World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
57
Citations
16947
World Ranking
788
National Ranking
102

Bernd R. Noack publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Bernd R. Noack sits on this spectrum.

47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 115 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 62 scientists 317–326 publications: 70 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47 publications 659+

This scientist: 335 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

Bernd R. Noack D-index placement in Mechanical and Aerospace Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Mechanical and Aerospace Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Bernd R. Noack sits on this spectrum.

30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 126 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 107 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 100 scientists
30 D-Index 93+

This scientist: 57 D-Index — 77th percentile

77% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

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
Rudibert King
Rudibert King Technical University of Berlin
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
Mark Glauser
Mark Glauser Syracuse University
Peter Jordan
Peter Jordan University of Poitiers

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