Compressor cascade total pressure loss correlation modelling at design points using artificial neural networks

dc.contributor.author	Kovář, P.
dc.contributor.author	Fürst, J.
dc.contributor.editor	Adámek, Vítězslav
dc.contributor.editor	Jonášová, Alena
dc.contributor.editor	Plánička, Stanislav
dc.contributor.editor	Zajíček, Martin
dc.date.accessioned	2022-11-23T06:32:36Z
dc.date.available	2022-11-23T06:32:36Z
dc.date.issued	2022
dc.description.sponsorship	grant No. SGS22/148/OHK2/3T/12, project TK03030121 Conceptual Design of an Innovative Safety System for Gas-cooled Nuclear Reactors	en
dc.format	4 s.	cs
dc.format.mimetype	application/pdf
dc.identifier.citation	Computational mechanics 2022: book of extended abstracts: 37th conference with international participation, p. 50-53.	en
dc.identifier.uri	http://hdl.handle.net/11025/50370
dc.language.iso	en	en
dc.publisher	Západočeská univerzita v Plzni	cs
dc.rights	© 2021 University of West Bohemia, Plzeň, Czech Republic	en
dc.rights.access	openAccess	en
dc.subject	umělé neuronové sítě	cs
dc.subject	výpočetní dynamika tekutin	cs
dc.subject	NACA 65	cs
dc.subject	kompresor	cs
dc.subject.translated	artificial neural networks	en
dc.subject.translated	computational fluid dynamics	en
dc.subject.translated	NACA 65	en
dc.subject.translated	compressor	en
dc.title	Compressor cascade total pressure loss correlation modelling at design points using artificial neural networks	en
dc.type	konferenční příspěvek	cs
dc.type	conferenceObject	en
dc.type.status	Peer-reviewed	en
dc.type.version	publishedVersion	en

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