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On the assessment of centrifugal compressor performance parameters by theoretical and computational models
KTH, School of Engineering Sciences (SCI), Mechanics. KTH, School of Industrial Engineering and Management (ITM), Centres, Competence Center for Gas Exchange (CCGEx).
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.). KTH, School of Industrial Engineering and Management (ITM), Centres, Competence Center for Gas Exchange (CCGEx).
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.). KTH, School of Industrial Engineering and Management (ITM), Centres, Competence Center for Gas Exchange (CCGEx).
KTH, School of Engineering Sciences (SCI), Mechanics. KTH, School of Industrial Engineering and Management (ITM), Centres, Competence Center for Gas Exchange (CCGEx).
2017 (English)In: Proceedings of the ASME Turbo ExpoVolume 2C-2017, ASME Press, 2017, Vol. 2C-2017Conference paper (Refereed)
Abstract [en]

1D performance prediction modeling and steady-state CFD are applied to assess a high-performance centrifugal compressor. Computed total pressure ratio is compared with experimental data obtained from a gas stand. The focus of the paper is to assess the validity range of the methodologies used. Another aim is to quantify the relative differences between experimental and predicted data, and distinguish differences in the conjectured loss budget. The RANS data manifest overall a higher degree of accuracy than the 1D model when compared with experiments. The 1D model considered shows comparable accuracy at design condition but larger discrepancies at higher speedlines towards surge and choke. Component-wise parametric losses are correlated to pinpoint flow regimes with larger differences between 1D and RANS data. The result exposes significant disparity in the, impeller, vaneless diffuser and the volute model, respectively, especially off-design. Improving these features in the 1D modeling would potentially be profitable for improved accuracy in the performance prognosis.

Place, publisher, year, edition, pages
ASME Press, 2017. Vol. 2C-2017
National Category
Other Engineering and Technologies
Identifiers
URN: urn:nbn:se:kth:diva-216329DOI: 10.1115/GT2017-65230ISI: 000412715300042Scopus ID: 2-s2.0-85021789125ISBN: 9780791850800 OAI: oai:DiVA.org:kth-216329DiVA, id: diva2:1151294
Conference
ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition, GT 2017, Charlotte, United States, 26 June 2017 through 30 June 2017
Note

QC 20171023

Available from: 2017-10-23 Created: 2017-10-23 Last updated: 2017-11-02Bibliographically approved

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Sundström, EliasKerres, BertrandSanz, SergioMihǎescu, Mihai
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