Structure-preserving formulations for data-driven analysis of coupled multi-physics systems
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
1 Online-Ressource.
- Language
-
Englisch
- Bibliographic citation
-
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
- Classification
-
Elektrotechnik, Elektronik
- Creator
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1007/s00466-024-02508-x
- URN
-
urn:nbn:de:101:1-2408151244587.340554143741
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:46 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Muixí, Alba
- González, David
- Chinesta, Francisco
- Cueto, Elías
- SpringerLink (Online service)
Other Objects (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
Data transfer in partitioned multi-physics simulations : interpolation & communication
Multi-physics ensemble modelling of Arctic tundra snowpack properties
Simulation of offshore wind turbines by computational multi-physics
Navigating speed–accuracy trade-offs for multi-physics simulations
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
Data transfer in partitioned multi-physics simulations : interpolation & communication
Multi-physics ensemble modelling of Arctic tundra snowpack properties
Simulation of offshore wind turbines by computational multi-physics
Navigating speed–accuracy trade-offs for multi-physics simulations
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
Data transfer in partitioned multi-physics simulations : interpolation & communication
Multi-physics ensemble modelling of Arctic tundra snowpack properties
Simulation of offshore wind turbines by computational multi-physics