Fast simulation of coronary in‐stent restenosis: A non‐intrusive data‐driven reduced order surrogate model
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
-
Englisch
- Bibliographic citation
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In: 10.1002/pamm.202400067
- Event
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Veröffentlichung
- (where)
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Aachen
- (who)
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Universitätsbibliothek der RWTH Aachen
- (when)
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2024
- Creator
- DOI
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10.18154/RWTH-2024-11081
- URN
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urn:nbn:de:101:1-2412100127247.648361377660
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:28 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
- Shi, Jianye
- Manjunatha, Kiran
- Reese, Stefanie
- Universitätsbibliothek der RWTH Aachen
Time of origin
- 2024
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Fast simulation of coronary in‐stent restenosis: A non‐intrusive data‐driven reduced order surrogate model
Deep learning‐based surrogate modeling of coronary in‐stent restenosis
Deep learning‐based surrogate modeling of coronary in‐stent restenosis
A coupled multiphysics approach for modelling in-stent restenosis
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Theorie und Numerik des Stabilitätsverhaltens hyperelastischer Festkörper
A continuum chemo‐mechano‐biological model for in‐stent restenosis with consideration of hemodynamic effects
Thermomechanische Modellierung gummiartiger Polymerstrukturen
In-stent restenosis in real world
Numerical implementation of tension–compression asymmetry in a gradient‐extended two‐surface damage–plasticity model
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