ScienceOpen:
research and publishing network
For Publishers
Discovery
Metadata
Peer review
Hosting
Publishing
For Researchers
Join
Publish
Review
Collect
My ScienceOpen
Sign in
Register
Dashboard
Blog
About
Search
Advanced search
My ScienceOpen
Sign in
Register
Dashboard
Search
Search
Advanced search
For Publishers
Discovery
Metadata
Peer review
Hosting
Publishing
For Researchers
Join
Publish
Review
Collect
Blog
About
3
views
0
references
Top references
cited by
4
0 reviews
Review
0
comments
Comment
0
recommends
+1
Recommend
0
collections
Add to
0
shares
Share
Twitter
Sina Weibo
Facebook
Email
1,849
similar
All similar
Record
: found
Abstract
: not found
Article
: not found
Real‐time updating of structural mechanics models using Kalman filtering, modified constitutive relation error, and proper generalized decomposition
Author(s):
Basile Marchand
,
Ludovic Chamoin
,
Christian Rey
,
B Marchand
,
L. Chamoin
,
C Rey
Publication date:
2016
Journal:
Int J Numer Methods Eng
Read this article at
ScienceOpen
Publisher
Bookmark
There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.
Related collections
Genome Engineering using CRISPR
Author and article information
Journal
DOI::
10.1002/nme.5197
Data availability:
Comments
Comment on this article
Sign in to comment
scite_
Similar content
1,849
Phase unwrapping of multibaseline interferometry using Kalman filtering
Authors:
M.G. Kim
An Unscented Kalman Filter Approach to the Estimation of Nonlinear Dynamical Systems Models
Authors:
Sy-Miin Chow
,
John R Nesselroade
,
Emilio Ferrer
The Kalman filter in transfer alignment of inertial guidance systems.
Authors:
A. A. SUTHERLAND, JR.
See all similar
Cited by
4
NN‐mCRE: A modified constitutive relation error framework for unsupervised learning of nonlinear state laws with physics‐augmented neural networks
Authors:
Antoine Benady
,
Emmanuel Baranger
,
Ludovic Chamoin
Unsupervised learning of history-dependent constitutive material laws with thermodynamically-consistent neural networks in the modified Constitutive Relation Error framework
Authors:
Antoine Benady
,
Emmanuel Baranger
,
Ludovic Chamoin
Data-driven material modeling based on the Constitutive Relation Error
Authors:
Pierre Ladevèze
,
Ludovic Chamoin
See all cited by