Ricerc@Sapienza

Since the studies by Toms (1946), it is known that a small amount of polymers, few parts per million, drastically reduces the friction drag in turbulent pipes or boundary layers. However, there is still an open debate on the ways turbulence and polymers interact, especially when a significant drag reduction (DR) is achieved. The complexity arises from the coupled multi-scale dynamics of turbulence and polymer chains.

We propose an innovative micro-mechanical model for the interaction of the polymers with a background turbulent flow. The idea consists in considering a multi-mode Finite Extensible Non Linear Elastic (FENE) bead spring model to represent a single effective polymer chain that retains the relevant degrees of freedom (spatial and temporal scales). The population of millions of effective chains is followed in a Lagrangian way and momentum-coupled with the carrier flow exploiting the fact that each bead experiences a drag force when interacting with the solvent. The approach resolves the micro-structure of the suspension achieving momentum coupling at the level of each instantaneous configuration. This avoids infeasible assumptions (Gaussian distribution of the polymer configuration) that are made in pre-averaged models. The proposed approach is thus able to explore a range of parameters that is unreachable to standard methods given their intrinsic numerical instabilities and the relatively poor physical modelling.

The micro-structure of the polymers is actually resolved and needs the calculation of the momentum feedback of millions of beads. This requires specific techniques that have been developed by the research group for particle and bubble laden flows where the Exact Regularized Point Particle (ERPP) has been developed in its hybrid MPI/GPU implementation.

This research will account the feedback effects of each single polymer chain on wall turbulence in a context where the micro-structure of the chains are retained in all their relevant features.