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Analytical and neural network models for gas turbine design and off-design simulation
Department of Mechanical Engineering, University of Padova.
2001 (Engelska)Ingår i: International Journal of Thermodynamics, ISSN 1301-9724, Vol. 4, nr 4, s. 173-182Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

This paper presents a gas turbine design and off-design model in which the difficulties due to lack of knowledge about stage-by-stage performance are overcome by constructing artificial machine maps through appropriate scaling techniques applied to generalized maps taken from the literature and validating them with test measurement data from real plants. In particular, off-design performance is obtained through compressor map modifications according to variable inlet guide vane closure. The set of equations of the developed analytical model is solved by a commercial package, which provides great flexibility in the choice of independent variables of the overall system. The results obtained from this simulator are used for neural network training: problems associated with the construction and use of neural networks are discussed and their capability as a tool for predicting machine performance is analyzed.

Ort, förlag, år, upplaga, sidor
2001. Vol. 4, nr 4, s. 173-182
Identifikatorer
URN: urn:nbn:se:ltu:diva-11055Lokalt ID: 9f44a3d1-c424-4a05-9cf6-37215375f999OAI: oai:DiVA.org:ltu-11055DiVA, id: diva2:984004
Anmärkning
Upprättat; 2012; 20120817 (andbra)Tillgänglig från: 2016-09-29 Skapad: 2016-09-29 Senast uppdaterad: 2017-11-24Bibliografiskt granskad

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