Computational efficiency of CFD modeling for building engineering: An empty domain study

In computational wind engineering, Large Eddy Simulation (LES) operates with superior accuracy. However, this comes with a higher computational cost compared to Reynolds Averaged Navier-Stokes (RANS) models. We propose multiple strategies to reduce the computational cost without compromising accuracy. The turbulence synthesis approach is adopted for efficient inflow generation. To alleviate the issues with tedious and resource-consuming computations, the concept of 'interpolation' is endorsed. This approach allows the usage of identical inflow information for different arrangements of meshing. The effect of employing larger time-step and coarser mesh, on the performance of LES with wall functions, is also investigated. Several LES cases are studied, initially with special near-wall treatment, and later, with three different Subgrid Scale (SGS) models. The profiles of mean velocities, turbulence intensities, and integral length scales are examined, in addition to the velocity spectra. The horizontal homogeneity is assessed for all cases. The results show that the wall-adapting eddy viscosity (WALE) SGS model with LES can reduce the computational time at a lower error range. Besides, among three investigated hybrid models, the Detached Eddy Simulation (DES) and the Delayed Detached Eddy Simulation (DDES) provide a significant reduction in the computational cost, compared to LES with the dynamic one-equation eddy-viscosity SGS model, when the objective is to achieve a similar level of accuracy.

Automated summary

In computational wind engineering, Large Eddy Simulation (LES) offers higher accuracy but comes with increased computational cost compared to Reynolds Averaged Navier-Stokes (RANS) models. Strategies proposed in the study include turbulence synthesis for efficient inflow generation, interpolation concept to reduce tedious computations, and investigation of larger time-step and coarser mesh impact on LES performance. Results suggest that using the wall-adapting eddy viscosity (WALE) SGS model with LES can reduce computational time within an acceptable error range.