H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Mechanical and Aerospace Engineering D-index 36 Citations 8,464 188 World Ranking 729 National Ranking 55

Overview

What is he best known for?

The fields of study he is best known for:

  • Quantum mechanics
  • Artificial intelligence
  • Mechanics

Bernd R. Noack mainly focuses on Mechanics, Wake, Galerkin method, Nonlinear system and Turbulence. Mechanics and Classical mechanics are commonly linked in his work. His Wake research is multidisciplinary, relying on both Drag, Shear flow and Cylinder.

His Galerkin method study combines topics from a wide range of disciplines, such as Mathematical analysis, Laminar flow, Incompressible flow, Compressibility and Applied mathematics. The Nonlinear system study combines topics in areas such as Feature, Lift, Feature vector, Interpretability and Algorithm. His Turbulence research focuses on subjects like Control engineering, which are linked to Artificial neural network and Reduced order.

His most cited work include:

  • A hierarchy of low-dimensional models for the transient and post-transient cylinder wake (764 citations)
  • Machine Learning for Fluid Mechanics (347 citations)
  • Machine Learning for Fluid Mechanics (347 citations)

What are the main themes of his work throughout his whole career to date?

Bernd R. Noack mostly deals with Mechanics, Wake, Turbulence, Control theory and Galerkin method. His Mechanics study frequently intersects with other fields, such as Classical mechanics. His Wake study combines topics in areas such as Laminar flow, Cylinder, Particle image velocimetry, Bluff and Mean flow.

His study on Turbulence also encompasses disciplines like

  • Jet and related Nozzle,
  • Machine learning which is related to area like Flow. Many of his research projects under Control theory are closely connected to Flow control with Flow control, tying the diverse disciplines of science together. The concepts of his Galerkin method study are interwoven with issues in Projection, Attractor, Mathematical analysis, Compressibility and Applied mathematics.

He most often published in these fields:

  • Mechanics (43.93%)
  • Wake (33.24%)
  • Turbulence (35.84%)

What were the highlights of his more recent work (between 2018-2021)?

  • Drag (26.59%)
  • Mechanics (43.93%)
  • Reynolds number (23.12%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Drag, Mechanics, Reynolds number, Turbulence and Boundary layer. His research in Drag intersects with topics in Aerodynamics, Control theory, Reduction, Flow and Wake. His study in Wake is interdisciplinary in nature, drawing from both Bluff, Actuator and Mathematical analysis.

His Mechanics research incorporates elements of Amplitude, Surface wave and Field. Bernd R. Noack works in the field of Reynolds number, namely Vortex shedding. His work deals with themes such as Isotropy, Non-equilibrium thermodynamics, Thermal and Compressibility, which intersect with Turbulence.

Between 2018 and 2021, his most popular works were:

  • Machine Learning for Fluid Mechanics (347 citations)
  • Machine Learning for Fluid Mechanics (347 citations)
  • Cluster-based feedback control of turbulent post-stall separated flows (24 citations)

In his most recent research, the most cited papers focused on:

  • Quantum mechanics
  • Artificial intelligence
  • Mathematical analysis

Bernd R. Noack spends much of his time researching Drag, Control theory, Mechanics, Reynolds number and Reduction. His Drag study integrates concerns from other disciplines, such as Fluidics, Turbulence, Aerodynamics and Boundary layer. His studies deal with areas such as Mathematical analysis and Forcing as well as Turbulence.

His research on Mechanics frequently links to adjacent areas such as Field. His Reynolds number research is multidisciplinary, incorporating perspectives in Flow separation, Wake and Angle of attack. His research integrates issues of Manifold and Vortex shedding in his study of Wake.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

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

Bernd R. Noack;Konstantin Afanasiev;Marek Morzynski;Gilead Tadmor.
Journal of Fluid Mechanics (2003)

870 Citations

On the transition of the cylinder wake

Hong‐Quan Zhang;Uwe Fey;Bernd R. Noack;Michael König.
Physics of Fluids (1995)

453 Citations

Machine Learning for Fluid Mechanics

Steven L. Brunton;Bernd R. Noack;Bernd R. Noack;Petros Koumoutsakos.
Annual Review of Fluid Mechanics (2020)

381 Citations

Arrangement for controlling fluid jets injected into a fluid stream

Fabio R. Bertolotti;David S. Liscinsky;Vincent C. Nardone;Michael K. Sahm.
(2008)

369 Citations

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.
Journal of Fluid Mechanics (2011)

340 Citations

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

Bernd R. Noack;Paul Papas;Peter A. Monkewitz.
Journal of Fluid Mechanics (2005)

336 Citations

Closed-Loop Turbulence Control: Progress and Challenges

Steven L. Brunton;Bernd R. Noack.
Applied Mechanics Reviews (2015)

333 Citations

Feedback shear layer control for bluff body drag reduction

Mark Pastoor;Lars Henning;Bernd R. Noack;Rudibert King.
Journal of Fluid Mechanics (2008)

319 Citations

Reduced-Order Modelling for Flow Control

Bernd R. Noack;Marek Morzynski;Gilead Tadmor.
romf (2013)

281 Citations

A global stability analysis of the steady and periodic cylinder wake

Bernd R. Noack;Helmut Eckelmann.
Journal of Fluid Mechanics (1994)

247 Citations

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