From Bypass Transition to Flow Control and Data-Driven Turbulence Modeling: An Input-Output Viewpoint

• Published in: Annual review of fluid mechanics 2021-01, Vol.53 (1), p.311-345
• Main Author: Jovanovi, Mihailo R
• Format: Article
• Language: English
• Subjects: convex optimization; flow modeling and control; frequency responses; input-output analysis; physics-aware data-driven modeling; stochastic dynamics; transition to turbulence; turbulent flows
• ISSN: 0066-4189; 1545-4479
• DOI: 10.1146/annurev-fluid-010719-060244

Transient growth and resolvent analyses are routinely used to assess nonasymptotic properties of fluid flows. In particular, resolvent analysis can be interpreted as a special case of viewing flow dynamics as an open system in which free-stream turbulence, surface roughness, and other irregularities provide sources of input forcing. We offer a comprehensive summary of the tools that can be employed to probe the dynamics of fluctuations around a laminar or turbulent base flow in the presence of such stochastic or deterministic input forcing and describe how input-output techniques enhance resolvent analysis. Specifically, physical insights that may remain hidden in the resolvent analysis are gained by detailed examination of input-output responses between spatially localized body forces and selected linear combinations of state variables. This differentiating feature plays a key role in quantifying the importance of different mechanisms for bypass transition in wall-bounded shear flows and in explaining how turbulent jets generate noise. We highlight the utility of a stochastic framework, with white or colored inputs, in addressing a variety of open challenges including transition in complex fluids, flow control, and physics-aware data-driven turbulence modeling. Applications with temporally or spatially periodic base flows are discussed and future research directions are outlined.