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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Vydáno v:	International journal for numerical methods in engineering Ročník 123; číslo 13; s. 2986 - 3003
Hlavní autoři:	Kapteyn, M.G., Knezevic, D.J., Huynh, D.B.P., Tran, M., Willcox, K.E.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Hoboken, USA John Wiley & Sons, Inc 15.07.2022 Wiley Subscription Services, Inc
Témata:	Adaptation Aircraft Aircraft components Aircraft structures Bayesian analysis Complex systems data‐model fusion digital twin Digital twins Libraries Model reduction model updating Physics reduced‐order model State estimation Structural damage unmanned aerial vehicle Unmanned aerial vehicles Wing span
ISSN:	0029-5981, 1097-0207
On-line přístup:	Získat plný text
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