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LES loss prediction in an axial compressor cascade at off-design incidences with free stream disturbances

LES loss prediction in an axial compressor cascade at off-design incidences with free stream disturbances
LES loss prediction in an axial compressor cascade at off-design incidences with free stream disturbances
It is well known that an axial compressor cascade will exhibit variation in loss coefficient, described as a loss bucket, when run over a sweep of incidences, and that higher levels of free stream turbulence are likely to suppress separation bubbles and cause earlier transition (see e.g. [23]). However, it remains difficult to achieve accurate quantitative prediction of these changes using numerical simulation, particularly at off-design conditions, without the added computational expense of using eddy-resolving techniques. The aim of the present study is to investigate profile losses in an axial compressor under such conditions using wall-resolved Large Eddy Simulation (LES) and RANS. The work extends on previous work by Leggett et al.[11] with the intention of furthering our understanding of loss prediction tools and improving our quantification of the physical processes involved in loss generation. The results show that while RANS predicts losses with good accuracy the breakdown of these losses are attributed to different processes, meaning that optimisation of a compressor cascade profile, based solely on RANS,
may be hard to achieve.
Leggett, J.
31ece775-d118-4dab-a6ae-c66317e012ac
Priebe, S.
bf2e6c75-7e6e-4e71-8ce3-6f53f0e36d96
Shabbir, A.
0ea0da57-8989-4119-a8ed-09cc0db0ec79
Sandberg, R.D.
65156e9e-12ce-4709-8a83-f5f8879944cf
Richardson, E.
a8357516-e871-40d8-8a53-de7847aa2d08
Michelassi, V.
b596e629-2057-4a5b-afbc-24f891a61638
Leggett, J.
31ece775-d118-4dab-a6ae-c66317e012ac
Priebe, S.
bf2e6c75-7e6e-4e71-8ce3-6f53f0e36d96
Shabbir, A.
0ea0da57-8989-4119-a8ed-09cc0db0ec79
Sandberg, R.D.
65156e9e-12ce-4709-8a83-f5f8879944cf
Richardson, E.
a8357516-e871-40d8-8a53-de7847aa2d08
Michelassi, V.
b596e629-2057-4a5b-afbc-24f891a61638

Leggett, J., Priebe, S., Shabbir, A., Sandberg, R.D., Richardson, E. and Michelassi, V. (2017) LES loss prediction in an axial compressor cascade at off-design incidences with free stream disturbances. ASME Turbo Expo (International Gas Turbines Institute), , Charlotte, United States. 26 - 30 Jun 2017. (doi:10.1115/GT201764292).

Record type: Conference or Workshop Item (Paper)

Abstract

It is well known that an axial compressor cascade will exhibit variation in loss coefficient, described as a loss bucket, when run over a sweep of incidences, and that higher levels of free stream turbulence are likely to suppress separation bubbles and cause earlier transition (see e.g. [23]). However, it remains difficult to achieve accurate quantitative prediction of these changes using numerical simulation, particularly at off-design conditions, without the added computational expense of using eddy-resolving techniques. The aim of the present study is to investigate profile losses in an axial compressor under such conditions using wall-resolved Large Eddy Simulation (LES) and RANS. The work extends on previous work by Leggett et al.[11] with the intention of furthering our understanding of loss prediction tools and improving our quantification of the physical processes involved in loss generation. The results show that while RANS predicts losses with good accuracy the breakdown of these losses are attributed to different processes, meaning that optimisation of a compressor cascade profile, based solely on RANS,
may be hard to achieve.

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More information

Published date: June 2017
Venue - Dates: ASME Turbo Expo (International Gas Turbines Institute), , Charlotte, United States, 2017-06-26 - 2017-06-30
Organisations: Aerodynamics & Flight Mechanics Group, Education Hub

Identifiers

Local EPrints ID: 410105
URI: http://eprints.soton.ac.uk/id/eprint/410105
PURE UUID: 387c57bb-9a0b-4863-bfb4-b5a1f5338e15
ORCID for E. Richardson: ORCID iD orcid.org/0000-0002-7631-0377

Catalogue record

Date deposited: 03 Jun 2017 04:03
Last modified: 16 Mar 2024 04:05

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Contributors

Author: J. Leggett
Author: S. Priebe
Author: A. Shabbir
Author: R.D. Sandberg
Author: E. Richardson ORCID iD
Author: V. Michelassi

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