Data‐driven physics‐based digital twins via a library of component‐based reduced‐order models
Summary This work proposes an approach that combines a library of component‐based reduced‐order models with Bayesian state estimation in order to create data‐driven physics‐based digital twins. Reduced‐order modeling produces physics‐based computational models that are reliable enough for predictive...
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| Published in: | International journal for numerical methods in engineering Vol. 123; no. 13; pp. 2986 - 3003 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Hoboken, USA
John Wiley & Sons, Inc
15.07.2022
Wiley Subscription Services, Inc |
| Subjects: | |
| ISSN: | 0029-5981, 1097-0207 |
| Online Access: | Get full text |
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