Comparison of Turbulence Modeling Strategies for Indoor Flows

Abstract

Turbulence modeling techniques are compared for the simulation of low speed indoor air flow in a simple room. The effect of inlet turbulence intensity on the flow field is investigated using the constant coefficient large eddy simulation (LES) model with uniform mean inlet conditions at several levels of inlet turbulence intensities. The results show significant differences between the simulations with laminar inflow conditions and those in which turbulence was introduced at the inlet. For simulations with turbulent inlet conditions, it is noticed that the jet transitions to a state of fully developed turbulence wherein the dynamics of the flow become nearly insensitive to any further increase in the level of inlet turbulence. For laminar flow conditions, it is seen that the jet slowly spreads and mixes with the quiescent room air. As a result, the jet reaches a fully developed turbulent state further away from the inlet relative to the simulations with inlet turbulence. The effect of using experimental inlet profiles is also investigated. It is seen that, close to the inlet, the flow is sensitive to the inflow details, whereas further away from the inlet, these effects become less pronounced. The results from the constant coefficient and the dynamic LES models are compared. The most noticeable differences in the flow occur at the locations where the subgrid-scale’s contribution to the turbulent kinetic energy is highest. Finally, the results from the dynamic LES and the k-ϵ models are compared. It is found that there are significant differences between the two models for the zero inlet turbulence limit where the flow is most probably transitional in nature and turbulence has not yet reached a fully developed state. It is seen that in the laminar inflow case the k-ϵ model predicts a fully turbulent jet very close to the inlet and thus fails to capture the slow development of the jet found in LES. Accordingly, the k-ϵ model results are nearly insensitive to the level of inlet turbulence especially far from the origin of the flow. It is also seen that for cases with nonzero inlet turbulence level, the k-ϵ model predicts the general features of the mean flow reasonably well; however, the k-ϵ model overpredicts the jet spreading rate and the turbulent kinetic energy close to the inlet. Furthermore, the k-ϵ model under predicts the turbulence level near the corner of the ceiling as it fails to capture the complicated mean velocity and turbulent kinetic energy, most likely because of the highly intermittent flow pattern found there in LES.

CFD and ventilation research

“…Different turbulence models for building airflows were evaluated, including Reynolds‐averaged modeling (Chen, 1996; Murakami, 1998; Abdilghanie et al., 2009) and large eddy simulations (Mochida et al., 2005; Béghein et al., 2005). Owing to turbulence modeling difficulties, CFD may not be able to reveal the real physics as in experiments.…”

Computational Fluid Dynamics Study of Molten Steel Flow Patterns and Particle–Wall Interactions Inside a Slide-Gate Nozzle by a Hybrid Turbulent Model

“…[31] The general conservation equation contains a general variable, /, by which a balance between various processes within a finite control volume is made. The momentum, continuity, and turbulence equations can be derived from the following general equation: [11,32] …”

Low-Reynolds number mixing ventilation flows: Impact of physical and numerical diffusion on flow and dispersion

“…Joubert et al (1996) performed CFD simulations for the same case and for the same range of TI (between 4% and 37.4%) and also found no effect on the results. However, Abdilghanie et al (2009) assessed the influence of the inlet TI for a generic enclosure and found local differences of more than 100% for the mean velocities and the velocity fluctuations when comparing the results for inlet turbulence intensities of 5% and 13%. Cao and Meyers (2013) studied mixing ventilation flow in a cubical enclosure and found a clear effect of inlet turbulence conditions on the flow pattern calculated; detachment of the incoming wall jet was delayed with increasing TI (range between 5% and 30%).…”