Prediction of steady-state flow in a 3D domain using  a convolutional neural network

dc.contributor.author	Bublík, O.
dc.contributor.author	Heidler, V.
dc.contributor.author	Vimmr, J.
dc.contributor.editor	Adámek, Vítězslav
dc.contributor.editor	Jonášová, Alena
dc.contributor.editor	Plánička, Stanislav
dc.date.accessioned	2025-11-30T09:45:18Z
dc.date.available	2025-11-30T09:45:18Z
dc.date.issued	2025
dc.description.sponsorship	This research is supported by project ”Investigation of 3D flow structures and their effects on aeroelastic stability of turbine-blade cascades using experiment and deep learning approach” GACR 24-12144S of the Grant Agency of the Czech Republic.	en
dc.format	2 s.	cs
dc.format.mimetype	application/pdf
dc.format.version	publishedVersion	en
dc.identifier.isbn	978-80-261-1254-9
dc.identifier.uri	http://hdl.handle.net/11025/64183
dc.language.iso	en	en
dc.publisher	University of West Bohemia in Pilsen	en
dc.rights	© University of West Bohemia in Pilsen	en
dc.rights.access	openAccess	en
dc.subject	konvoluční neuronová síť	cs
dc.subject	3D doména	cs
dc.subject	test	cs
dc.subject.translated	convolutional neural network	en
dc.subject.translated	3D domain	en
dc.subject.translated	test	en
dc.title	Prediction of steady-state flow in a 3D domain using a convolutional neural network	en
dc.type	konferenční příspěvek	cs
dc.type	conferenceObject	en
dc.type.status	Peer reviewed	en
local.files.count	2	*
local.files.size	843004	*
local.has.files	yes	*

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