Application of recurrence CFD (rCFD) to species transport in turbulent vortex shedding

Abstract The functionality of computational fluid dynamics (CFD) for turbulent flows is limited by huge computational demands which prevent any detailed long-term studies. In this publication, we apply the recently introduced, data-assisted method “recurrence CFD” (rCFD) to turbulent vortex shedding after a circular cylinder at Reynolds number R e = 3900 . Using a database of flow fields from short, conventional simulations, we time-extrapolate their behavior to arbitrary durations and obtain promising results for passive species transport with speed-up factors of more than 120 at 1 / 20 of the required computer power compared to the underlying large eddy simulation (LES). Besides this massive run-time reduction, we focus on data efficiency. For cases with strong, spatial scale separation, rCFD’s resilience towards grid coarsening allows us to carry out calculations at lower mesh resolution provided one retains meso-scale velocity fluctuations as a contribution to diffusivity. This reduces database size which would otherwise become a bottleneck in the methodology.