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Title:

Stochastic multi-fidelity surrogate modeling of dendritic crystal growth

Document type:
Zeitschriftenaufsatz
Author(s):
Winter, J.M.; Kaiser, J.W.J.; Adami, S.; Akhatov, I.S.; Adams, N.A.
Abstract:
In this work, we propose a novel framework coupling state-of-the-art multi-fidelity Gaussian Process modeling techniques with input-space warping for a cost-efficient construction of a stochastic surrogate model. During model generation, we achieve high computational efficiency by combining a large number of cheap estimates (low-fidelity model) with only a few, computationally expensive, high-fidelity measurements. We base the fidelity hierarchy on coarse-grid approximations of high-fidelity num...     »
Keywords:
Dendritic growth; Gaussian processes; Input warping; Multi-fidelity model; Multiresolution; Stochastic surrogate modeling
Dewey Decimal Classification:
620 Ingenieurwissenschaften
Horizon 2020:
Horizon 2020 Framework Programme, No. 667483
Journal title:
Computer Methods in Applied Mechanics and Engineering
Year:
2022
Journal volume:
393
Pages contribution:
114799
Covered by:
Scopus
Language:
en
Fulltext / DOI:
doi:10.1016/j.cma.2022.114799
WWW:
https://www.sciencedirect.com/science/article/abs/pii/S0045782522001311
Publisher:
Elsevier BV
E-ISSN:
0045-7825
Notes:
Funding text 1 The first, third, and fifth authors acknowledge funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No. 667483 ). The authors gratefully acknowledge the Gauss Centre for Supercomputing e.V. ( www.gauss-centre.eu ) for funding this project by providing computing time on the GCS Supercomputer SuperMUC-NG at Leibniz Supercomputing Centre ( www.lrz.de ). Funding text 2 The first, third, and fifth...     »
Submitted:
08.09.2021
Accepted:
20.02.2022
Date of publication:
01.04.2022
TUM Institution:
Lehrstuhl für Aerodynamik und Strömungsmechanik
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