Large Eddy Simulation for Jet Installation Effects

Paliath, Umesh; Premasuthan, Sachin

doi:10.2514/6.2013-2137

Cited by 18 publications

(14 citation statements)

References 3 publications

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“…22b, we shows the same jet at locations further away, y This explanation is consistent with numerical simulations. The predictions of Paliath & Premasuthan [52], for the same cases that we use in this paper were based on numerical simulations using LES and Ffowcs-- [18] found that in the absence of any linear/non--linear interaction, the predicted polar directivity is cardioid shaped at low frequencies. Any departure from the cardioid symmetry in the directivity pattern then appears in either as asymmetry (about the jet centerline for the polar directivity) or in the appearance of multiple lobes.…”

Section: Applicability Of Rdt Modelmentioning

confidence: 82%

“…Other efforts have focused more on aerofoil applications [48] using Goldstein's (1978) RDT theory [22] to model high frequency noise at low Mach numbers. There have also been a number of numerical studies (Wolf et al [49], Cheung et al [50] and Venugopal et al [51]) in which Large--Eddy simulations were used to predict aerofoil noise and jet--surface interaction with a rectangular jet and flat plate [52].…”

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confidence: 99%

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Effect of de-correlating turbulence on the low frequency decay of jet-surface interaction noise in sub-sonic unheated air jets using a CFD-based approach

Afsar

Leib

Bozak

2017

Journal of Sound and Vibration

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In this paper we extend the Rapid-distortion theory (RDT)-based model derived by Goldstein, Afsar & Leib (J. Fluid Mech., vol. 736, pp. 532-569, 2013) for the sound generated by the interaction of a large-aspect-ratio rectangular jet with the trailing edge of a flat plate to include a more realistic upstream turbulence spectrum that possess a de-correlation (i.e. negative dip) in its space-time structure and use results from three-dimensional Reynolds-Averaged Navier-Stokes (RANS) solutions to determine the mean flow, turbulent kinetic energy and turbulence length & time scales. Since the interaction noise dominates the low-frequency portion of the spectrum, we use an appropriate asymptotic approximation for the Rayleigh equation Green’s function, which enters the analysis, based on a two-dimensional mean flow representation for the jet. We use the model to predict jet-surface interaction noise for a range of subsonic acoustic Mach number jets, nozzle aspect ratios, streamwise and transverse trailing-edge locations and compare them with experimental data. The RANS meanflow computations are also compared with flow data for selected cases to assess their validity. We find that finite de-correlation in the turbulence spectrum increases the low-frequency algebraic decay (the low-frequency “roll-off”) of the acoustic spectrum with angular frequency to give a model that has a pure dipole frequency scaling. This gives better agreement with noise data compared to Goldstein et al. (2013) for Strouhal numbers less than the peak jet-surface interaction noise. For example, through sensitivity analysis we find that there is a difference of 10 dB at the lowest frequency for which data exists (relative to a model without de-correlation effects included) for the highest acoustic Mach number case. Secondly, our results for the planar flow theory provide a first estimate of the low-frequency amplification due to the jet-surface interaction for moderate aspect ratio nozzles when RANS meanflow quantities are used appropriately. This work will hopefully add to noise prediction efforts for aircraft configurations in which the exhaust systems are tightly integrated with the airframe

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Section: Applicability Of Rdt Modelmentioning

confidence: 82%

mentioning

confidence: 99%

Effect of de-correlating turbulence on the low frequency decay of jet-surface interaction noise in sub-sonic unheated air jets using a CFD-based approach

Afsar

Leib

Bozak

2017

Journal of Sound and Vibration

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“…GE Aviation has developed a similar LES based approach (Paliath et al, 2011) to accurately predict the acoustic signature from complex exhaust nozzles and noise control devices such as dual stream and chevron nozzles an example of which can be found in Figure 5. GE Aviation has also extended the predictive capability to canonical jet-installed configurations (Paliath et al, 2013) shown in Figure 5. It is essential to be able to predict and understand the altering of the noise source generation and propagation mechanisms in the presence of forward flight and installation geometries like pylon, wing and flap.…”

Section: Ii1 Exhaust Jet Noisementioning

confidence: 98%

Future Directions of High Fidelity CFD for Aerothermal Turbomachinery Analysis and Design

Laskowski¹,

Kopriva²,

Michelassi³

et al. 2016

46th AIAA Fluid Dynamics Conference

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Computational Fluid Dynamics is a powerful tool used on a daily basis by designers and researchers in the advancement of propulsion technology. As hardware and software technology continue to evolve, the impact on propulsion systems has the potential to be disruptive. With continued development of High Performance Computing, Large Eddy Simulation, High-Order unstructured grid algorithms, optimization and uncertainty quantification it is conceivable that a new frontier of simulation based research, analysis and design capability is in the foreseeable future. In order to accelerate this development collaboration between industry, academia and government labs is required. NomenclatureBR = Bypass Ratio c = Chord Length CFD = Computational Fluid Dynamics DNS = Direct Numerical Simulation HLES = Hybrid Large Eddy Simulation HO = High-Order HPC = High Performance Computing HPC = High Pressure Compressor HPT = High Pressure Turbine IDDES = Improved Delayed Detached Eddy Simulation IDDES-T = Improved Delayed Detached Eddy Simulation with Transition LES = Large Eddy Simulation LPC = Low Pressure Compressor LPT = Low Pressure Turbine Ma = Mach Number 1 Principal Engineer high-fidelity CFD, Advanced Design Tools, 2 MDAO = Multi-Disciplinary Analysis and Optimization OPR = Overall Pressure Ratio Pt = Total Pressure RANS = Reynolds Averaged Navier Stokes Equations Re = Reynolds number Ro = Rossby Number S = Slot Height S1B = Stage 1 Blade S2B = Stage 2 Blade S1N = Stage 1 Nozzle S2N = Stage 2 Nozzle SFC = Specific Fuel Consumption St = Strouhal Number TIT = Turbine Inlet Temperature Tt = Total Temperature TVD = Total Variation Diminishing UQ = Uncertainty Quantification URANS = Unsteady Reynolds Averaged Navier Stokes Equations VKI = von Karman Institute WMLES = Wall-Modeled Large Eddy Simulation WRLES = Wall-Resolved Large Eddy Simulation

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“…A second order kinetic energy preserving (KEP) discretisation [24] is used in space with numerical smoothing adapted for jet simulations. The KEP inviscid cell face flux with additional numerical smoothing is given below by equation (6).…”

Section: Discretisationmentioning

confidence: 99%

“…For complex geometries the optimum FWH surface placement is not clear a priori. Paliath and Premasuthan [6] use a simplified surface that encompasses the entire geometry at a nearly uniform distance. Another method is to base the FWH surface on an iso-surface of mean turbulence kinetic energy [7].…”

mentioning

confidence: 99%

Large-Scale Multifidelity, Multiphysics, Hybrid Reynolds-Averaged Navier–Stokes/Large-Eddy Simulation of an Installed Aeroengine

Tyacke

Mahak

Tucker

2016

Journal of Propulsion and Power

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The aerodynamics and also noise produced by aeroengines is a critical topic in engine design. Hybrid Reynolds-Averaged Navier-Stokes-Large-Eddy Simulation (RANS-LES), is used to investigate the influence of upstream internal geometry on jet flow and noise. The methods are validated using an isolated nozzle. Internal geometry is added using approximated Immersed Boundary Methods (IBMs) and Body Force Methods (BFMs) reducing grid complexity and cost. Installed coaxial nozzles including an intake, wing and flap and internally, the fan, outlet guide vanes (OGVs) and other large features are modelled. These large scale multi-fidelity, multi-physics calculations are shown to reveal substantial new aeroacoustic insights into an installed aeroengine. The turbulence generated internally introduces a complex unsteady nozzle exit flow. This accelerates inner shear layer development moving it one jet diameter upstream and reduces the potential core length by 5%. For the more intense outer shear layer, the effect appears secondary.

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Large Eddy Simulation for Jet Installation Effects

Cited by 18 publications

References 3 publications

Effect of de-correlating turbulence on the low frequency decay of jet-surface interaction noise in sub-sonic unheated air jets using a CFD-based approach

Effect of de-correlating turbulence on the low frequency decay of jet-surface interaction noise in sub-sonic unheated air jets using a CFD-based approach

Future Directions of High Fidelity CFD for Aerothermal Turbomachinery Analysis and Design

Large-Scale Multifidelity, Multiphysics, Hybrid Reynolds-Averaged Navier–Stokes/Large-Eddy Simulation of an Installed Aeroengine

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