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General Formulation of the Gradient Richardson Number for RANS Modelling

Ströer, Philip and Knopp, Tobias (2023) General Formulation of the Gradient Richardson Number for RANS Modelling. In: AIAA SciTech 2023 Forum, pp. 1-20. AIAA. AIAA Scitech 2023 Forum, 23. - 27. Jan. 2023, National Harbor, MD. doi: 10.2514/6.2023-1801.

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Official URL: https://arc.aiaa.org/doi/pdf/10.2514/6.2023-1801


The present paper deals with a grid-point local and general reformulation of the gradient Richardson number that is used to characterize and quantify mean-streamline curvature and rotation effects inside a fluid flow. In this context, a new computational relation is derived from the classical definition used by Bradshaw. This includes a condition to maintain the directional information which is associated with amplification and damping of turbulence. For this purpose, an in-depth analysis and a comparison with Richardson numbers from the literature are provided. The newly derived equations and terms are eventually verified with the analytical solution using a channel with U-turn test case and a vortex downstream of a delta wing. Moreover, potential areas of applications for the gradient Richardson number in the field of computational fluid dynamics are presented. Besides an application in classical RANS modelling, the usage of the parameter inside the Field Inversion/Machine Learning approach as a flow feature is discussed.

Item URL in elib:https://elib.dlr.de/193837/
Document Type:Conference or Workshop Item (Speech)
Title:General Formulation of the Gradient Richardson Number for RANS Modelling
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Knopp, TobiasUNSPECIFIEDhttps://orcid.org/0000-0002-3161-5353UNSPECIFIED
Date:19 January 2023
Journal or Publication Title:AIAA SciTech 2023 Forum
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 1-20
EditorsEmailEditor's ORCID iDORCID Put Code
Keywords:Mean-Streamline Curvature, Rotation, Gradient Richardson number, Computational Fluid Dynamics, RANS Modelling, Flow Feature, Machine Learning
Event Title:AIAA Scitech 2023 Forum
Event Location:National Harbor, MD
Event Type:international Conference
Event Dates:23. - 27. Jan. 2023
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Efficient Vehicle
DLR - Research area:Aeronautics
DLR - Program:L EV - Efficient Vehicle
DLR - Research theme (Project):L - Digital Technologies
Location: Göttingen
Institutes and Institutions:Institute for Aerodynamics and Flow Technology > CASE, GO
Deposited By: Ströer, Philip
Deposited On:09 Mar 2023 15:34
Last Modified:09 Mar 2023 15:34

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