UFR 4-16 Evaluation: Difference between revisions

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Brief information on these hs been given in the "Relevant Studies" Section.
Brief information on these hs been given in the "Relevant Studies" Section.


===DNS and LES===
Typical LES results for the two diffusers are shown in  Fig.  26.  The  iso-
contours of the zero mean streamwise velocity component are plotted and  the
mean separation lines are highlighted by white dashed  lines.  Three  highly
complex shaped regions of mean reverse flow can be discerned: SB1,  SB2  and
SB3. SB1 is an artefact of the specific setup shown here, where the  rounded
corners at the inlet of the diffuser were replaced by sharp edges.  SB2  and
SB3 match, within experimental uncertainties, the reference data  of  Cherry
et al. (2008) and, according to Ohlsson et al. (2010), are  even  closer  to
the DNS data than the experiments.





Revision as of 18:26, 1 August 2012

Flow in a 3D diffuser

Front Page

Description

Test Case Studies

Evaluation

Best Practice Advice

References

Confined flows

Underlying Flow Regime 4-16

Evaluation of the results

Both 3D diffuser configurations have served as test cases of the 13th and 14th ERCOFTAC SIG15 Workshops on refined turbulence modelling, Steiner et al. (2009) and Jakirlic et al. (2010b). In addition to different RANS models, the LES and LES-related methods (different seamless and zonal hybrid LES/RANS - HLR - models; DES - Detached Eddy Simulation) were comparatively assessed (visit www.ercoftac.org; under SIG15); the comparative analysis of selected results is presented in the section "Cross- Comparison of CFD calculations with experimental results" of the present contribution. Before starting with the latter, some key physical characteristics illustrated appropriately are discussed as follows.

Physical issues/characteristics of the flow in a 3D diffuser

Here an overview of the most important flow features posing a special challenge to the turbulence modeling is given. Their correct capturing is of decisive importance with respect to the quality of the final results. In order to illustrate these phenomena the experimental and DNS results are used along with some results obtained by LES, hybrid LES/RANS and RANS methods by the groups participating at the SIG15 workshop.

Developed ("equilibrium") flow in the inflow duct / secondary currents

Fig. 20 depicts the linear plot of the axial velocity component across the central plane (z/B=0.5) of the inflow duct at x/h=-2 obtained experimentally indicating a symmetric profile. The inflow conditions correspond clearly to those typical for a fully-developed, equilibrium flow. This is provided by a long inflow duct whose length corresponds to 62.9 channel heights. Fig. 21 shows the semi-log plot of the axial velocity component across the central plane (z/B=0.5) of the inflow duct at x/h=-2. The velocity profile shape obtained by DNS follows closely the logarithmic law, despite a certain departure from it. This departure, expressed in terms of a slight underprediction of the coefficient B in the log-law ([pic] with B=5.2), can also be regarded as a consequence of the back- influence of the adverse pressure gradient evoked by the flow expansion. The pressure coefficient evolution, displayed in Fig. 24, reveals a related pressure increase already in the inflow duct ([pic]). The LES and HLR results (Jakirlic et al., 2010a) exhibit a certain overprediction of the velocity in the logarithmic region. This seems to indicate that the grid may not have been fine enough. On the other hand, the corresponding underprediction of the friction velocity U?, serving here for the normalization - [pic], contributed also to such an outcome (the quantitative information about the U? velocity can be extracted from the friction factor evolution, Fig. 14 in the chapter "Test case studied").

Adverse Pressure Gradient (APG) effects

The boundary layer separation is the direct consequence of the Adverse Pressure Gradient imposed on the duct flow by expanding the cross-section area. The following figures should give the potential practitioners insight into the topology and magnitude of the pressure recovery within the diffuser section. Fig. 24-upper displays the non-dimensional pressure gradient p+=? dp/dx / (?U3?) used traditionally to characterize the intensity of the pressure increase in a boundary layers subjected to APG. Accordingly, the displayed results enable a direct comparison with some APG boundary layer experiments. E.g., the range of p+ between 0.01-0.025 was documented in the Nagano et al. (1993) experiments, indicating a much lower level than in the present diffuser. Although the results presented were extracted from the LES and Hybrid LES/RANS simulations their quality is of a fairly high level, keeping in mind good agreement of the near-wall velocity field (see the section "Cross-Comparison of CFD calculations with experimental results"), skin-friction (Fig. 14 in the chapter "Test case studied") and surface pressure (Fig. 24-lower) development with the reference experimental and DNS results.

Cross-comparison of CFD calculations with experimental results

The present cross-comparison of the results obtained by different calculation methods in the DNS, LES, RANS, zonal and seamless Hybrid LES/RANS (including DES) frameworks is based to a large extent on the activity conducted within the two previously-mentioned ERCOFTAC-SIG15 Workshops on Refined Turbulence Modelling, Steiner et al. (2009) and Jakirlic et al. (2010b), see "List of References". A large amount of simulation results along with detailed comparison with the experimentally obtained reference data has been assembled. The diversity of the models/methods applied can be seen from Tables 1 and 2 (Section: Test Case Studied). The specification of the models used as well as further computational details - details about the numerical code used, discretization schemes/code accuracy, grid arrangement/resolution, temporal resolution, details about the inflow (also about fluctuating inflow generation where applicable) and outflow conditions, etc. - are given in the short summaries provided by each computational group, which can be downloaded (see the appropriate link to the "workshop proceedings" at the end of this file).

In this section, a short summary of some specific outcomes and the most important conclusions are given. The presentation of results and corresponding discussion is given separately for DNS/LES, hybrid LES/RANS (HLR) and RANS methods. The analysis of the results obtained was conducted with respect to the size and shape of the flow separation pattern and associated mean flow and turbulence features: pressure redistribution along the lower non-deflected wall, axial velocity contours, axial velocity and Reynolds stress component profiles at selected streamwise and spanwise positions.

Here, just a selection of the results obtained will be shown and discussed. At the end of the section links are given to the files (the "workshop proceedings") comprising among others the detailed descriptions of the numerical methods and turbulence models used by all participating groups as well as the complete cross-comparisons of all reference and computational results concerning the mean velocity and turbulence fields at vertical planes at two spanwise positions (z/B=1/2 and z/B=7/8) and fifteen streamwise positions.

In the meantime a number of additional computational studies dealing with the flow in the present 3D diffuser configurations have been published. Brief information on these hs been given in the "Relevant Studies" Section.

DNS and LES

Typical LES results for the two diffusers are shown in Fig. 26. The iso- contours of the zero mean streamwise velocity component are plotted and the mean separation lines are highlighted by white dashed lines. Three highly complex shaped regions of mean reverse flow can be discerned: SB1, SB2 and SB3. SB1 is an artefact of the specific setup shown here, where the rounded corners at the inlet of the diffuser were replaced by sharp edges. SB2 and SB3 match, within experimental uncertainties, the reference data of Cherry et al. (2008) and, according to Ohlsson et al. (2010), are even closer to the DNS data than the experiments.





Contributed by: Suad Jakirlić, Gisa John-Puthenveettil — Technische Universität Darmstadt

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Evaluation

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References


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