Multi-output multilevel best linear unbiased estimators via semidefinite programming

Multifidelity forward uncertainty quantification (UQ) problems often involve multiple quantities of interest and heterogeneous models (e.g., different grids, equations, dimensions, physics, surrogate and reduced-order models). While computational efficiency is key in this context, multi-output strat...

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Bibliographic Details
Published in:	Computer methods in applied mechanics and engineering Vol. 413; no. C; p. 116130
Main Authors:	Croci, M., Willcox, K.E., Wright, S.J.
Format:	Journal Article
Language:	English
Published:	United States Elsevier B.V 01.08.2023 Elsevier
Subjects:	Engineering Mathematics MATHEMATICS AND COMPUTING Mechanics Model selection Multifidelity Monte Carlo Multilevel Monte Carlo Sample allocation Semidefinite programming Uncertainty quantification Multilevel Monte Carlo Uncertainty quantification Semidefinite programming Multifidelity Monte Carlo Sample allocation Model selection
ISSN:	0045-7825, 1879-2138
Online Access:	Get full text
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