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Multifidelity approaches for uncertainty quantification

Published:2019-04-05 Issue:2 Volume:42 Page:e201900008
ISSN:0936-7195
Container-title:GAMM-Mitteilungen
language:en
Short-container-title:GAMM‐Mitteilungen

Author:

Biehler Jonas¹,Mäck Markus²,Nitzler Jonas¹³,Hanss Michael²,Koutsourelakis Phaedon‐Stelios³,Wall Wolfgang A.¹

Affiliation:

1. Institute for Computational MechanicsTechnical University of Munich Munich Germany

2. Institute of Engineering and Computational MechanicsUniversity of Stuttgart Stuttgart Germany

3. Associate Professorship of Continuum MechanicsTechnical University of Munich Munich Germany

Funder

Deutsche Forschungsgemeinschaft

Publisher

Wiley

Subject

Applied Mathematics,General Physics and Astronomy,General Materials Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/gamm.201900008

Reference75 articles.

1. An overview of the Trilinos project

2. Multilevel Monte Carlo Path Simulation

3. Multifidelity importance sampling

4. Predicting the output from a complex computer code when fast approximations are available

5. Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling

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3. A generalized probabilistic learning approach for multi-fidelity uncertainty quantification in complex physical simulations;Computer Methods in Applied Mechanics and Engineering;2022-10

4. Uncertainty quantification of large-scale dynamical systems using parametric model order reduction;MECH SYST SIGNAL PR;2022

5. Uncertainty quantification of large-scale dynamical systems using parametric model order reduction;Mechanical Systems and Signal Processing;2022-05

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