World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
57
Citations
16947
World Ranking
787
National Ranking
102

Overview

Bernd R. Noack is affiliated with the Harbin Institute of Technology in China, where they contribute to research primarily in the field of engineering. Their scholarly work focuses specifically on computational mechanics, aerospace engineering, statistical and nonlinear physics, control and systems engineering, and artificial intelligence.

The scientist's publications emphasize topics including fluid dynamics and turbulent flows, model reduction and neural networks, fluid dynamics and vibration analysis, aerodynamics and acoustics in jet flows, aerodynamics and fluid dynamics research, plasma and flow control in aerodynamics, and lattice Boltzmann simulation studies.

Frequent collaborators in their research include Guy Y. Cornejo Maceda, Nan Deng, Gang Hu, Richard Semaan, and Tamir Shaqarin.

Bernd R. Noack has published extensively in several venues, notably:

  • Physics of Fluids
  • arXiv (Cornell University)
  • Journal of Fluid Mechanics
  • Acta Mechanica Sinica
  • Experiments in Fluids

A selection of recent papers authored or coauthored by Bernd R. Noack demonstrates the focus of their research:

  • Dynamic feature-based deep reinforcement learning for flow control of circular cylinder with sparse surface pressure sensing, 2024, Journal of Fluid Mechanics
  • Deep reinforcement learning-based active flow control of vortex-induced vibration of a square cylinder, 2023, Physics of Fluids
  • DRLinFluids: An open-source Python platform of coupling deep reinforcement learning and OpenFOAM, 2022, Physics of Fluids
  • Cluster-based network modeling-From snapshots to complex dynamical systems, 2021, Science Advances
  • Machine learning strategies applied to the control of a fluidic pinball, 2020, Physics of Fluids

In addition to journal articles, they have contributed to book literature with the publication of xROM: A Toolkit for Reduced-Order Modeling of Fluid Flows in 2020, under the LeoPARD - TU Braunschweig Publications And Research Data imprint.

Best Publications

  • Machine Learning for Fluid Mechanics

    Steven L. Brunton;Bernd R. Noack;Bernd R. Noack;Petros Koumoutsakos

  • A hierarchy of low-dimensional models for the transient and post-transient cylinder wake

    Bernd R. Noack;Konstantin Afanasiev;Marek Morzynski;Gilead Tadmor

  • Closed-Loop Turbulence Control: Progress and Challenges

    Steven L. Brunton;Bernd R. Noack

  • On the transition of the cylinder wake

    Hong‐Quan Zhang;Uwe Fey;Bernd R. Noack;Michael König

  • Three-dimensional coherent structures in a swirling jet undergoing vortex breakdown: stability analysis and empirical mode construction

    Kilian Oberleithner;Moritz Sieber;Christian Nayeri;Christian Paschereit

  • Arrangement for controlling fluid jets injected into a fluid stream of a bleed air discharge nozzle

    Fabio R. Bertolotti;David S. Liscinsky;Vincent C. Nardone;Michael K. Sahm

  • The need for a pressure-term representation in empirical Galerkin models of incompressible shear flows

    Bernd R. Noack;Paul Papas;Peter A. Monkewitz

  • Cluster-based reduced-order modelling of a mixing layer

    Eurika Kaiser;Bernd R. Noack;Laurent Cordier;Andreas Spohn

  • Reduced-Order Modelling for Flow Control

    Bernd R. Noack;Marek Morzynski;Gilead Tadmor

  • Feedback shear layer control for bluff body drag reduction

    Mark Pastoor;Lars Henning;Bernd R. Noack;Rudibert King

  • Machine Learning Control – Taming Nonlinear Dynamics and Turbulence

    Thomas Duriez;Bernd R Noack;Steven L Brunton

  • A global stability analysis of the steady and periodic cylinder wake

    Bernd R. Noack;Helmut Eckelmann

  • Sparse reduced-order modeling : Sensor-based dynamics to full-state estimation

    Jean-Christophe Loiseau;Bernd R. Noack;Steven L. Brunton

  • On closures for reduced order models—A spectrum of first-principle to machine-learned avenues

    Shady E. Ahmed;Suraj Pawar;Omer San;Adil Rasheed

  • Closed-loop separation control using machine learning

    Nicolas Gautier;Thomas Duriez;Jean-Luc Aider;Bernd Noack

  • Recursive dynamic mode decomposition of transient and post-transient wake flows

    Bernard R. Noack;Witold Stankiewicz;Marek Morzyński;Peter J. Schmid

  • Sparse reduced-order modelling: sensor-based dynamics to full-state estimation

    Jean-Christophe Loiseau;Bernd R. Noack;Steven L. Brunton

  • On the need for a nonlinear subscale turbulence term in POD models as exemplified for a high-Reynolds-number flow over an Ahmed body

    Jan Östh;Bernd R. Noack;Siniša Krajnović;Diogo Barros

  • Closed-loop separation control using machine learning

    N. Gautier;J. L. Aider;Thomas Pierre Cornil Duriez;B. R. Noack

  • Low-dimensional modelling of high-Reynolds-number shear flows incorporating constraints from the Navier-Stokes equation

    Maciej J. Balajewicz;Earl H. Dowell;Bernd R. Noack

  • A Novel Model Order Reduction Approach for Navier-Stokes Equations at High Reynolds Number

    Maciej Balajewicz;Earl Dowell;Bernd Noack

  • A low‐dimensional Galerkin method for the three‐dimensional flow around a circular cylinder

    Bernd R. Noack;Helmut Eckelmann

  • Turbulence, Coherent Structures, Dynamical Systems and SymmetryP. Holmes, J. L. Lumley, G. Berkooz, and C. W. Rowley, 2nd ed., Cambridge University Press, Cambridge, England, U.K., 2012, 386 pp., $90

    Bernd R. Noack

Frequent Co-Authors

Gilead Tadmor
Gilead Tadmor Northeastern University
Hans-Christian Hege
Hans-Christian Hege Zuse Institute Berlin
Wolfgang Schröder
Wolfgang Schröder RWTH Aachen University
Sinisa Krajnovic
Sinisa Krajnovic Chalmers University of Technology
Robert J. Martinuzzi
Robert J. Martinuzzi University of Calgary
Christian Oliver Paschereit
Christian Oliver Paschereit Technical University of Berlin
Louis N. Cattafesta
Louis N. Cattafesta Illinois Institute of Technology
Peter Jordan
Peter Jordan University of Poitiers
Israel J Wygnanski
Israel J Wygnanski University of Arizona
Kunihiko Taira
Kunihiko Taira University of California, Los Angeles

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