Zonal RANS/LES coupling simulation of a transitional and separated flow around an airfoil near stall

Richez, François; Mary, Ivan; Gleize, Vincent; Basdevant, C.

doi:10.1007/s00162-007-0068-8

Cited by 19 publications

(15 citation statements)

References 13 publications

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“…Recent studies demonstrated the benefits of LES on complex flow prediction in turbomachinery applications [16][17] [18] and in helicopter framework where the laminar separation bubble exists, especially near the leading edge in dynamic stall conditions. Richez et al [19] showed that the transition of the suction-side boundary layer via a LSB near the leading edge can be captured by LES as proved by the very good agreement with a linear inviscid instability theory.…”

Section: Introductionmentioning

confidence: 92%

Numerical investigations of separation-induced transition on high-lift low-pressure turbine using RANS and LES methods

Marty

2014

Proceedings of the Institution of Mechanical Engineers, Part A:

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International audienceAt low Reynolds numbers, laminar-turbulent transition occurs on the suction side of high-lift low-pressure turbine blades. The prediction of this flow is an important step in low-pressure turbine design. Thus the laminar-turbulent transition must be modeled or resolved. The flow around the high-lift low-pressure turbine blade T106C is predicted using RANS simulations, without and with transition model, and Large-Eddy Simulations (LES). Large-eddy simulations are performed in order to predict the laminar separation bubble without any laminar-turbulent transition modeling. Only two Reynolds numbers are investigated with LES and the current study concerns also the validation of the turbulent random flow generation technique of Smirnov et al. [1]. Reynolds number and freestream turbulence effects are studied using the analysis of the unsteady behavior of the separated shear layer and the bubble. The steady flow predicted by RANS simulation with transition model and by the time-averaged LES are in good agreement with isentropic Mach number distribution at midspan, except for the lowest Reynolds number (Re 2is = 80 000). For this last case, the separation and transition points are predicted downstream of the experimental points. The spectral analysis of LES results at different locations allows determining specific frequencies of physical mechanisms. Large-eddy simulations are able to predict laminar separation bubble over the high-lift low-pressure turbine blade T106C as RANS simulation with transition model and to capture the Kelvin-Helmholtz instability which is the cause of the transition mechanism

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Section: Introductionmentioning

confidence: 92%

Numerical investigations of separation-induced transition on high-lift low-pressure turbine using RANS and LES methods

Marty

2014

Proceedings of the Institution of Mechanical Engineers, Part A:

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“…The contours of U b , S w , and L t uncertainty contributions to the variance of the time-averaged velocity magnitude are respectively plotted in Figures 9-11 and illustrate the very weak contribution to the global variance of the uncertainty on bulk velocity, swirl number, and turbulence length scale. Figure 12 displays the mean-value contours of the time-averaged axial velocity for the no-swirl configuration computed using the RANS approach and PC (3). With respect to the previously studied configuration, the absence of swirl yields a higher velocity in the centerline region of the flow; note also that back-flow regions appear close to the wall immediately downstream of the expansion.…”

Section: Explanation Of Variancementioning

confidence: 92%

“…Indeed, because the turbulence intensity T i appears to be the most influential uncertain inflow parameter for the high-swirl flow configuration, it is decided to compute the mean flow and its variance when this single inflow parameter is left uncertain; in that case, the size of the stochastic DOE is limited respectively to 8, 16, and 32 for PC(3), PC(4), and PC (5), which makes the convergence study truly affordable. It has been found that the L 2 norm of the variance of the computed velocity fields displays a maximum variation of 1% when using PC(4) instead of PC (3). Once this additional confidence in the results computed using PC(3) is obtained, it is decided to perform in the next section the physical analysis of the flow, including the whole set of uncertain inflow parameters, on the basis of the PC(3) solutions.…”

Section: Convergence Analysis Of the Uncertainty Quantificationmentioning

confidence: 99%

Numerical prediction of turbulent flows using Reynolds‐averaged Navier–Stokes and large‐eddy simulation with uncertain inflow conditions

Congedo

Duprat

Balarac

et al. 2012

Numerical Methods in Fluids

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SUMMARYNumerous comparisons between Reynolds‐averaged Navier–Stokes (RANS) and large‐eddy simulation (LES) modeling have already been performed for a large variety of turbulent flows in the context of fully deterministic flows, that is, with fixed flow and model parameters. More recently, RANS and LES have been separately assessed in conjunction with stochastic flow and/or model parameters. The present paper performs a comparison of the RANS k − ε model and the LES dynamic Smagorinsky model for turbulent flow in a pipe geometry subject to uncertain inflow conditions. The influence of the experimental uncertainties on the computed flow is analyzed using a non‐intrusive polynomial chaos approach for two flow configurations (with or without swirl). Measured quantities including an estimation of the measurement error are then compared with the statistical representation (mean value and variance) of their RANS and LES numerical approximations in order to check whether experiment/simulation discrepancies can be explained within the uncertainty inherent to the studied configuration. The statistics of the RANS prediction are found in poor agreement with experimental results when the flow is characterized by a strong swirl, whereas the computationally more expensive LES prediction remains statistically well inside the measurement intervals for the key flow quantities.Copyright © 2012 John Wiley & Sons, Ltd.

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“…Their simulations demonstrate the ability of the approach to predict aerodynamics and aeroacoustics of the flow. Richez et al 16 performed zonal RANS/LES coupling simulation for transitional and separated flow around an airfoil near stall. They used overlapping RANS and LES zones to cover the computational domain.…”

Section: Previous Studiesmentioning

confidence: 99%

“…= 0.025 <u v >/U 2 (d) − u ′ v ′ /U Mean and second-order statistics for DNS 33 (symbols), embedded LES-RANS with no synthetic turbulence (dash-dot line in blue), with synthetic turbulence and LES interface placed at three fence-heights upstream of the fence (dash line in green), with synthetic turbulence and LES interface placed at six fenceheights upstream of the fence (solid line in red)16 of 17 American Institute of Aeronautics and Astronautics Downloaded by UNIVERSITY OF QUEENSLAND on October 2, 2015 | http://arc.aiaa.org | DOI: 10.Streamlines on the xy-plane, computed using mean and spanwise averaged velocity components, depicting three recirculation regions for the case with the LES interface at −6h. turbulence LES interface at -3h LES interface at -6h DNS…”

mentioning

confidence: 99%

An Embedded LES-RANS Solver for Aerodynamic Simulations

Anupindi

Sandberg

2015

22nd AIAA Computational Fluid Dynamics Conference

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In the current work, we present the development and application of an embedded largeeddy simulation (LES) -Reynolds-averaged Navier Stokes (RANS) solver. The novelty of the present work lies in fully embedding the LES region inside a global RANS region. RANS and LES regions are explicitly coupled through arbitrary mesh interfaces and flow and turbulence quantities are exchanged between them as the solution is advanced. A digital filter method extracting mean flow, turbulent kinetic energy and Reynolds stresses from the upstream RANS interface is used to provide meaningful small scale fluctuations to the LES interface. The framework is developed in the open-source computational fluid dynamics software OpenFOAM. The embedding approach is validated by simulating a spatially developing turbulent channel flow. Thereafter, flow over a surface mounted spanwiseperiodic vertical fence is simulated to demonstrate the importance of DFM and the effect of the location of the RANS-LES interface. In each case, both mean and second-order statistics are compared with the direct numerical simulation (DNS) data from the literature. The streamwise evolution of skin friction coefficient on the wall is compared with the DNS result and the attachment point of the primary recirculation zone behind the fence matches the reference data well. Results indicate that by feeding synthetic turbulence at the LES interface a good match can be obtained for the mean flow quantities. However, in order to obtain a good match for the Reynolds stresses the LES interface needs to be placed sufficiently far upstream, which in the present case was six spoiler-heights before the fence.

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Zonal RANS/LES coupling simulation of a transitional and separated flow around an airfoil near stall

Cited by 19 publications

References 13 publications

Numerical investigations of separation-induced transition on high-lift low-pressure turbine using RANS and LES methods

Numerical investigations of separation-induced transition on high-lift low-pressure turbine using RANS and LES methods

Numerical prediction of turbulent flows using Reynolds‐averaged Navier–Stokes and large‐eddy simulation with uncertain inflow conditions

An Embedded LES-RANS Solver for Aerodynamic Simulations

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