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...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Computer methods in applied mechanics and engineering Jg. 413; H. C; S. 116130
Hauptverfasser:	Croci, M., Willcox, K.E., Wright, S.J.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier B.V 01.08.2023 Elsevier
Schlagworte:	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-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!