Finite-difference computations of high reynolds number flows using the dynamic subgrid-scale model

Balaras, Elias; Benocci, C.; Piomelli, Ugo

doi:10.1007/bf00312363

Cited by 50 publications

(37 citation statements)

References 7 publications

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“…Computations of ows in complex domains, frequent cases in engineering applications, are di cult to solve by employing the spectral methods, and are usually performed with ÿnite-di erence or ÿnite-volume methods. Balaras et al [8] studied high-Reynolds-number channel ows with dynamic model combined with a di erence method. They applied approximate boundary conditions and were able to obtain good results with coarse grids.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Smagorinsky‐based subgrid‐scale models in a finite‐volume computation

Majander¹,

Siikonen

2002

Numerical Methods in Fluids

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SUMMARYSmagorinsky-based models are assessed in a turbulent channel ow simulation at Re b = 2800 and Re b = 12 500. The Navier-Stokes equations are solved with three di erent grid resolutions by using a co-located ÿnite-volume method. Computations are repeated with Smagorinsky-based subgrid-scale models. A traditional Smagorinsky model is implemented with a van Driest damping function. A dynamic model assumes a similarity of the subgrid and the subtest Reynolds stresses and an explicit ÿltering operation is required. A top-hat test ÿlter is implemented with a trapezoidal and a Simpson rule. At the low Reynolds number computation none of the tested models improves the results at any grid level compared to the calculations with no model. The e ect of the subgrid-scale model is reduced as the grid is reÿned. The numerical implementation of the test ÿlter in uences on the result. At the higher Reynolds number the subgrid-scale models stabilize the computation. An analysis of an accurately resolved ow ÿeld reveals that the discretization error overwhelms the subgrid term at Re b = 2800 in the most part of the computational domain.

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Section: Introductionmentioning

confidence: 99%

Evaluation of Smagorinsky‐based subgrid‐scale models in a finite‐volume computation

Majander¹,

Siikonen

2002

Numerical Methods in Fluids

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“…Two-layer models, first proposed by Balaras and Benocci [20], use a coarse grid LES up to the wall, but embed a second finer grid for solving the near-wall region with the boundary layer equations, closed with an algebraic eddy viscosity. The Poisson equation is not solved near the wall and the wall normal velocity is obtained by enforcing mass conservation across the interface.…”

Section: /5mentioning

confidence: 99%

Reynolds Stress Structures in the Hybrid RANS/LES of a Planar Channel

Weatheritt

Sandberg

Lozano-Durán

2016

J. Phys.: Conf. Ser.

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“…Reconstruction of the E-field is straightforward from (3). Reconstruction of the Ffield from the H-field, on the other hand, is an ill-posed deconvolution problem and is an inherently noisy process.…”

Section: Blending Function and Reconstructionmentioning

confidence: 99%

“…Hybrid approaches, which combine the strengths of RANS and LES techniques, have become popular in the last decade. In traditional zonal hybrid methods (e.g., Balaras et al [3], Wang and Moin [21], Abe [1], Temmerman et al [19], and Templeton et al [20]), two separate turbulence models-a RANS model in the near-wall region and a subgrid-scale model for LES in outer regions-are used. The solutions in these two regions are then combined at a suitably chosen near-wall crossover location by matching a secondary quantity such as eddy viscosity.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid-Filter Approach to Turbulence Simulation

Rajamani

Kim

2010

Flow Turbulence Combust

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Germano (Theor Comput Fluid Dyn 17:225-331, 2004) proposed a hybridfilter approach, which additively combines an LES-like filter operator (F) and a RANS-like statistical operator (E) using a blending function k: H = kF + (1 − k)E. Using turbulent channel flow as an example, we first conducted a priori tests in order to gain some insights into this hybrid-filter approach, and then performed full simulations to further assess the approach in actual simulations. For a priori tests, two separate simulations, RANS (E) and LES (F), were performed using the same grid in order to construct a hybrid-filtered field (H). It was shown that the extra terms arising out of the hybrid-filtered Navier-Stokes (HFNS) equations provided additional energy transfer from the RANS region to the LES region, thus alleviating the need for the ad hoc forcing term that has been used by some investigators. The complexity of the governing equations necessitated several modifications in order to render it suitable for a full numerical simulation. Despite some issues associated with the numerical implementation, good results were obtained for the mean velocity and skin friction coefficient. The mean velocity profile did not have an overshoot in the logarithmic region for most blending functions, confirming that proper energy transfer from the RANS to the LES region was a key to successful hybrid models. It is shown that Germano's hybrid-filter approach is a viable and mathematically more appealing approach to simulate high Reynolds number turbulent flows.

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Finite-difference computations of high reynolds number flows using the dynamic subgrid-scale model

Cited by 50 publications

References 7 publications

Evaluation of Smagorinsky‐based subgrid‐scale models in a finite‐volume computation

Evaluation of Smagorinsky‐based subgrid‐scale models in a finite‐volume computation

Reynolds Stress Structures in the Hybrid RANS/LES of a Planar Channel

A Hybrid-Filter Approach to Turbulence Simulation

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