Turbulence: Model Analysis via Statistical and Probabilistic Techniques
ORAL · D34
Presentations
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A probability distribution approach to synthetic turbulence time series
ORAL
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Authors
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Michael Sinhuber
Stanford University
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Eberhard Bodenschatz
Max Planck Institute for Dynamics and Self-Organization, Max Planck Institute for Dynamics and Self Organization, Max Planck Institute f. Dynamics and Self-Organisation, Max Planck Institute for Dynamics and Self-Organisation
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Michael Wilczek
Max Planck Institute for Dynamics and Self-Organization, Max Planck Institute, Max Planck Institute for Dynamics and Self-Organisation
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Non-Gaussian Extension of the Sparse-Direct Interaction Perturbation
ORAL
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Authors
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David Petty
Univ of Illinois - Urbana
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Carlos Pantano
University of Illinois at Urbana-Champaign, Univ of Illinois - Urbana
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Turbulence Model Discovery with Data-Driven Learning and Optimization
ORAL
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Authors
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Ryan King
University of Colorado, Boulder
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Peter Hamlington
University of Colorado - Boulder, University of Colorado, Boulder, Department of Mechanical Engineering, University of Colorado Boulder
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Reducing RANS Model Error Using Random Forest
ORAL
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Authors
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Jian-Xun Wang
Virginia Tech
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Jin-Long Wu
Virginia Tech
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Heng Xiao
Virginia Tech
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Julia Ling
Sandia National Labs
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RANS turbulence model form uncertainty quantification for wind engineering flows
ORAL
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Authors
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Catherine Gorle
Stanford University
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Stephanie Zeoli
University of Mons
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Laurent Bricteux
University of Mons
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Galerkin POD Model Closure with Triadic Interactions by the Maximum Entropy Method
ORAL
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Authors
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Nicolas H\'erouard
School of Engineering and Information Technology, The University of New South Wales, Northcott Drive, Canberra, ACT, 2600.
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Robert K. Niven
The University of New South Wales, School of Engineering and Information Technology, The University of New South Wales, Northcott Drive, Canberra, ACT, 2600, Australia.
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Bernd R. Noack
LIMSI-CNRS, France, LIMSI, CNRS, Paris, France.
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Markus W. Abel
Potsdam University, Ambrosys GmbH, Institute for Physics and Astrophysics, Potsdam University, Potsdam, Germany.
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Michael Schlegel
Institut f\"{u}r Str\"{o}mungsmechanik und Technische Akustik, Technische Universit\"{a}t Berlin, Berlin, Germany
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A single-point model from SO(3) decomposition of the axisymmetric mean-flow coupled two-point equations
ORAL
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Authors
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Timothy Clark
Department of Mechanical Engineering, University of New Mexico, Albuquerque NM
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Robert Rubinstein
Computational Aerosciences Branch, NASA Langley Research Center, Hampton VA
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Susan Kurien
Theoretical Division, Los Alamos National Laboratory, Los Alamos NM
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Rapid Bayesian Inference for Fluid Flow Modeling and Control
ORAL
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Authors
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Robert K. Niven
The University of New South Wales, School of Engineering and Information Technology, The University of New South Wales, Northcott Drive, Canberra, ACT, 2600, Australia.
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Eurika Kaiser
University of Washington
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Bernd R. Noack
LIMSI-CNRS, France, LIMSI, CNRS, Paris, France.
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Louis N. Cattafesta III
Florida State University
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Markus W. Abel
Potsdam University, Ambrosys GmbH, Institute for Physics and Astrophysics, Potsdam University, Potsdam, Germany.
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Laurent Cordier
CNRS - Universit\'e de Poitiers
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On the statistics of backscatter from sub-grid fluctuations at high Reynolds numbers
ORAL
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Authors
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Michele Buzzicotti
Department of Physics \& INFN, University of Rome Tor Vergata, Rome, Italy.
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Hussein Aluie
University of Rochester and Laboratory for Laser Energetics, University of Rochester, Department of Mechanical Engineering, University of Rochester, USA
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Luca Biferale
Department of Physics and INFN, University of Rome, Tor Vergata, University of Rome Tor Vergata, Deparment of Physics, University of Rome Tor Vergata and INFN, Department of Physics \& INFN, University of Rome Tor Vergata, Rome, Italy.
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Fabio Bonaccorso
Department of Physics and INFN, University of Rome, Tor Vergata, Department of Physics \& INFN, University of Rome Tor Vergata, Rome, Italy.
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Moritz Linkmann
Department of Physics \& INFN, University of Rome Tor Vergata, Rome, Italy.
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ABSTRACT WITHDRAWN
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