To study the influence of dynamic interactions between turbulent vortical structures and polymer stress on turbulent friction drag reduction, a series of simulations of channel flow is performed. We obtain self-consistent evolution of an initial eddy in the presence of polymer stresses by utilizing the finitely extensible nonlinear elastic-Peterlin (FENE-P) model. The initial eddy is extracted by the conditional averages for the second quadrant event from fully turbulent Newtonian flow, and the initial polymer conformation fields are given by the solutions of the FENE-P model equations corresponding to the mean shear flow in the Newtonian case. At a relatively low Weissenberg number We τ (=50), defined as the ratio of the polymer relaxation time to the wall time scale, the generation of new vortices is inhibited by polymer-induced countertorques. Thus fewer vortices are generated in the buffer layer. However, the head of the primary hairpin is unaffected by the polymer stress. At larger Weτ values (≥100), the hairpin head becomes weaker and vortex autogeneration and Reynolds stress growth are almost entirely suppressed. The temporal evolution of the vortex strength and polymer torque magnitude reveals that polymer extension by the vortical motion results in a polymer torque that increases in magnitude with time until a maximum value is reached over a time scale comparable to the polymer relaxation time. The polymer torque retards the vortical motion and Reynolds stress production, which in turn weakens flow-induced chain extension and torque itself. An analysis of the vortex time scales reveals that with increasing Weτ, vortical motions associated with a broader range of time scales are affected by the polymer stress. This is qualitatively consistent with Lumley's time criterion for the onset of drag reduction.
|Original language||English (US)|
|Journal||Physical Review E - Statistical, Nonlinear, and Soft Matter Physics|
|State||Published - Jun 4 2013|
ASJC Scopus subject areas
- Condensed Matter Physics
- Statistical and Nonlinear Physics
- Statistics and Probability