A machine learning approach to identifying waveform coalescence in supersonic jet noise
Author:
Affiliation:
1. The University of Texas at Austin Applied Research Laboratories
Publisher
American Institute of Aeronautics and Astronautics
Link
https://arc.aiaa.org/doi/pdf/10.2514/6.2023-3353
Reference27 articles.
1. Piecewise-Spreading Regime Model for Calculating Effective Gol’dberg Numbers for Supersonic Jet Noise
2. Effective Gol'dberg number for diverging waves
3. ‘Crackle’: an annoying component of jet noise
4. Crackle Noise in Heated Supersonic Jets
5. The near-field pressure radiated by planar high-speed free-shear-flow turbulence
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