Leveraging LDV techniques for the investigation of unsteady turbomachinery flows.
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| Title: | Leveraging LDV techniques for the investigation of unsteady turbomachinery flows. |
|---|---|
| Authors: | Gooding, W. J.1 (AUTHOR) wgooding@purdue.edu, Key, N. L.1 (AUTHOR) |
| Source: | Aeronautical Journal. Dec2019, Vol. 123 Issue 1270, p1919-1937. 19p. |
| Abstract: | Steps required for proper acquisition and processing of laser Doppler velocimetry data for turbomachinery research applications are addressed. Turbomachinery applications are difficult due to the small internal passages, high-frequency fluctuations, large turbulence intensities, and strong secondary flows resulting in low overall signal-to-noise ratios and narrowband noise sources that cannot be removed by simple band-pass filters. Special aspects that must be considered for successful and accurate laser Doppler velocimetry studies to be conducted in turbomachinery are discussed. Specifically, the design of the measurement volume size, reflection mitigation, engineering of seed particle size and injection schema, and alignment of the traverse mechanism are addressed in terms of their importance (from literature sources) and the solutions implemented by the authors. These techniques have been applied to successfully obtain three-component, unsteady velocity data in a high-speed centrifugal compressor for aeroengine application. Processing techniques are also presented including a novel mixture-model-based statistical method for narrowband noise isolation developed by the authors. The method, validation steps, and example results are presented, showing the successful rejection of noise with high accuracy, a low failure rate, and a significant reduction in required manual inspection. This newly developed method elucidated flow features that were not clear prior to the noise removal. [ABSTRACT FROM AUTHOR] |
| Copyright of Aeronautical Journal is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 144835928 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Leveraging LDV techniques for the investigation of unsteady turbomachinery flows. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Gooding%2C+W%2E+J%2E%22">Gooding, W. J.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wgooding@purdue.edu</i><br /><searchLink fieldCode="AR" term="%22Key%2C+N%2E+L%2E%22">Key, N. L.</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Aeronautical+Journal%22">Aeronautical Journal</searchLink>. Dec2019, Vol. 123 Issue 1270, p1919-1937. 19p. – Name: Abstract Label: Abstract Group: Ab Data: Steps required for proper acquisition and processing of laser Doppler velocimetry data for turbomachinery research applications are addressed. Turbomachinery applications are difficult due to the small internal passages, high-frequency fluctuations, large turbulence intensities, and strong secondary flows resulting in low overall signal-to-noise ratios and narrowband noise sources that cannot be removed by simple band-pass filters. Special aspects that must be considered for successful and accurate laser Doppler velocimetry studies to be conducted in turbomachinery are discussed. Specifically, the design of the measurement volume size, reflection mitigation, engineering of seed particle size and injection schema, and alignment of the traverse mechanism are addressed in terms of their importance (from literature sources) and the solutions implemented by the authors. These techniques have been applied to successfully obtain three-component, unsteady velocity data in a high-speed centrifugal compressor for aeroengine application. Processing techniques are also presented including a novel mixture-model-based statistical method for narrowband noise isolation developed by the authors. The method, validation steps, and example results are presented, showing the successful rejection of noise with high accuracy, a low failure rate, and a significant reduction in required manual inspection. This newly developed method elucidated flow features that were not clear prior to the noise removal. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Aeronautical Journal is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1017/aer.2019.28 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 1919 Titles: – TitleFull: Leveraging LDV techniques for the investigation of unsteady turbomachinery flows. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Gooding, W. J. – PersonEntity: Name: NameFull: Key, N. L. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2019 Type: published Y: 2019 Identifiers: – Type: issn-print Value: 00019240 Numbering: – Type: volume Value: 123 – Type: issue Value: 1270 Titles: – TitleFull: Aeronautical Journal Type: main |
| ResultId | 1 |
