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Divergence-free turbulent inflow data from realistic covariance tensor

Abstract:

Scale-resolving computational fluid dynamics (CFD) methods require carefully constructed boundary conditions to produce accurate results. The inflow data should be unsteady and the successive realizations must follow specific statistics while ideally having a particular correlation in both space and time. A method for generating synthetic correlated stochastic data from uncorrelated sequences is detailed and applied to the problem of inflow turbulence generation for CFD simulations. The techn...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1063/5.0136568

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
St Catherine's College
Role:
Author
ORCID:
0000-0001-5998-0021
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
St John's College
Role:
Author
ORCID:
0000-0003-2551-2822
Publisher:
AIP Publishing
Journal:
Physics of Fluids More from this journal
Volume:
35
Issue:
2
Article number:
025120
Publication date:
2023-02-09
Acceptance date:
2023-01-24
DOI:
EISSN:
1089-7666
ISSN:
1070-6631

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