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Journal of the Acoustical Society of America / Volume 121 / Issue 5 / JASA EXPRESS LETTERS

Characterization of uncertainty in outdoor sound propagation predictions a

a Preliminary results from this study were presented in D. K. Wilson, E. L Andreas, J. W. Weatherly, and C. L. Pettit, “Uncertainty in outdoor sound propagation predictions as determined from high-resolution atmospheric simulations,” InterNoise 2006, Honolulu, HI.

J. Acoust. Soc. Am. Volume 121, Issue 5, pp. EL177-EL183 (2007); (7 pages)

D. Keith Wilson1, Edgar L Andreas1, John W. Weatherly1, Chris L. Pettit2, Edward G. Patton3, and Peter P. Sullivan3

1U.S. Army Engineer Research and Development Center, 72 Lyme Rd., Hanover, New Hampshire 03755
2Aerospace Engineering Department, U.S. Naval Academy, 590 Holloway Rd., MS-11B, Annapolis, Maryland 21402
3National Center for Atmospheric Research, P.O. Box 3000, Boulder, Colorado 80307

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Predictive skill for outdoor sound propagation is assessed using high-resolution atmospheric fields from large-eddy simulations (LES). Propagation calculations through the full LES fields are compared to calculations through subsets of the LES fields that have been processed in typical ways, such as mean vertical profiles and instantaneous vertical profiles synchronized to the sound propagation. It is found that mean sound pressure levels can be predicted with low errors from the mean profiles, except in refractive shadow regions. Prediction of sound pressure levels for short-duration events is much less accurate, with errors of 8–10 dB for near-ground propagation being typical.

© 2007 Acoustical Society of America

Acknowledgments

Funding for this project was provided by the U.S. Army Engineer Research and Development Center. The LES were performed under a DoD High Performance Computing Modernization Office Common High-Performance Scalable Software Initiative project managed by David H. Marlin of the U.S. Army Research Laboratory.

Article Outline

  1. Introduction
  2. Description of the atmospheric simulations
  3. Sound propagation calculations and procedure
  4. Results and discussion
    1. Predictability of mean sound levels
    2. Predictability of event sound levels
  5. Conclusions

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KEYWORDS and PACS

Keywords

aeroacoustics, atmospheric acoustics, acoustic wave propagation

PACS

  • 43.28.Gq

    Outdoor sound propagation and scattering in a turbulent atmosphere, and in non-uniform flow fields

  • 43.28.Lv

    Statistical characteristics of sound fields and propagation parameters

ARTICLE DATA

History
Received 11 Jan 2007
Accepted 19 Feb 2007
Revised 13 Feb 2007
Published online 06 Apr 2007
Digital Object Identifier
http://dx.doi.org/10.1121/1.2716159

PUBLICATION DATA

ISSN

0001-4966 (print)  

Publisher

$abstract.society.value is a Member of CrossRef Acoustical Society of America

  1. D. K. Wilson, J. M. Noble, and M. A. Coleman, “Sound propagation in the nocturnal boundary layer,” J. Atmos. Sci. 60, 2473–2486 (2003). [ISI]
  2. P. P. Sullivan, J. C. McWilliams, and C.-H. Moeng, “A subgrid-scale model for large-eddy simulation of planetary boundary-layer flows,” Boundary-Layer Meteorol. 71, 247–276 (1994). [Inspec] [ISI]
  3. M. West, K. Gilbert, and R. A. Sack, “A tutorial on the parabolic equation (PE) model used for long range sound propagation in the atmosphere,” Appl. Acoust. 37, 31–49 (1992). [Inspec] [ISI]
  4. P. Blanc Benon, L. Dallois, and D. Juvé, “Long range sound propagation in a turbulent atmosphere within the parabolic approximation,” Acust. Acta Acust. 87, 659–669 (2001). [ISI]
  5. L. R. Hole and H. M. Mohr, “Modeling of sound propagation in the atmospheric boundary layer: Application of the MIUU mesoscale model,” J. Geophys. Res., [Solid Earth] 104, 11891–11901 (1999).
  6. K. E. Gilbert, R. Raspet, and X. Di, “Calculation of turbulence effects in an upward refracting atmosphere,” J. Acoust. Soc. Am. 87, 2428–2437 (1990)JASMAN000087000006002428000001. [ISI]
  7. T. Yokota, K. Makino, Y. Hirao, K. Yamamoto, Y. Okada, and K. Yoshihisa, “Numerical simulation on outdoor sound propagation under the influence of wind speed gradient by the PE method,” in Proceedings of InterNoise 2006, Honolulu, HI (Institute of Noise Control Engineering of the USA, Inc., 2006).


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FIG.1
(Color online) Errors for mean sound pressure level estimates at 150 Hz in unstable stratification. The left and right halves of the plot are upwind and downwind propagation, respectively, from a source located at 0 m range and 1 m height. (a) Bias error for estimation using ensemble mean vertical profiles. (b) Bias error for averaging propagation predictions from a large number of samples of the vertical profiles. (c) Bias error for estimation from a single, randomly collected set of vertical profiles. (d) Root mean square error corresponding to (c).

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FIG.2
(Color online) Bias errors for mean sound pressure level estimates at 150 Hz based on ensemble mean vertical profiles. Four different atmospheric stratifications are shown. Receiver height is 2 m.

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FIG.3
(Color online) Root mean square errors for estimates of the event sound pressure levels at 150 Hz in unstable stratification by several different methods. (a) Estimation based on ensemble mean vertical profiles. (b) Estimation based on path-averaged vertical profiles. (c) Estimation based on instantaneous vertical profiles at midpoint of the propagation path. (d) Estimation based on instantaneous vertical profiles displaced from the propagation path.

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FIG.4
(Color online) Root mean square errors for estimates of the event sound pressure levels based on instantaneous, displaced vertical profiles. Receiver height is 2 m. Three different frequencies are shown: 50 Hz (top), 150 Hz (middle), 250 Hz (bottom). Solid lines: downwind propagation, stable stratification. Dashed lines: crosswind propagation, neutral stratification. Dotted lines: upwind propagation, unstable stratification.

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