Simulation of indoor airflow with RAST and SST-SAS models: A comparative study
indoor airflow, CFD, impinging jet, RAST, sub-grid scale model, hybrid RANS-LES
Computational fluid dynamics (CFD) provides a suitable means to predict the air distribution characteristics in indoor spaces. This paper evaluates the performance of two turbulence models in predicting an indoor airflow: the RAST (Rahman-Agarwal-Siikonen-Taghinia) sub-grid scale model (SGS) and SST-SAS (Shear Stress Transport with Scale-Adaptive Simulation) k-ω model of hybrid RANS-LES type. These two models are applied to investigate the airflows for three ventilation scenarios: (a) forced convection, (b) mixed (natural+forced) convection and (c) isothermal impinging jet in a room. The predictions are compared with the available experimental data in the literature. However, both models produce good results but comparisons show that RAST model predictions are in better agreement with experiments due to its sensitivity toward both the resolved strain rate and vorticity parameters.
Tsinghua University Press
Javad Taghinia, Mizanur Rahman, Timo Siikonen. Simulation of indoor airflow with RAST and SST-SAS models: A comparative study. Build Simul, 2015, 8(3): 297–306.