On- and off-design performance of a model rotating turbine with non-axisymmetric endwall contouring and a comparison to cascade data

Snedden, G.; Dunn, D.; Ingram, G.

Abstract

Non-axisymmetric endwalls in turbine stages have shown to be a robust method to improve the performance of turbines in both power generation and aero-derivative applications. Non-axisymmetric endwalls target the control of secondary flows and are designed using detailed computational fluid dynamics coupled with a variety of optimisation algorithms and utilising a number of objective functions according to the engine company or researcher's preference. These numerical predictions are often backed up by detailed measurements in linear and annular cascades and later proven in full-scale engine tests. Relatively little literature is available describing their performance in rotating test rigs or at conditions other than design, apart from that of the authors. This study comprehensively revisits the low-speed, model turbines used in the earlier study, replacing all of the 5-hole probe data with more accurate results and additional hot-film measurements. These results together with computational fluid dynamics solutions are used to show the success of the method across a large incidence range and to compare to earlier cascade results for a similar endwall and blade profile to establish the usefulness of cascade testing in this application. In addition, a comparison to two other off-design studies is made. Results indicate that the endwalls successfully improve the rotor total isentropic efficiency at all test conditions and that the improvement increases with increased turning in the blade row, from 0.5% to 1.8% across the incidence range. The results also compare well to the estimation of isentropic efficiency improvement that can be drawn from the cascade testing which stands at 1.55%.

Citation

Snedden, G., Dunn, D., & Ingram, G. (2018). On- and off-design performance of a model rotating turbine with non-axisymmetric endwall contouring and a comparison to cascade data. Aeronautical Journal, 122(1250), 646-665. https://doi.org/10.1017/aer.2018.13

• Journal Article Type: Article
• Acceptance Date: Feb 8, 2018
• Online Publication Date: Mar 21, 2018
• Publication Date: Apr 1, 2018
• Deposit Date: Apr 24, 2018
• Publicly Available Date: Sep 21, 2018
• Journal: Aeronautical Journal
• Print ISSN: 0001-9240
• Electronic ISSN: 2059-6464
• Publisher: Cambridge University Press
• Peer Reviewed: Peer Reviewed
• Volume: 122
• Issue: 1250
• Pages: 646-665
• DOI: https://doi.org/10.1017/aer.2018.13