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The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry
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Published on: August 12, 2013

Broadband trailing edge noise from a sharp-edged strut.

Danielle J Moreau1, Laura A Brooks, Con J Doolan

  • 1School of Mechanical Engineering, The University of Adelaide, Adelaide, South Australia 5005, Australia. danielle.moreau@adelaide.edu.au

The Journal of the Acoustical Society of America
|May 17, 2011
PubMed
Summary
This summary is machine-generated.

This study investigates airflow noise from sharp-edged flat plates at low-to-moderate Reynolds numbers. Existing prediction methods underestimate low-frequency noise, highlighting the need for improved models based on wake flow characteristics.

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Area of Science:

  • Fluid Dynamics
  • Aeroacoustics
  • Aerodynamics

Background:

  • Trailing edge noise is a significant factor in aerodynamic applications.
  • Existing semi-empirical models often fail to accurately predict noise spectra, particularly at lower frequencies.
  • Understanding flow structures in the near wake is crucial for noise prediction.

Purpose of the Study:

  • To present experimental data on flow and noise from sharp-edged flat plates.
  • To evaluate the accuracy of existing semi-empirical trailing edge noise prediction methods.
  • To develop an improved semi-empirical model for predicting trailing edge noise.

Main Methods:

  • Experimental measurements of flow and noise generated by a sharp-edged flat plate.
  • Analysis of velocity spectra in the near wake region.
  • Evaluation of multiple semi-empirical trailing edge noise prediction models.
  • Derivation of a new semi-empirical model for surface pressure spectrum.

Main Results:

  • Experimental data were collected for Reynolds numbers ranging from 2.0 × 10^5 to 5.0 × 10^5.
  • All evaluated semi-empirical methods under-predicted noise at lower frequencies.
  • Energetic velocity fluctuations were observed at low frequencies in the near wake.
  • A new semi-empirical model for the surface pressure spectrum was derived.

Conclusions:

  • Current semi-empirical models are inadequate for predicting trailing edge noise at low-to-moderate Reynolds numbers.
  • Low-frequency velocity fluctuations in the near wake are a key factor influencing noise generation.
  • The derived semi-empirical model offers a potential improvement for trailing edge noise prediction.