Partial-field decomposition analysis of full-scale supersonic jet noise using optimized-location virtual references

Supersonic jet noise reduction efforts benefit from targeted source feature extraction and high-resolution acoustic imaging. Another useful tool for feature extraction is partial field decomposition of sources into independent contributors. Since such decomposition processes are nonunique, care must...

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Veröffentlicht in:The Journal of the Acoustical Society of America 2018-09, Vol.144 (3), p.1356-1367
Hauptverfasser: Wall, Alan T., Gee, Kent L., Leete, Kevin M., Neilsen, Tracianne B., Stout, Trevor A., James, Michael M.
Format: Artikel
Sprache:eng
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Zusammenfassung:Supersonic jet noise reduction efforts benefit from targeted source feature extraction and high-resolution acoustic imaging. Another useful tool for feature extraction is partial field decomposition of sources into independent contributors. Since such decomposition processes are nonunique, care must be taken in the physical interpretation of decomposed partially coherent aeroacoustic fields. The optimized-location virtual reference method (OLVR) is a partial field decomposition designed to extract physically meaningful source and field information through the strategic placement of virtual references within a reconstructed field. The OLVR method is applied here to obtain spatially distinct and ordered partial sources at multiple frequencies of a full-scale, high-performance supersonic jet engine operating at 100% engine power. Partial sources are shown to mimic behaviors of the total source distributions including monotonic growth and decay. Because of finite spatial coherence, multiple partial sources are used to reproduce far-field radiation away from the main lobe, and the number of required sources increases with increasing frequency. An analytical multiwavepacket model is fitted to the partial sources to demonstrate how OLVR partial fields can be leveraged to produce reduced-order models.
ISSN:0001-4966
1520-8524
DOI:10.1121/1.5053580