Time-accurate computations of isolated circular synthetic jets in crossflow

Rumsey, Christopher L.; Schaeffler, Norman W.; Milanović, Ivana; Zaman, K. B. M. Q.

doi:10.1016/j.compfluid.2006.09.002

Cited by 28 publications

(4 citation statements)

References 24 publications

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“…URANS was particularly unsuccessful at predicting turbulence quantities. A later publication by Rumsey et al 33 contrasted case 3 with a similar synthetic jet experiment conducted at NASA Glenn Research Center. It was emphasized that there were differences between case 2 PIV and LDV measurements in some regions of the flow, and the URANS computations tended to agree better with the LDV data in those regions.…”

Section: B Urans Methodsmentioning

confidence: 99%

Successes and Challenges for Flow Control Simulations (Invited)

Rumsey

2008

4th Flow Control Conference

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A survey is made of recent computations published for synthetic jet flow control cases from a CFD workshop held in 2004. The three workshop cases were originally chosen to represent different aspects of flow control physics: nominally 2-D synthetic jet into quiescent air, 3-D circular synthetic jet into turbulent boundary-layer crossflow, and nominally 2-D flow-control (both steady suction and oscillatory zero-net-mass-flow) for separation control on a simple wall-mounted aerodynamic hump shape. The purpose of this survey is to summarize the progress as related to these workshop cases, particularly noting successes and remaining challenges for computational methods. It is hoped that this summary will also by extension serve as an overview of the state-of-the-art of CFD for these types of flow-controlled flow fields in general.

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Section: B Urans Methodsmentioning

confidence: 99%

Successes and Challenges for Flow Control Simulations (Invited)

Rumsey

2008

4th Flow Control Conference

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“…Rumsey reported that unsteady RANS (URANS) was particularly unsuccessful to predict turbulence quantities. Rumsey et al emphasized that there were differences between particle image velocimetry (PIV) and laser Doppler velocimetry (LDV) measurements of the current case in some regions of the flow, and the URANS computations tended to agree better with the LDV data in those regions. In confirmation, all turbulence models by the coarse grid of Rumsey in a normal domain size can capture the general character of the flow.…”

Section: Introductionmentioning

confidence: 99%

Numerical prediction of turbulent flow structure generated by a synthetic cross‐jet into a turbulent boundary layer

Javadi

El‐Askary

2011

Numerical Methods in Fluids

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SUMMARY A detailed numerical study using large‐eddy simulation (LES) and unsteady Reynolds‐averaged Navier–Stokes (URANS) was undertaken to investigate physical processes that are engendered in the injection of a circular synthetic (zero‐net mass flux) jet in a zero pressure gradient turbulent boundary layer. A complementary study was carried out and was verified by comparisons with the available experimental data that were obtained at corresponding conditions with the aim of achieving an improved understanding of fluid dynamics of the studied processes. The computations were conducted by OpenFOAM C++, and the physical realism of the incoming turbulent boundary layer was secured by employing random field generation algorithm. The cavity was computed with a sinusoidal transpiration boundary condition on its floor. The results from URANS computation and LES were compared and described qualitatively and quantitatively. There is a particular interest for acquiring the turbulent structures from the present numerical data. The numerical methods can capture vortical structures including a hairpin (primary) vortex and secondary structures. However, the present computations confirmed that URANS and LES are capable of predicting current flow field with a more detailed structure presented by LES data as expected. Copyright © 2011 John Wiley & Sons, Ltd.

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“…3. Unsteady Reynolds-Averaged Navier-Stokes equations were solved using ANSYS CFX as described in [8,26]. The k-ω Shear Stress Transport turbulence model has been found to best simulate dynamic stall [10,23,29] as well as synthetic jet actuation in crossflows [30], and was consequently employed in this study.…”

Section: Methodsmentioning

confidence: 99%

Role of Synthetic Jet Frequency & Orientation in Dynamic Stall Vorticity Creation

Yen

Ahmed

2013

31st AIAA Applied Aerodynamics Conference

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Vorticity creation and its evolution play an important role in the formation of large dynamic stall vortices which cause large excursions in lift, drag and pitching moment on rapidly pitching and oscillating airfoils. While synthetic jets have shown potential in controlling dynamic stall vortices by sustaining lift increases without corresponding drag and pitching moment, their effect on the vorticity creation remains unknown. To address this, high fidelity computational fluid dynamics simulations were conducted to investigate how synthetic jet frequency and orientation alter the dynamic stall leading-edge boundary vorticity flux. Changes in baseline boundary vorticity flux were related to corresponding flow fields to delineate the role of synthetic jets in vorticity creation. Slot orientation was found to play a greater role in altering the amount of vorticity diffused into the flow than actuation frequency. Dynamic stall vortex sizes were found to be directly proportional to the vorticity diffused from the leading-edge and could therefore be effectively manipulated using synthetic jets. The study provides a better understanding of the dynamic stall vorticity creation process and its control using synthetic jets. Nomenclature ‫ܣ‬= synthetic jet amplitude, ‫ݏ݉‬ ିଵ = acceleration ‫ܥ‬ ఓ = synthetic jet momentum coefficient, ሺ݀ ܿ ⁄ ሻ൫ܷ ,௫ ܷ ஶ ⁄ ൯ ଶ ܿ = chord length ݀ = slot width = body force ݂ = airfoil oscillation frequency, ‫ݖܪ‬ ݂ = jet actuation frequency, ‫ݖܪ‬ ݂ ା = non-dimensional actuation frequency, ݂ ‫ݔ‬ ்ா ܷ ஶ ⁄ = unit normal vector pointing out of the flow ܲ = pressure ܴ݁ = chord Reynolds Number, ߩܷ ஶ ܿ ߤ ⁄ ‫ݏ‬ = distance along surface ‫ݐ‬ = time ܷ ,௫ = maximum jet velocity during blowing phase, ‫ݏ݉‬ ିଵ ܷ ஶ = freestream velocity ‫ݔ‬ ்ா = distance from synthetic jet to trailing-edge ߛ = slot orientation ߢ = reduced airfoil oscillation frequency, ߱ܿ 2ܷ ஶ ⁄ ߤ = dynamic viscosity ߩ = density = boundary vorticity flux, ‫ݏ݉‬ ିଶ ࣓ = vorticity ߱ = airfoil angular frequency, 2ߨ݂ ߱ = jet angular frequency, 2ߨ݂

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Time-accurate computations of isolated circular synthetic jets in crossflow

Cited by 28 publications

References 24 publications

Successes and Challenges for Flow Control Simulations (Invited)

Successes and Challenges for Flow Control Simulations (Invited)

Numerical prediction of turbulent flow structure generated by a synthetic cross‐jet into a turbulent boundary layer

Role of Synthetic Jet Frequency & Orientation in Dynamic Stall Vorticity Creation

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