Application of FUN3D Solver for Aeroacoustic Simulation of a Nose Landing Gear Configuration

Vatsa, Veer N.; Lockard, David P.; Khorrami, Mehdi R.

doi:10.2514/6.2011-2820

Cited by 28 publications

(29 citation statements)

References 30 publications

(37 reference statements)

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“…As reported by Vatsa et al, 15 the resulting near-field solutions from these simulations were found to be in good agreement with measured data from the BART tunnel for surface pressures, and turbulence kinetic energy (TKE) and vorticity fields in wake regions of the gear. However, the accuracy of the predicted farfield noise was found to be less satisfactory, presumably because of the closed-wall tunnel configuration used in the simulations of Ref.…”

Section: Introductionsupporting

confidence: 70%

“…In a previous paper, Vatsa et al 15 examined the same configuration installed in the BART at NASA Langley. 16 A set of three successively finer unstructured tetrahedral grids comprised of approximately 9, 25, and 71 million nodes (54, 150, and 420 million cells) were generated using the VGRID grid generation software 32 for the G550 PDCC-NLG configuration including the tunnel walls.…”

Section: Configuration and Gridsmentioning

confidence: 99%

“…However, the accuracy of the predicted farfield noise was found to be less satisfactory, presumably because of the closed-wall tunnel configuration used in the simulations of Ref. 15. In this paper, we focus on simulating the same landing gear installed in an open-jet tunnel, replicating the test set-up used for experimental measurements of the farfield noise, thus facilitating direct comparison of the predicted noise with measured data.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Aeroacoustic Simulation of a Nose Landing Gear in an Open Jet Facility using FUN3D

Vatsa

Lockard

Khorrami

et al. 2012

18th AIAA/CEAS Aeroacoustics Conference (33rd AIAA Aeroacoustics Conference)

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Numerical simulations have been performed for a partially-dressed, cavity-closed nose landing gear configuration that was tested in NASA Langley's closed-wall Basic Aerodynamic Research Tunnel (BART) and in the University of Florida's open-jet acoustic facility known as UFAFF. The unstructured-grid flow solver, FUN3D, developed at NASA Langley Research center is used to compute the unsteady flow field for this configuration. A hybrid Reynolds-averaged Navier-Stokes/large eddy simulation (RANS/LES) turbulence model is used for these computations. Time-averaged and instantaneous solutions compare favorably with the measured data. Unsteady flowfield data obtained from the FUN3D code are used as input to a Ffowcs Williams-Hawkings noise propagation code to compute the sound pressure levels at microphones placed in the farfield. Significant improvement in predicted noise levels is obtained when the flowfield data from the open jet UFAFF simulations is used as compared to the case using flowfield data from the closed-wall BART configuration.

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Section: Introductionsupporting

confidence: 70%

Section: Configuration and Gridsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Aeroacoustic Simulation of a Nose Landing Gear in an Open Jet Facility using FUN3D

Vatsa

Lockard

Khorrami

et al. 2012

18th AIAA/CEAS Aeroacoustics Conference (33rd AIAA Aeroacoustics Conference)

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“…Various groups are actively pursuing turbulence resolving simulations of the flow over simplified landing gear (nose landing gear and main landing gear). Spalart and co-workers [113,114] have focused on simplified main gear, whereas the NASA and ONERA groups have focused on the nose landing gear (see [115][116][117][118]). Comparisons conducted under the BANC-I and BANC-II workshops provide a perspective on the current status.…”

Section: (Iii) Landing Gear Noisementioning

confidence: 99%

A second golden age of aeroacoustics?

Lele

Nichols

2014

Phil. Trans. R. Soc. A.

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In 1992, Sir James Lighthill foresaw the dawn of a second golden age in aeroacoustics enabled by computer simulations (Hardin JC, Hussaini MY (eds) 1993 Computational aeroacoustics, New York, NY: Springer (doi:10.1007). This review traces the progress in large-scale computations to resolve the noise-source processes and the methods devised to predict the far-field radiated sound using this information. Keeping focus on aviation-related noise sources a brief account of the progress in simulations of jet noise, fan noise and airframe noise is given highlighting the key technical issues and challenges. The complex geometry of nozzle elements and airframe components as well as the high Reynolds number of target applications require careful assessment of the discretization algorithms on unstructured grids and modelling compromises. High-fidelity simulations with 200-500 million points are not uncommon today and are used to improve scientific understanding of the noise generation process in specific situations. We attempt to discern where the future might take us, especially if exascale computing becomes a reality in 10 years. A pressing question in this context concerns the role of modelling in the coming era. While the sheer scale of the data generated by large-scale simulations will require new methods for data analysis and data visualization, it is our view that suitable theoretical formulations and reduced models will be even more important in future.

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“…The underlying mechanisms of noise emissions by landing gears are complex, as shown by various efforts to characterize them via experimentation [1][2][3][4][5][6][7][8][9][10] and/or numerical simulation [11][12][13][14][15][16][17][18]. In particular, some of these past experimental and numerical efforts offered a ground for the present work, which constitutes a step further toward the characterization of the aeroacoustics by landing gears.…”

mentioning

confidence: 99%

Landing Gear Noise Identification Using Phased Array with Experimental and Computational Data

Bulté

Redonnet

2017

AIAA Journal

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In regard to aircraft noise mitigation, this paper focuses on noise emission by a simplified nose landing gear (NLG), whose noise sources are identified by the means of sensor array methods. More precisely, following a former characterization of the aeroacoustics by the NLG via dedicated experiments and computations, the subsequent experimental and numerical noise signals are applied two popular sensor array methods of noise localization, namely, classical beam forming (CBF) and deconvolution approach for the mapping of acoustic sources (DAMAS). The resulting noise source maps are then analyzed from both the points of view of phenomenology (NLG noise generation mechanisms) and methodology (noise localization methods and application). The results show how sensor array methods (more especially DAMAS) are capable of revealing the underlying physics of the NLG noise source mechanisms, whether it is within an experimental or a computational context. This speaks in favor of a more systematic use of sensor array methods for investigating the noise physics of aircraft components.

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Application of FUN3D Solver for Aeroacoustic Simulation of a Nose Landing Gear Configuration

Cited by 28 publications

References 30 publications

Aeroacoustic Simulation of a Nose Landing Gear in an Open Jet Facility using FUN3D

Aeroacoustic Simulation of a Nose Landing Gear in an Open Jet Facility using FUN3D

A second golden age of aeroacoustics?

Landing Gear Noise Identification Using Phased Array with Experimental and Computational Data

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