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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Vydané v:	Computer methods in applied mechanics and engineering Ročník 413; číslo C; s. 116130
Hlavní autori:	Croci, M., Willcox, K.E., Wright, S.J.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Elsevier B.V 01.08.2023 Elsevier
Predmet:	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
On-line prístup:	Získať plný text
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