UFR 3-36 Description: Difference between revisions

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{{Demo_UFR_Desc_Intro}}
{{Demo_UFR_Desc_Intro}}
== Review of UFR studies and choice of test case ==
== Review of UFR studies and choice of test case ==
{{Demo_UFR_Desc_Review}}
The present UFR is one of multiple industrially-relevant flow phenomena that are being investigated as part of the European project “HiFi-TURB”, that has received funding from the European Union’s Horizon 2020 research and innovation programs under grant agreement n° 814837. The aim of the project is to use Artificial Intelligence (AI) to modify available turbulence models in order to obtain a more accurate prediction of the key flow features for a range of selected reference test cases. The geometry of this UFR was designed by the Center of Computer Applications in AeroSpace Science and Engineering (C²A²S²E) at the DLR Institute of Aerodynamics and Flow Technology. The key flow feature investigated is a turbulent boundary layer (TBL) subjected to an adverse pressure gradient (APG) over a smooth surface with/without flow separation and reattachment, in which state-of-the-art Reynolds-Averaged Navier-Stokes (RANS) models are known to fail in accurately predicting the flow and which is of importance, e.g. in external aerodynamics. The designed 2D curved step geometry is a generic curved body surface. The 2D geometry allows for a well-defined and computationally affordable Direct Numerical Simulations (DNS). Geometric variations of the test case were designed to achieve attached flow, incipient, moderate and strong separation and computational results were obtained by several project partners using well-known RANS turbulence models as well as DNS computations performed by project partners from the university of Bergamo
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Revision as of 15:48, 1 November 2022

Lib:Create_Ercoftac_Article_Form

Front Page

Description

Test Case Studies

Evaluation

Best Practice Advice

References

Underlying Flow Regime 3-36

Description

Introduction

Give a brief overview of the UFR in question. Describe the main characteristics of the type of flow. In particular, what are the underlying flow physics which characterise this UFR and must be captured by the CFD methods? If the UFR considered here is of special relevance for a particular AC featured in the KB, this should be mentioned.

Review of UFR studies and choice of test case

The present UFR is one of multiple industrially-relevant flow phenomena that are being investigated as part of the European project “HiFi-TURB”, that has received funding from the European Union’s Horizon 2020 research and innovation programs under grant agreement n° 814837. The aim of the project is to use Artificial Intelligence (AI) to modify available turbulence models in order to obtain a more accurate prediction of the key flow features for a range of selected reference test cases. The geometry of this UFR was designed by the Center of Computer Applications in AeroSpace Science and Engineering (C²A²S²E) at the DLR Institute of Aerodynamics and Flow Technology. The key flow feature investigated is a turbulent boundary layer (TBL) subjected to an adverse pressure gradient (APG) over a smooth surface with/without flow separation and reattachment, in which state-of-the-art Reynolds-Averaged Navier-Stokes (RANS) models are known to fail in accurately predicting the flow and which is of importance, e.g. in external aerodynamics. The designed 2D curved step geometry is a generic curved body surface. The 2D geometry allows for a well-defined and computationally affordable Direct Numerical Simulations (DNS). Geometric variations of the test case were designed to achieve attached flow, incipient, moderate and strong separation and computational results were obtained by several project partners using well-known RANS turbulence models as well as DNS computations performed by project partners from the university of Bergamo



Contributed by: Erij Alaya and Cornelia Grabe — Deutsches Luft-und Raumfahrt Zentrum (DLR)

Front Page

Description

Test Case Studies

Evaluation

Best Practice Advice

References


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