An outlook on the recently proposed quasi-steady quasi-homogeneous (QSQH) theory of the effect of large-scale structures on the near-wall turbulence is provided. The paper focuses on the selection of the filter, which defines the large-scale structures. It gives a brief overview of the QSQH theory, discusses the filter needed to distinguish between large and small scales, and the related issues of the accuracy of the QSQH theory, describes the probe needed for using the QSQH theory, and outlines the procedure of extrapolating the characteristics of near-wall turbulence from medium to high Reynolds numbers.

Identifying coherent structures of fluid flows is of great importance for reduced order modelling and flow control. Finding such structures in a turbulent flow, however, can be challenging. A number of modal decomposition algorithms have been proposed in recent years which decompose snapshots of data into spatial modes, each associated with a single frequency and growth-rate, most prominently dynamic mode decomposition (DMD). However, the number of modes that DMD-like algorithms construct may be unrelated to the number of significant degrees of freedom of the underlying system. This provides a difficulty if one wants to create a low-order model of a flow. In this work, we present a method of post-processing DMD modes for extracting a small number of dynamically relevant modes. This is achieved by first ranking the DMD modes, then using an iterative approach based on the graph-theoretic notion of maximal cliques to identify clusters of modes and, finally, by replacing each cluster with a single (pair of) modes.