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Extrapolation of cavitation and hydrodynamic pressure in lubricated contacts: a physics-informed neural network approach
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In
Advanced modeling and simulation in engineering sciences 12, Seiten/Artikel-Nr.:2
2025
Online
DOI: 10.1186/s40323-025-00283-9
DOI: 10.18154/RWTH-2025-00937
URL: https://publications.rwth-aachen.de/record/1003244/files/1003244.pdf
Einrichtungen
Projekte
Inhaltliche Beschreibung (Schlagwörter)
Hydrodynamic pressure extrapolation (frei) ; Physics-informed machine learning (frei) ; Physics-informed neural networks (frei) ; Pneumatic sealing (frei) ; Spatial and temporal extrapolation (frei) ; cavitation extrapolation (frei) ; elastohydrodynamic lubrication simulation (frei) ; tribology (frei)
Thematische Einordnung (Klassifikation)
DDC: 620
OpenAccess: 
PDF
Dokumenttyp
Journal Article
Format
online
Sprache
English
Anmerkung
Peer reviewed article
Externe Identnummern
WOS Core Collection: WOS:001406638800001
SCOPUS: SCOPUS:2-s2.0-85218198457
Interne Identnummern
RWTH-2025-00937
Datensatz-ID: 1003244
Beteiligte Länder
Germany
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