with oxygenation at high altitudes. China Railway Science. 33(4), 126-132.
 Sun H., An L., Feng Z. & Long Z. (2014).CFD simulation and thermal comfort analysis in an airliner cockpit. Journal of Tianjin University Science and Technology. 47(4), 298-303.
 Li Y. & Nielsen P.V. (2011).CFD and ventilation research. Indoor Air. 21, 442-453.
 Sørensen D.N. & Nielsen P.V. (2003). Quality control of computational fluid dynamics in indoor environments. Indoor Air. 13, 2-17.
 van Hooff T. Blocken B. & van Heijst G.J.F. (2013). On the suitability of steady RANS CFD for forced mixing ventilation at transitional slot Reynolds numbers. Indoor Air. 23, 236-249.
 Castanet S. (1998). Contribution to the study of ventilation and indoor air quality. Doctoral dissertation, INSA de Lyon, Villeurbanne, France.
 Stamou A. & Katsiris I. (2006). Verification of a CFD model for indoor airflow and heat transfer. Building and Environment. 41, 1171-1181.
 Zhai Z., Zhang Z., Zhang W. & Chen Q.Y. (2007). Evaluation of Various Turbulence Models in Predicting Airflow and Turbulence in Enclosed Environments by CFD: Part 1 - Summary of Prevalent Turbulence Models. HVAC&R Research. 13(6), 853-870.
Zhang Z, Zhang W., Zhigiang J.W. & Chen Q.Y. (2007).Evaluation of Various Turbulence Models in Predicting Airflow and Turbulence in Enclosed Environments by CFD: Part 2-Comparison with Experimental Data from Literature. HVAC&R Research. 13(6), 871-886.
Launder B.E. & Spalding D.B. (1972). Lectures in Mathematical Models of Turbulence. London, England: Academic Press
 Schälin A. & Nielsen P.V. (2004). Impact of turbulence anisotropy near walls in room air flow. Indoor Air. 14(3), 159-168.
Yakhot V. & Orszag S.A. (1986). Renormalisation group analysis of turbulence. Journal of Science Computing. 1(1), 3-51.
 Teodosiu C., Rusaouen G. & Hohotă R. (2003). Influence of boundary conditions uncertainties on the simulation of ventilated enclosures. Numerical Heat Transfer, Part A: Applications - An International Journal of Computation and Methodology. 44, 483-504.
 Hussain S. & Oosthuizen P.H. (2012). Validation of numerical modeling of conditions in an atrium space with a hybrid ventilation system. Building and Environment. 52, 152-161.
 Shih T.H., Liou A., Shabbir A., Yang Z. & Zhu J. (1995). A new k-ε Eddy-Viscosity Model for High Reynolds Number Turbulent Flows - Model Development and Validation. Computers Fluids. 24(3), 227-238.
Menter F.R. (1994). Two-Equation Eddy-Viscosity Turbulence Models for Engineering Applications. AIAA Journal. 32(8), 1598-1605.
Langtry R.B. & Menter F.R. (2009). Correlation-Based Transition Modeling for Unstructured Parallelized Computational Fluid Dynamics Codes. AIAA Journal. 47(12), 2894-2906.
Wilcox D.C. (1998). Turbulence Modeling for CFD. La Canada, California, USA: DCW Industries, Inc.
 Hussain S., Oosthuizen P.H. & Kalendar A. (2012). Evaluation of various turbulence models for the prediction of the airflow and temperature distributions in atria. Energy and Buildings. 48, 18-28.