Flow in a 3D diffuser

Confined flows

Underlying Flow Regime 4-16

Best Practice Advice

Key Physics

The flow in the present three-dimensional diffuser configurations is extremely complex, despite a simple geometry: namely a "through flow" in a duct — with the cross-section of its "central part" exhibiting a certain expansion and having one clearly defined inlet and one clearly defined outlet. The basic feature of the flow is a complex three-dimensional separation pattern being the consequence of an adverse pressure gradient imposed on the flow through a duct expansion. Two diffuser configurations characterized by slightly different expansion geometry but leading to completely different recirculation zone topology have been investigated. The differences are with respect to the separation onset and reattachment (form and position of the 3D separation/reattachment line) — multiple corner separation and corner reattachment — as well as with the shape and size (length, thickness, fraction of the cross-sectional area occupied by separation) of the recirculation pattern. An important prerequisite for a successful reproduction of the separating flow structure in the diffuser section is the correct capturing of the flow in the inlet duct characterized by intensive secondary currents — being normal to the main flow direction — induced by the Reynolds stress anisotropy.

Numerical Issues

Discretization

It is well-known that the accuracy of the spatial and temporal discretization in the LES-framework should be at least of the second-order. DNS results, which we regarded here more as a reference database, were obtained by applying a code with much higher accuracy level. All LES and LES-related simulations were carried out with second-order accurate discretization schemes. The latter simulations imply the application of Hybrid LES/RANS models. These model schemes employ a RANS model, consisting mostly of two additional (for k and ε) equations (e.g., the TUD-HLR model). For the equations governing such turbulent quantities some upwinding can be used by applying the so called "flux blending" technique without noticeable influence on the quality of the results.

Grid resolution and grid quality

It is interesting to note that virtually the best agreement with the reference experimental database was obtained by applying a relatively coarse grid (1.6 and 2.0 Mio. grid cells in total for diffuser 1 and 2 respectively) whose cells were distributed uniformly over the entire solution domain. In this LES simulation performed by the Karlsruhe group (ITS-LES-SM) the standard Smagorinsky model was applied in conjunction with wall functions for wall treatment. There was no specific refinement in the region of separation and reattachment. This example shows that results of high quality (with respect to the time-averaged quantities) can be obtained on a moderate grid size - for diffuser 2 there was no significant difference to the wall-resolving LES with 42.0 Mio. cells. The much finer resolutions applied by HSU-LES-DSM (up to 18 Mio. cells; Dynamic Smagorinsky model was used -DSM) and TUD-LES-DSM (the geometry was meshed with the grid consisting of up to 4 Mio. cells in total) resulted in a very similar outcome with no noticeable improvement compared to the ITS-LES results. The reasons for that lie in the nature of the flow in the present 3D diffuser (see the discussion in 2.3 and 2.4).

Computational domain and boundary conditions

Physical modelling

Turbulence modelling
Transition modelling
Near-wall modelling
Other modelling

Application Uncertainties

Summarise any aspects of the UFR model set-up which are subject to uncertainty and to which the assessment parameters are particularly sensitive (e.g location and nature of transition to turbulence; specification of turbulence quantities at inlet; flow leakage through gaps etc.)

Recommendations for Future Work

Propose further studies which will improve the quality or scope of the BPA and perhaps bring it up to date. For example, perhaps further calculations of the test-case should be performed employing more recent, highly promising models of turbulence (e.g Spalart and Allmaras, Durbin's v2f, etc.). Or perhaps new experiments should be undertaken for which the values of key parameters (e.g. pressure gradient or streamline curvature) are much closer to those encountered in real application challenges.

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