Multi-fidelity modelling of shark skin denticle flows: Insights into drag generation mechanisms
Cite this dataset
Lloyd, Charlie et al. (2023). Multi-fidelity modelling of shark skin denticle flows: Insights into drag generation mechanisms [Dataset]. Dryad. https://doi.org/10.5061/dryad.cnp5hqc7z
We investigate the flow over smooth (non-ribletted) shark skin denticles in an open-channel flow using Direct Numerical Simulation (DNS) and two Reynolds Averaged Navier-Stokes (RANS) closures. Large peaks in pressure and viscous drag are observed at the denticle crown edges, where they are exposed to high-speed fluid which penetrates between individual denticles, increasing shear and turbulence. Strong lift forces lead to a positive spanwise torque acting on individual denticles, potentially encouraging bristling if the denticles were not fixed. However, DNS predicts that denticles ultimately increase drag by 58 % compared to a flat plate.
Good predictions of drag distributions are obtained by RANS models, although an underestimation of turbulent kinetic energy production leads to an underprediction of drag. Nevertheless, RANS methods correctly predict trends in the drag data and the regions contributing most to viscous and pressure drag. Subsequently, RANS models are used to investigate the dependence of drag on the flow blockage ratio (boundary layer to roughness height ratio), finding that the drag increase due to denticles is halved when the blockage ratio δ /h is increased from 14 to 45. Our results provide an integrated understanding of the drag over non-ribletted denticles, enabling existing diverse drag data to be explained.
Engineering and Physical Sciences Research Council, Award: EP/L01615X/1