To test various turbulence models for flow over a building, a standard scaled down case of a building, i.e. surface mounted cube, has been used. Experimental data for such a case is widely available in scientific literature, making it convenient to compare the results obtained from CFD simulations.
Several commonly used turbulence models for external flow in the built-environment have been tested:
- RNG: This is a k-e based turbulence model, derived using renormalized group theory. This refines and improves the standard k-e in case of rapidly strained flows.
- SST: This is a hybrid model with both k-omega and k-e. The k-omega model is well suited for simulating flow in the viscous sub-layer. The k-epsilon model is ideal for predicting flow behavior in regions away from the wall. Therefore it can account for the transport of the turbulent shear stress and can accurately predict flow separations under adverse pressure gradients.
- SST-RM: The SST model (like most RANS models) can underpredict turbulent stresses in separating shear layers. This can lead to lower mixing and hence longer separation zones. The SST model is capable of predicting the separation onset well but to improve the prediction of the separated shear layer modification are made to the original SST model. This model is called SST-RM (RM: Reattachment Modification), it introduces additional production of turbulence in the separated shear layer.
- SAS: The Scale-Adaptive Simulation (SAS) is derived by introducing the von Karman length-scale into the turbulence scale equation. The Scale-Adaptive Simulation can then dynamically change to resolved structures in a URANS simulation, as a consequence an LES-like behavior can be observed in unsteady regions of the flow field while still keeping RANS capabilities in stable flow regions.
- DES: This model is developed to overcome the shortcomings of RANS by using LES in certain areas away from the wall boundary layer and using RANS in the near wall regions. This allows the use of LES without having to refine the near wall mesh layer. A blending function is used in the solver which acts as a switch between RANS and LES resolved regions.
A comparison of the results obtained using the above mentioned models with experimental data is presented in the slider below.
The following conclusion are drawn from the comparison of several turbulence models in terms of its use in built-environment:
- Wind climate assessment simulations are generally conducted for large areas, 300-500m radius around the building of interest. At such scales the use of DES or SAS models are computationally very expensive and hence not practical. Amongst the RANS models, all models predict longer wakes but it would be desirable to capture the windward side corners more accurately in order to assess the pedestrian comfort in the high velocity regions (upstream corner) where the climate is more critical. Although the SST-RM models predict the velocity on the top of the cube and wake better, it fails to predict a realistic horse shoe vortex around the corners. For wind studies conducted for large areas, use of RNG or SST turbulence models seems to be the optimal option considering accuracy in predicting relevant aspects and computational cost.
- Built-environment CFD modelling is often used to calculate wind loads on buildings or structures on and around the building. Based in the comparative study conducted for the surface mounted cube, several tips can be used for different scenarios and are listed below:
- In case of objects/structures placed on the windward side of the building like a canopy, a rooftop railing or signage near the leading edge of the building, the use of RNG or SST turbulence models can provide sufficient accuracy in predicting wind loads on these objects.
- For objects mounted on top of the building such as rooftop equipment, a more accurate velocity field can be calculated using the SST-RM turbulence model.
- For buildings or structures in the wake of another building, the wind loads on building/structure in the wake would be highly error prone if RANS models are used. In such cases either an LES/DES/SAS simulations should be performed (if computationally feasible) or a reasonable factor of safety should be assumed to correct the under-estimated forces due to the longer wake that RANS models predict.