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Titel:

Multi-fidelity Bayesian optimization to solve the inverse Stefan problem

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Winter, J.M.; Abaidi, R.; Kaiser, J.W.J.; Adami, S.; Adams, N.A.
Abstract:
In this work, we propose an efficient solution of the inverse Stefan problem by multi-fidelity Bayesian optimization. We construct a multi-fidelity Gaussian process surrogate model by combining many low-fidelity estimates of a solidification problem with only a few high-fidelity measurements. To solve the inverse problem, we employ the Gaussian process model in a Bayesian optimization approach based on a multi-fidelity knowledge gradient acquisition function. To account for the specific structur...     »
Stichworte:
Bayesian optimization; Dendritic growth; Inverse problem; Multi-fidelity modeling; Multiresolution
Dewey Dezimalklassifikation:
620 Ingenieurwissenschaften
Zeitschriftentitel:
Computer Methods in Applied Mechanics and Engineering
Jahr:
2023
Band / Volume:
410
Seitenangaben Beitrag:
115946
Nachgewiesen in:
Scopus
Sprache:
en
Volltext / DOI:
doi:10.1016/j.cma.2023.115946
Verlag / Institution:
Elsevier BV
E-ISSN:
0045-7825
Publikationsdatum:
01.05.2023
TUM Einrichtung:
Lehrstuhl für Aerodynamik und Strömungsmechanik
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