UFR 3-36 Best Practice Advice: Difference between revisions
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== Key Physics == | == Key Physics == | ||
The key flow physics to be accurately captured in this UFR are turbulent boundary layers subjected to an adverse pressure gradient over a curved surface with and without separation and reattachment. | The key flow physics to be accurately captured in this UFR are turbulent boundary layers subjected to an adverse pressure gradient over a curved surface with and without separation and reattachment. | ||
== Numerical Modelling == | == Numerical Modelling and Boundary Conditions == | ||
With the DLR-TAU Code a second order discretization for convective fluxes was used including the turbulence model. For grid details please refer to the previous section ("[[Lib:UFR 3-36 Test Case#CFD Methods|CFD Methods]]"). Otherwise, standard rules of grid generation apply. | With the DLR-TAU Code a second order discretization for convective fluxes was used including the turbulence model. For grid details please refer to the previous section ("[[Lib:UFR 3-36 Test Case#CFD Methods|CFD Methods]]"). Otherwise, standard rules of grid generation apply. | ||
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Besides studying the far-field position, three simulations were performed to study the sensitivity of the inlet position: the upstream section of the curved step was extended, a Dirichlet boundary condition was applied and laminar-turbulent transition was considered applying a RANS-based transition transport model. The results showed no significant effect and did not change the incipient character of the flow. | Besides studying the far-field position, three simulations were performed to study the sensitivity of the inlet position: the upstream section of the curved step was extended, a Dirichlet boundary condition was applied and laminar-turbulent transition was considered applying a RANS-based transition transport model. The results showed no significant effect and did not change the incipient character of the flow. | ||
== Physical Modelling == | |||
In the early design phase of the testcase, five different RANS turbulence models already released in the DLR-TAU code and one additional model modification were used for assessment of the flow. | |||
* Four variations of the one-equation Spalart-Allmaras RANS turbulence model: | * Four variations of the one-equation Spalart-Allmaras RANS turbulence model: | ||
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*The seven-equation omega-based Differential Reynolds stress turbulence model SSG/LRR-<math>\omega</math> [‌[[Lib:UFR_3-36_References#16|16]]] including the length scale correction [‌[[Lib:UFR_3-36_References#17|17]]] | *The seven-equation omega-based Differential Reynolds stress turbulence model SSG/LRR-<math>\omega</math> [‌[[Lib:UFR_3-36_References#16|16]]] including the length scale correction [‌[[Lib:UFR_3-36_References#17|17]]] | ||
For the detailed analysis of the flow only the SSG/LRR-<math>\omega</math> model was evaluated, results for the other RANS turbulence models are not given in detail. An indication of the performance of these models is displayed in [[Lib:UFR_3-36_Test_Case#figure8|Fig. 8]] | For the detailed analysis of the flow only the SSG/LRR-<math>\omega</math> model was evaluated, results for the other RANS turbulence models are not given in detail. An indication of the performance of these models is displayed in [[Lib:UFR_3-36_Test_Case#figure8|Fig. 8]]. | ||
<div id="figure8"></div> | <div id="figure8"></div> |
Revision as of 20:44, 15 February 2023
HiFi-TURB-DLR rounded step
Semi-confined flows
Underlying Flow Regime 3-36
Best Practice Advice
Key Physics
The key flow physics to be accurately captured in this UFR are turbulent boundary layers subjected to an adverse pressure gradient over a curved surface with and without separation and reattachment.
Numerical Modelling and Boundary Conditions
With the DLR-TAU Code a second order discretization for convective fluxes was used including the turbulence model. For grid details please refer to the previous section ("CFD Methods"). Otherwise, standard rules of grid generation apply.
To ensure the upper boundary will not influence the flow over the curved wall, a study was performed to find the optimal position for the far-field boundary condition. It was found that a distance to the curved wall less than shows an influence on the computed pressure distributions. With a distance larger than the influence vanishes. These results were generated during the initial design stage of the testcase when a cheaper negative Spalart-Allmaras turbulence model (SA-neg) was applied. Results of this study are given in Fig. 7. Minor deviations (not visible) only vanished for a distance larger than .
Figure 7: Pressure distributions for varying distances of the far-field boundary condition |
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Besides studying the far-field position, three simulations were performed to study the sensitivity of the inlet position: the upstream section of the curved step was extended, a Dirichlet boundary condition was applied and laminar-turbulent transition was considered applying a RANS-based transition transport model. The results showed no significant effect and did not change the incipient character of the flow.
Physical Modelling
In the early design phase of the testcase, five different RANS turbulence models already released in the DLR-TAU code and one additional model modification were used for assessment of the flow.
- Four variations of the one-equation Spalart-Allmaras RANS turbulence model:
- SA-neg [9]
- Non-linear SA-neg model version with rotation and curvature correction (RC) and quadratic constitutive relation (QCR) [10][11]: SA-RC-QCR
- SA model version with Low-Re-modifications [12][13]: SA-LRe
- Non-linear SA-neg model version with rotation and curvature correction (RC) and quadratic constitutive relation (QCR) as well as Low-Re-modifications: SA-RC-QCR-LRe
- Two variations of the two-equation Menter SST RANS turbulence model:
- The seven-equation omega-based Differential Reynolds stress turbulence model SSG/LRR- [16] including the length scale correction [17]
For the detailed analysis of the flow only the SSG/LRR- model was evaluated, results for the other RANS turbulence models are not given in detail. An indication of the performance of these models is displayed in Fig. 8.
Figure 8: Skin friction (left) and pressure coefficient (right) distributions for different RANS turbulence models |
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Application uncertainties
The Reynolds numbers for the testcase were determined, on the one hand, low enough to be affordable for DNS computations and on the other hand, high enough to avoid re-laminarization in the accelerated region of the turbulent boundary layer upstream of the APG region. The latter was ensured by applying two different criteria for possible re-laminarization, the acceleration parameter
as well as the pressure-gradient parameter
and compared to limiting values for re-laminarization according to the literature [24], [25] and [26]. Here, is the friction velocity. Fig. 9 shows the distribution of and for the Reynolds number together with the threshold values for both parameters, not exceeded for this Reynolds number.
Figure 9: Assessment of possible re-laminarization |
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Recommendations for Future Work
This test case was designed to be part of a family of test cases with varying pressure gradient and Reynolds number to provide a comprehensive data base for data-driven turbulence modeling. As soon as DNS data for the other configurations are available, these cases should be added to the test case description and evaluation.
Contributed by: Erij Alaya and Cornelia Grabe — Deutsches Luft-und Raumfahrt Zentrum (DLR)
© copyright ERCOFTAC 2024