UFR 3-30 Test Case: Difference between revisions
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In the following, both codes are described briefly. | In the following, both codes are described briefly. | ||
= Finite-volume code LESOCC = | |||
LESOCC solves the (filtered) Navier-Stokes equations based on a | |||
three-dimensional finite | three-dimensional finite-volume method for arbitrary non-orthogonal | ||
and non-staggered block- | and non-staggered block-structured grids (see, e.g.\ | ||
Fig. | Fig. ??). The spatial discretization of all | ||
fluxes is based on central differences of second-order accuracy. Time | fluxes is based on central differences of second-order accuracy. Time | ||
advancement is performed by a predictor--corrector scheme. A | advancement is performed by a predictor--corrector scheme. A | ||
low-storage multi-stage Runge | low-storage multi-stage Runge-Kutta method (three sub-steps, | ||
second-order accuracy) is applied for integrating the momentum | second-order accuracy) is applied for integrating the momentum | ||
equations in the predictor step. Within the corrector step the | equations in the predictor step. Within the corrector step the | ||
Poisson equation for the pressure correction is solved implicitly by | Poisson equation for the pressure correction is solved implicitly by | ||
the incomplete LU decomposition method | the incomplete LU decomposition method. | ||
Explicit time marching works well for DNS and LES with small time | Explicit time marching works well for DNS and LES with small time | ||
steps which are necessary to resolve turbulence motion in time. In | steps which are necessary to resolve turbulence motion in time. In | ||
order to ensure the coupling of pressure and velocity fields on | order to ensure the coupling of pressure and velocity fields on | ||
non-staggered grids, the momentum interpolation technique | non-staggered grids, the momentum interpolation technique is used. | ||
For modeling the non-resolvable subgrid | |||
scales, two different models are implemented, namely the well-known | scales, two different models are implemented, namely the well-known | ||
Smagorinsky model | Smagorinsky model (1963) with Van Driest damping near | ||
solid walls and the dynamic approach with a Smagorinsky base model | solid walls and the dynamic approach with a Smagorinsky base model | ||
proposed by Germano et al. | proposed by Germano et al. (1991) and modified by | ||
Lilly | Lilly (1992). In order to stabilize the dynamic model, | ||
averaging of the numerator and the denominator in the relation for the | averaging of the numerator and the denominator in the relation for the | ||
determination of the Smagorinsky value | determination of the Smagorinsky value was | ||
carried out in the spanwise homogeneous direction and also in time | carried out in the spanwise homogeneous direction and also in time | ||
using a recursive digital low-pass filter | using a recursive digital low-pass filter (Breuer and Rodi 1996, Breuer 2002). | ||
The code and the implemented SGS models were validated on a variety of | The code and the implemented SGS models were validated on a variety of | ||
different test cases. For more information on this issue, please refer | different test cases. For more information on this issue, please refer | ||
Breuer and Rodi (1996), Breuer (1998, 1999, 2002). | |||
Revision as of 18:41, 8 December 2009
2D Periodic Hill
Underlying Flow Regime 3-30
Test Case
Brief Description of the Test Case Studied
The measures of the geometry introduced by Mellen et al. (2000) relate to the hill height h. The hill constricts the channel height of 3.036h by about one third, whereas the inter hill distance is 9h. The contour of the 3.857h long two-dimensional hill is described by the following six polynomials.
At x/h=0 the hill height is maximal, whereas the boundary is flat in the range between x/h=1.929 and x/h=7.071. Between x/h=7.071 and x/h=9 the contour follows the above equations but the hill geometry is mirrored at x/h = 4.5. Besides the geometry, the following figure shows streamlines at a Reynolds number, that is based on the hill height h and the bulk velocity above the crest, of 5,600 [Rapp 2009)].
The mean flow separates at the curved hill crown. In the wake of the hill the fluid recirculates before it attaches naturally at about x/h=4.5.
Experimental Setup
A water channel has been set up in the Laboratory for Hydromechanics of the Technische Universität München to investigate the flow experimentally. In total 10 hills with a height of 50 mm were built into the rectangular channel to accomplish periodicity whilst the measurement range lies between hills seven and eight. To achieve homogeneity in the spanwise direction an extent of 18 hill heights was appointed. The following figure sketches the experimental setup.
The 2D PIV measurements were undertaken between hills seven and eight - and to investigate the periodicity of the flow - between the hill pair six and seven through vertical laser light sheets. The homogeneity in the spanwise direction was controlled by 2D PIV measurements in horizontal planes. The PIV field data was thoroughly validated through 1D LDA measurements. Experiments were done at four Reynolds numbers: Re=5,600; Re=10,600; Re=19,000 and Re=37,000.
CFD Methods
The numerical part of the present study relies on two completely independent codes based on either curvilinear body-fitted grids with a colocated variable arrangement or Cartesian non-uniform grids using a staggered configuration. The objective is to present highly reliable results obtained by carefully cross-checking between the outcome of both numerical schemes and additional experimental data. Afterwards the investigations concentrate on the physical aspects of the flow considered.
In the following, both codes are described briefly.
Finite-volume code LESOCC
LESOCC solves the (filtered) Navier-Stokes equations based on a three-dimensional finite-volume method for arbitrary non-orthogonal and non-staggered block-structured grids (see, e.g.\ Fig. ??). The spatial discretization of all fluxes is based on central differences of second-order accuracy. Time advancement is performed by a predictor--corrector scheme. A low-storage multi-stage Runge-Kutta method (three sub-steps, second-order accuracy) is applied for integrating the momentum equations in the predictor step. Within the corrector step the Poisson equation for the pressure correction is solved implicitly by the incomplete LU decomposition method. Explicit time marching works well for DNS and LES with small time steps which are necessary to resolve turbulence motion in time. In order to ensure the coupling of pressure and velocity fields on non-staggered grids, the momentum interpolation technique is used. For modeling the non-resolvable subgrid scales, two different models are implemented, namely the well-known Smagorinsky model (1963) with Van Driest damping near solid walls and the dynamic approach with a Smagorinsky base model proposed by Germano et al. (1991) and modified by Lilly (1992). In order to stabilize the dynamic model, averaging of the numerator and the denominator in the relation for the determination of the Smagorinsky value was carried out in the spanwise homogeneous direction and also in time using a recursive digital low-pass filter (Breuer and Rodi 1996, Breuer 2002). The code and the implemented SGS models were validated on a variety of different test cases. For more information on this issue, please refer Breuer and Rodi (1996), Breuer (1998, 1999, 2002).
Contributed by: (*) Christoph Rapp, (**) Michael Breuer — (*) Technische Universitat München, (**) Helmut-Schmidt Universität Hamburg
© copyright ERCOFTAC 2009