Knowledge of temperature stratification in indoor environments is important for occupant thermal comfort and indoor air quality and for the design and evaluation of displacement ventilation systems. This paper presents a detailed and systematic evaluation of the performance of 3D steady Reynolds-Averaged Navier-Stokes (RANS) CFD simulations to predict the temperature stratification within a room with a heat source and two ventilation openings. The indoor air quality within the room is also investigated by assessing the distribution of the age of air. The evaluation is based on validation with full-scale measurements of air temperature. A sensitivity analysis is performed to investigate the impact of computational grid resolution, turbulence model, discretization schemes and iterative convergence on the predicted temperatures and age of air. The results show that steady RANS with the SST k-¿ model can accurately predict the temperature stratification in this particular indoor environment. However, of the five commonly used turbulence models, only the SST k-¿ model and the standard k-¿ model succeed in reproducing the thermal plume structure and the associated thermal stratification, while the three k-e models clearly fail in doing so. In addition, the iterative convergence criteria have a major impact on the predicted age of air, where it is shown that very stringent criteria in terms of scaled residuals are required to obtain accurate results. These required criteria are much more stringent than typical default settings. This paper is intended to contribute to improved accuracy and reliability of CFD simulations for displacement ventilation assessment.