Optimal eddy viscosity for resolvent-based models of coherent structures in turbulent jets
Ethan Pickering, Georgios Rigas, Oliver T. Schmidt, Denis Sipp, Tim, Colonius

TL;DR
This paper introduces a data-driven method to optimize eddy viscosity in resolvent models of turbulent jets, significantly improving the prediction of coherent structures by aligning models with high-fidelity simulation data.
Contribution
It proposes an optimal eddy-viscosity field derived from data to enhance resolvent model accuracy, and demonstrates that a single calibrated RANS eddy-viscosity model performs nearly as well.
Findings
Optimal eddy viscosity improves mode alignment to over 90%.
Standard RANS eddy-viscosity models with one coefficient are effective.
The method applies across subsonic, transonic, and supersonic jets.
Abstract
Response modes computed via linear resolvent analysis of a turbulent mean-flow field have been shown to qualitatively capture characteristics of the observed turbulent coherent structures in both wall-bounded and free shear flows. To make such resolvent models predictive, the nonlinear forcing term must be closed. Strategies to do so include imposing self-consistent sets of triadic interactions, proposing various source models, or through turbulence modelling. For the latter, several investigators have proposed using the mean-field eddy viscosity acting linearly on the fluctuation field. In this study, a data-driven approach is taken to quantitatively improve linear resolvent models by deducing an optimal eddy-viscosity field that maximizes the projection of the dominant resolvent mode to the energy-optimal coherent structure educed using spectral proper orthogonal decomposition (SPOD)…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
