Structured input-output analysis of transitional wall-bounded flows

TL;DR

This paper introduces a structured singular value-based input-output analysis method for transitional wall-bounded flows, capturing key nonlinear flow features and structures that traditional unstructured approaches miss.

Contribution

It develops a novel structured analysis framework that preserves nonlinear input-output properties, enabling better prediction of transitional flow structures and phenomena.

Findings

Identifies oblique flow structures requiring least energy for transition.

Captures oblique turbulent bands linked to transition observed in experiments.

Predicts larger amplification of flow structures consistent with DNS and nonlinear analysis.

Abstract

Input-output analysis of transitional channel flows has proven to be a valuable analytical tool for identifying important flow structures and energetic motions. The traditional approach abstracts the nonlinear terms as forcing that is unstructured, in the sense that this forcing is not directly tied to the underlying nonlinearity in the dynamics. This paper instead employs a structured singular value-based approach that preserves certain input-output properties of the nonlinear forcing function in an effort to recover the larger range of key flow features identified through nonlinear analysis, experiments, and direct numerical simulation (DNS) of transitional channel flows. Application of this method to transitional plane Couette and plane Poiseuille flows leads to not only the identification of the streamwise coherent structures predicted through traditional input-output approaches, but also the characterization of the oblique flow structures as those requiring the least energy to induce transition in agreement with DNS studies, and nonlinear optimal perturbation analysis. The proposed approach also captures the recently observed oblique turbulent bands that have been linked to transition in experiments and DNS with very large channel size. The ability to identify the larger amplification of the streamwise varying structures predicted from DNS and nonlinear analysis in both flow regimes suggests that the structured approach allows one to maintain the nonlinear effects associated with weakening of the lift-up mechanism, which is known to dominate the linear operator. Capturing this key nonlinear effect enables the prediction of the wider range of known transitional flow structures within the analytical input-output modeling paradigm.