2.9k citations · 5.6k across the 52 of their papers we have counts for
7 papers · 1 filter
Closed-loop control of an experimental mixing layer using machine learning control
Vladimir Parezanović, Thomas Duriez, Laurent Cordier +6
A novel framework for closed-loop control of turbulent flows is tested in an experimental mixing layer flow. This framework, called Machine Learning Control (MLC), provides a model…
Control Volume Analysis, Entropy Balance and the Entropy Production in Flow Systems
Robert K. Niven, Bernd R. Noack
This chapter concerns "control volume analysis", the standard engineering tool for the analysis of flow systems, and its application to entropy balance calculations. Firstly, the p…
Optimal Nonlinear Eddy Viscosity in Galerkin Models of Turbulent Flows
Bartosz Protas, Bernd R. Noack, Jan Östh
We propose a variational approach to identification of an optimal nonlinear eddy viscosity as a subscale turbulence representation for POD models. The ansatz for the eddy viscosity…
Closed-loop separation control using machine learning
Nicolas Gautier, Thomas Duriez, Jean-Luc Aider +3
A novel, model free, approach to experimental closed-loop flow control is implemented on a separated flow. Feedback control laws are generated using genetic programming where they…
Closed-Loop Turbulence Control Using Machine Learning
Thomas Duriez, Vladimir Parezanović, Laurent Cordier +5
We propose a general model-free strategy for feedback control design of turbulent flows. This strategy called 'machine learning control' (MLC) is capable of exploiting nonlinear me…
Discussion of Di Vita, A., On information thermodynamics and scale invariance in fluid dynamics, Journal of Thermodynamics & Catalysis 3: e108 (2012)
Robert K. Niven, Bernd R. Noack
We respond to two sets of criticisms of our analysis in Noack & Niven, Journal of Fluid Mechanics 700, 187--213 (2012), made by Di Vita, Journal of Thermodynamics & Catalysis, 3: e…