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Title:

Multi-fidelity Bayesian optimization to solve the inverse Stefan problem

Document type:
Zeitschriftenaufsatz
Author(s):
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...     »
Keywords:
Bayesian optimization; Dendritic growth; Inverse problem; Multi-fidelity modeling; Multiresolution
Dewey Decimal Classification:
620 Ingenieurwissenschaften
Journal title:
Computer Methods in Applied Mechanics and Engineering
Year:
2023
Journal volume:
410
Pages contribution:
115946
Covered by:
Scopus
Language:
en
Fulltext / DOI:
doi:10.1016/j.cma.2023.115946
Publisher:
Elsevier BV
E-ISSN:
0045-7825
Date of publication:
01.05.2023
TUM Institution:
Lehrstuhl für Aerodynamik und Strömungsmechanik
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