A non-intrusive nonlinear model reduction method for structural dynamical problems based on machine learning
J. Kneifl, D. Grunert, und J. Fehr. International Journal for Numerical Methods in Engineering, (April 2021)initial preprint available under http://elib.uni-stuttgart.de/handle/11682/11198.
DOI: 10.1002/nme.6712
%0 Journal Article
%1 KneiflGrunertFehr2021
%A Kneifl, Jonas
%A Grunert, Dennis
%A Fehr, Joerg
%D 2021
%I Wiley
%J International Journal for Numerical Methods in Engineering
%K EXC2075 PN7 PN7-6 curated
%R 10.1002/nme.6712
%T A non-intrusive nonlinear model reduction method for structural dynamical problems based on machine learning
%U https://doi.org/10.1002%2Fnme.6712
@article{KneiflGrunertFehr2021,
added-at = {2022-02-16T16:53:10.000+0100},
author = {Kneifl, Jonas and Grunert, Dennis and Fehr, Joerg},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2c6c53d5c369ab742722817452d6f3909/simtech},
doi = {10.1002/nme.6712},
interhash = {ebff56638151df73a7826c0567b8089b},
intrahash = {c6c53d5c369ab742722817452d6f3909},
journal = {International Journal for Numerical Methods in Engineering},
keywords = {EXC2075 PN7 PN7-6 curated},
month = {4},
note = {initial preprint available under http://elib.uni-stuttgart.de/handle/11682/11198},
publisher = {Wiley},
timestamp = {2023-12-06T08:55:18.000+0100},
title = {A non-intrusive nonlinear model reduction method for structural dynamical problems based on machine learning},
url = {https://doi.org/10.1002%2Fnme.6712},
year = 2021
}