A differential equation for approximate wall distance

Fares, Ehab; Schröder, Wolfgang

doi:10.1002/fld.348

Cited by 60 publications

(31 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is gotten by the solution of a partial differential equation [12,13,14] , which can be combined with turbulence models and can get more exact normal distance than calculating the minimum distance between discrete points on the wall and the points in the domain if the grid lines are not orthogonal to the surface. The partial differential equation used in this paper is based on the equation derived by Fares [14] .…”

Section: Computations Of Wall Distancesmentioning

confidence: 99%

Application and comparison of SST model in numerical simulation of the axial compressors

et al. 2010

View full text Add to dashboard Cite

The shear-stress transport (SST) turbulence model is incorporated into Navier-Stokes equations to simulate a turbomachinery flowfield. A staggered finite volume method is used to make the mean flow equations and turbulence model equations strongly coupled and enhance the stability of the numerical computation. The implicit treatment of the source terms is applied to the SST model. A steady state solution is obtained using five-stage Runge-Kutta time-stepping scheme with local time stepping and residual smoothing to accelerate convergence.The wall distance d, a key parameter in the SST model, is solved by a partial differential equation. The validations of the code are conducted on rotor 37, wp11 at design and off-design conditions by comparison with measurements and the Spalart-Allmaras (SA) turbulence model. The flow within the tip is calculated with a multi-block grid.

show abstract

Section: Computations Of Wall Distancesmentioning

confidence: 99%

Application and comparison of SST model in numerical simulation of the axial compressors

et al. 2010

View full text Add to dashboard Cite

show abstract

“…However, the new model doesn't require the wall distance. The startup distance calculation is therefore not necessary, which can be expensive in the case of complicated 3D geometries [11]. Using the same stability CFL limit and achieving almost similar convergence rates during the calculation the difference in the CPU time between simulations using the S A and the proposed model was within 4%.…”

Section: Numerical Robustness and Efficiencymentioning

confidence: 91%

A general one-equation turbulence model for free shear and wall-bounded flows

Fares¹,

Schröder²

2005

Flow Turbulence Combust

View full text Add to dashboard Cite

The purpose of this work is to introduce a complete and general one-equation model capable of correctly predicting a wide class of fundamental turbulent flows like boundary layer, wake, jet, and vortical flows. The starting point is the mature and validated two-equation k-ω turbulence model of Wilcox. The newly derived one-equation model has several advantages and yields better predictions than the Spalart-Allmaras model for jet and vortical flows while retaining the same efficiency and quality of the results for near-wall turbulent flows without using a wall distance. The derivation and validation of the new model using findings computed by the Spalart-Allmaras and the k-ω models are presented and discussed for several free shear and wall-bounded flows.

show abstract

“…The nearest normal wall distance, d, is a key parameter in many turbulence modeling and simulation approaches [1,2] and also in peripheral applications incorporating additional solution physics [3,4]. Such examples include explosive front, multiphase flow and electrostatic particle force modeling.…”

Section: Introductionmentioning

confidence: 99%

Finite volume distance field and its application to medial axis transforms

Xia

Tucker

2009

Numerical Meth Engineering

View full text Add to dashboard Cite

SUMMARYAccurate and efficient computation of the nearest wall distance d (or level set) is important for many areas of computational science/engineering. Differential equation-based distance/level set algorithms, such as the hyperbolic-natured Eikonal equation, have demonstrated valuable computational efficiency. Here, in the context, as an 'auxiliary' equation to the main flow equations, the Eikonal equation is solved efficiently with two different finite volume approaches (the cell-vertex and cell-centered). The application of the distance solution is studied for various geometries. Moreover, a procedure using the differential field to obtain the medial axis transform (MAT) for different geometries is presented. The latter provides a skeleton representation of geometric models that has many useful analysis properties. As an alternative to other methods, the current d-MAT procedure bypasses difficulties that are usually encountered by pure geometric methods (e.g. the Voronoi approach), especially in three dimensions, and provides better accuracy than pure thinning methods. It is also shown that the d-MAT approach provides the potential to sculpt/control the MAT form for specialized solution purposes.

show abstract

A differential equation for approximate wall distance

Cited by 60 publications

References 10 publications

Application and comparison of SST model in numerical simulation of the axial compressors

Application and comparison of SST model in numerical simulation of the axial compressors

A general one-equation turbulence model for free shear and wall-bounded flows

Finite volume distance field and its application to medial axis transforms

Contact Info

Product

Resources

About