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Axial-flow compressor model based on a cascade stacking technique and neural networks
Dipartimento di Ingegneria Meccano, Università di Padova.
2002 (English)In: Proceedings of the ASME Turbo Expo 2002 Turbomachinery: presented at the 2002 ASME Turbo Expo, June 3 - 6, 2002, Amsterdam, the Netherlands, New York: American Society of Mechanical Engineers , 2002, Vol. 5B, p. 793-801Conference paper, Published paper (Refereed)
Abstract [en]

This paper introduces a cascade-stacking technique for the development of a gas turbine multi-stage axial-flow compressor model. A large database of stationary and rotating cascade performance is first obtained by quasi three-dimensional CFD simulations and used to train neural networks for the prediction of cascade performance under generalized conditions. Then the model directly calculates the operating point of a compressor having known geometry characteristics, including variable inlet guide/stator vane effects, as a function of mass flow rate and rotational speed. The model can also be used as a valuable preliminary design tool, obtaining geometry characteristics by imposing flow patterns.

Place, publisher, year, edition, pages
New York: American Society of Mechanical Engineers , 2002. Vol. 5B, p. 793-801
Identifiers
URN: urn:nbn:se:ltu:diva-32936DOI: 10.1115/GT2002-30443Scopus ID: 37000726Local ID: 79884093-cd95-4a61-b8e3-0f9aa86b4ea5ISBN: 079183610X (print)OAI: oai:DiVA.org:ltu-32936DiVA, id: diva2:1006171
Conference
ASME Turbo Expo : 03/06/2002 - 06/06/2002
Note
Upprättat; 2012; 20120809 (andbra)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved

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Toffolo, Andrea

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CiteExportLink to record
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  • apa
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  • nn-NB
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  • Other locale
More languages
Output format
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  • asciidoc
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