Structure-preserving formulations for data-driven analysis of coupled multi-physics systems
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
1 Online-Ressource.
- Sprache
-
Englisch
- Erschienen in
-
Structure-preserving formulations for data-driven analysis of coupled multi-physics systems ; day:7 ; month:6 ; year:2024 ; pages:1-12
Computational mechanics ; (7.6.2024), 1-12
- Klassifikation
-
Elektrotechnik, Elektronik
- Urheber
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1007/s00466-024-02508-x
- URN
-
urn:nbn:de:101:1-2408151244587.340554143741
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:46 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Muixí, Alba
- González, David
- Chinesta, Francisco
- Cueto, Elías
- SpringerLink (Online service)
Ähnliche Objekte (12)
Load-balancing for multi-physics simulations
3D multi-physics uncertainty quantification using physics-based machine learning
3D multi-physics uncertainty quantification using physics-based machine learning
Multi-physics phase-field modeling of magnetic materials
Simulation of offshore wind turbines by computational multi-physics
Multi-physics Co-simulation of an Electric Reach Truck
A Multi-physics Methodology for Four States of Matter
Inelastic material response in multi-physics earthquake rupture simulations
Simulation of offshore wind turbines by computational multi-physics
Multi-physics ensemble modelling of Arctic tundra snowpack properties
Navigating speed–accuracy trade-offs for multi-physics simulations
Data transfer in partitioned multi-physics simulations : interpolation & communication
Load-balancing for multi-physics simulations
3D multi-physics uncertainty quantification using physics-based machine learning
3D multi-physics uncertainty quantification using physics-based machine learning
Multi-physics phase-field modeling of magnetic materials
Simulation of offshore wind turbines by computational multi-physics
Multi-physics Co-simulation of an Electric Reach Truck
A Multi-physics Methodology for Four States of Matter
Inelastic material response in multi-physics earthquake rupture simulations
Simulation of offshore wind turbines by computational multi-physics
Multi-physics ensemble modelling of Arctic tundra snowpack properties
Navigating speed–accuracy trade-offs for multi-physics simulations
Data transfer in partitioned multi-physics simulations : interpolation & communication
Load-balancing for multi-physics simulations
3D multi-physics uncertainty quantification using physics-based machine learning
3D multi-physics uncertainty quantification using physics-based machine learning
Multi-physics phase-field modeling of magnetic materials
Simulation of offshore wind turbines by computational multi-physics
Multi-physics Co-simulation of an Electric Reach Truck
A Multi-physics Methodology for Four States of Matter
Inelastic material response in multi-physics earthquake rupture simulations
Simulation of offshore wind turbines by computational multi-physics
Multi-physics ensemble modelling of Arctic tundra snowpack properties
Navigating speed–accuracy trade-offs for multi-physics simulations