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Optimalizace tvaru mazací mezery hydrodynamického ložiska s využitím umělých neuronových sítí / Lubricant gap shape optimization of the hydrodynamic thrust bearing using artificial neural networks

The thesis deals with the description of the main parts of the turbocharger and explains the concept of optimization. Furthermore, the work deals with the description of the flow of real fluids and lubrication of the hydrodynamic bearing. The work deals with the creation of a computational model, metamodel and subsequent search for a global extreme. In particular, the neural network metamodel technique is used in metamodel formation.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:417064
Date January 2020
CreatorsKukla, Lukáš
ContributorsCoufal, Tomáš, Jonák, Martin
PublisherVysoké učení technické v Brně. Fakulta strojního inženýrství
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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