A minimal model of self-sustaining turbulence

TL;DR

This paper demonstrates that a highly simplified RNL model, which uses minimal streamwise modes, can sustain turbulence in plane Couette flow, providing insights into the fundamental mechanisms of wall-turbulence with computational efficiency.

Contribution

The study shows that self-sustaining turbulence can be maintained in a minimal RNL model using only a few streamwise modes, simplifying analysis of turbulence mechanisms.

Findings

A small number of streamwise modes support turbulence in RNL.

Single streamwise mode truncation can sustain turbulence.

RNL simulations closely match DNS results.

Abstract

In this work we examine the turbulence maintained in a Restricted Nonlinear (RNL) model of plane Couette flow. This model is a computationally efficient approximation of the second order statistical state dynamics (SSD) obtained by partitioning the flow into a streamwise averaged mean flow and perturbations about that mean, a closure referred to herein as the RNL$_\infty$ model. The RNL model investigated here employs a single member of the infinite ensemble that comprises the covariance of the RNL$_\infty$ dynamics. The RNL system has previously been shown to support self-sustaining turbulence with a mean flow and structural features that are consistent with DNS. This paper demonstrates that the RNL system's self-sustaining turbulent state is supported by a small number of streamwise varying modes, which form the natural support for the self-sustaining process maintaining RNL turbulence. Remarkably, truncation of the RNL system's support to a single streamwise varying mode can suffice to sustain the turbulent state. The close correspondence between RNL simulations and DNS that has been previously observed along with the results presented here suggest that the fundamental mechanisms underlying wall-turbulence can be analyzed using these highly simplified RNL systems.