UFR 3-36

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Semi-confined Flows

Underlying Flow Regime 3-36

Abstract

The Underlying Flow Regime (UFR) studied here, is a Turbulent Boundary layer (TBL) subjected to an adverse pressure gradient (APG) inducing flow separation on a smooth curved surface. The physically and industrially significant flow phenomenon remains challenging to predict with state-of-the-art RANS turbulence models despite the numerous existing experimental and numerical studies. Popular examples are the 2D NASA Wall-mounted Hump of Greenblatt et al. [‌1][‌2] as well as the curved backward facing step [‌3][‌4]. For both cases, experimental data, LES/DNS-data as well as results from RANS turbulence models exist [‌4][‌5].

In contrast to the latter test cases, the UFR described here was designed by the German Aerospace Center (DLR) as a purely numerical test case that cannot be directly transferred to a wind tunnel experiment. The geometry is part of a family of four different geometries, each with two different Reynolds numbers ( and ) based on the step height H. The objective is to provide a test case suitable for DNS computations to generate a comprehensive database that can be exploited by data-driven approaches employing Machine Learning (ML). The final designs are based on a study applying several state-of-the-art Reynold-Averaged Navier-Stokes (RANS) models as well as on an experimental test case designed by NASA [‌6].

From the four different configurations designed for the purpose and the two different Reynolds numbers, only one test case is discussed here. The configuration presents a moderate APG which results in an incipient separation flow in the step region. For this configuration RANS simulations are performed using a Reynolds Stress model by DLR and a two-equation model by the University of Bergamo (UniBg). Additionally, uDNS computations are performed and made available by UniBg.




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

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Description

Test Case Studies

Evaluation

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References


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