Data reduction in viscoelastic turbulent channel flows

Monday, October 12, 2009 - 11:00am - 11:40am
EE/CS 3-180
Antony Beris (University of Delaware)
Direct Numerical Simulations (DNS) of turbulent viscoelastic channel flows
typically generate a tremendous volume of information (terabytes per run.
Data reduction is therefore essential in order to allow for an efficient
processing of the data, let alone its preservation for future studies.
However, previous attempts, using a projection of the velocity to the top
Karhunen-Loeve (K-L) modes, failed to produce velocity fields that could
generate the DNS conformation field adequately. In an effort to rectify
this deficiency we investigate here three different approaches that attempt
to introduce small scale information. First, we extended the K-L analysis
that allowed us to use a hybrid measure, based on a weight of the
pseudodissipation and the fluctuating kinetic energy, as a new objective
function. Second, we used a K-L decomposition of the vorticity field using
the enstrophy (average of the square of vorticity fluctuations) as our new
objective function. As a third attempt, we used again the standard velocity
K-L approach, but in the reconstruction stage of the conformation tensor we
compensated by suitably rescaling the Weissenberg number. It is shown here
that, whereas the first two methods fail to give any improvement over the
classical K-L approach, we were able to reconstruct fairly accurately the
conformation field using the third approach, even with a relatively small
set of 1714 K-L modes. The rescaling factor in that method was calculated
objectively, based on the ratio of DNS vs. K-L-reconstructed based estimates
of the extensional deformation rate in the buffer layer. Given that fact,
we hope that this approach can also provide the starting point for future
investigations into low-dimensional modeling of viscoelastic turbulence as
well as other multiscale applications.
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