DNS-based predictive control of turbulence: an optimal benchmark for feedback algorithms

By Thomas R. Bewley, Parviz Moin, Roger Temam. Journal of Fluid Mechanics, 2001

500 citations recorded by the source corpus.

Subfields: Computational Mechanics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/50ad3b51461c21373b4e44d6d892c5733da06eab

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In Computational Mechanics

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Citations in the corpus

Drag and lift reduction of a 3D bluff-body using active vortex generators (2010, background): “The consequence is that the control of wall turbulence (Bewley et al. 2001; Kim 2003) has rarely been tested in automotive aerodynamics compared to the control of separation and large coherent structures (Gad-El-Hak and Bushnell 1991; Greenblatt and Wygnanski 2000).”
Linear feedback control and estimation of transition in plane channel flow (2003, methodology): “Simulation of the nonlinear system The direct numerical simulation code of Bewley et al. (2001) was used to perform simulations of the constant-mass-flux channel flow system.”
Active control of turbulent boundary layers (2003, methodology): “These include control schemes based on qualitative physical arguments (Choi, Moin & Kim 1994; Schoppa & Hussain 1998), formal optimal and sub-optimal control theory ( Bewley, Moin & Temam 2001 ), neural networks (Lee et al. 1997) and reduced-order dynamical representations of the near-wall region of”
Machine Learning for Fluid Mechanics (2019, methodology): “These algorithms are iterative and often require several orders of magnitude more cost function evaluations than gradient based algorithms (Bewley et al. 2001).”
Nonlinear Nonmodal Stability Theory (2018, methodology): “…at each time and performing costly optimization calculations, which can’t be done in real time, so the use of fully nonlinear methods in control are still impractical (e.g. Joslin et al. 1995, 1997, Gunzburger 2000, Bewley et al. 2001, Chevalier et al. 2002, Pralits et al. 2002, Kim & Bewley 2007).”
A general framework for robust control in fluid mechanics (2000, unknown): “When optimized over a sufficiently long time horizon T in a receding-horizon predictive control framework, the performance of such schemes (in the optimal control case) has proven to be excellent even in fully turbulent flows (see [ 10 ], where the drag of a 3D channel flow is reduced to that of the”