Large Eddy Simulations: Modeling
ORAL · D31
Presentations
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A novel hybrid two-level and kinetic-eddy simulation model for high Reynolds number wall-bounded turbulent flows
ORAL
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Presenters
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Reetesh Ranjan
Georgia Institute of Technology
Authors
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Reetesh Ranjan
Georgia Institute of Technology
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Achyut Panchal
Georgia Institute of Technology
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Suresh Menon
Georgia Institute of Technology
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Local Variational Germano Identity for Dynamic Large Eddy Simulations based on Finite Elements
ORAL
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Presenters
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Onkar Sahni
Rensselaer Polytechnic Institute
Authors
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Onkar Sahni
Rensselaer Polytechnic Institute
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A simple extension to eddy-viscosity models for Large Eddy Simulations based on tensor decompositions.
ORAL
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Presenters
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Felipe A. V. de Bragança Alves
Univ of Mass - Amherst
Authors
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Felipe A. V. de Bragança Alves
Univ of Mass - Amherst
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Stephen de Bruyn Kops
Univ of Mass - Amherst
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Data-driven deconvolution for the large eddy simulation of Kraichnan turbulence
ORAL
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Presenters
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Romit Maulik
Oklahoma State University
Authors
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Romit Maulik
Oklahoma State University
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Omer San
Oklahoma State Univ, Oklahoma State University
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Adil Rasheed
SINTEF Norway, SINTEF Digital
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Prakash Vedula
University of Oklahoma
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Consistency and accuracy of LES by explicit filtering
ORAL
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Presenters
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Joseph Mathew
Indian Institute of Science
Authors
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Joseph Mathew
Indian Institute of Science
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Sumit Kumar Patel
Indian Institute of Science
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OpenFOAM based Evaluation of PANS Method with Non-Linear Eddy Viscosity Closure for Separated Turbulent Flows
ORAL
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Presenters
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Sagar Saroha
Indian Institute of Technology Delhi
Authors
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Sagar Saroha
Indian Institute of Technology Delhi
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Sawan S. Sinha
Indian Institute of Technology Delhi
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Sunil Lakshmipathy
Gexcon AS
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Abstract Withdrawn
ORAL Withdrawn
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ABSTRACT WITHDRAWN
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Assessment of different cut-off (filter-width) prescription approaches for the scale-resolving PANS method
ORAL
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Presenters
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Branislav Basara
AVL List GmbH
Authors
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Branislav Basara
AVL List GmbH
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Sharath S Girimaji
Texas A&M University, Texas A&M Univ
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Zoran Pavlovic
AVL List GmbH
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The application of data assimilation to combine experimental data and LES for improved state-estimation.
ORAL
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Presenters
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Jeffrey Labahn
Stanford Univ
Authors
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Jeffrey Labahn
Stanford Univ
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Hao Wu
Stanford Univ, Stanford Univ
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Shaun Harris
Stanford Univ, Stanford Univ
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Bruno Coriton
Sandia Natl Labs
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Matthias M. Ihme
Stanford University, Stanford Univ, Department of Mechanical Engineering - Stanford University
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Jonathan H Frank
Sandia Natl Labs, Sandia Natl Labs
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