4.6 Article

Extension of Near-Wall Domain Decomposition to Modeling Flows with Laminar-Turbulent Transition

Journal

COMMUNICATIONS IN COMPUTATIONAL PHYSICS
Volume 31, Issue 2, Pages 645-668

Publisher

GLOBAL SCIENCE PRESS
DOI: 10.4208/cicp.OA-2021-0123

Keywords

Domain decomposition; laminar-turbulent transition; interface boundary condition; near-wall flow; low-Reynolds-number model

Ask authors/readers for more resources

The near-wall domain decomposition method (NDD) has been extended to non-equilibrium regimes with laminar-turbulent transition (LTT) for the first time in this paper. By modifying NDD to efficiently consider LTT and implementing intermittency, the capabilities of NDD to model non-equilibrium turbulent flows with transition have been expanded. The performance of the modified NDD approach demonstrates a significant reduction in computational resources needed while maintaining almost the same accuracy of prediction.
The near-wall domain decomposition method (NDD) has proved to be very efficient for modeling near-wall fully turbulent flows. In this paper the NDD is extended to non-equilibrium regimes with laminar-turbulent transition (LTT) for the first time. The LTT is identified with the use of the eN-method which is applied to both incompressible and compressible flows. The NDD is modified to take into account LTT in an efficient way. In addition, implementation of the intermittency expands the capabilities of NDD to model non-equilibrium turbulent flows with transition. Performance of the modified NDD approach is demonstrated on various test problems of subsonic and supersonic flows past a flat plate, a supersonic flow over a compression corner and a planar shock wave impinging on a turbulent boundary layer. The results of modeling with and without decomposition are compared in terms of wall friction and show good agreement with each other while NDD significantly reducing computational resources needed. It turns out that the NDD can reduce the computational time as much as three times while retaining practically the same accuracy of prediction.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available