Inverse heat source problem and experimental design for determining iron loss distribution

Antti Hannukainen; Nuutti Hyvonen; Lauri Perkkiö

doi:10.1137/20M1329986

Inverse heat source problem and experimental design for determining iron loss distribution

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Abstract

Iron loss determination in the magnetic core of an electrical machine, such as a motor or a transformer, is formulated as an inverse heat source problem. The sensor positions inside the object are optimized in order to minimize the uncertainty in the reconstruction in the sense of the A-optimality of Bayesian experimental design. This paper focuses on the problem formulation and an efficient numerical solution of the discretized sensor optimization and source reconstruction problems. A semirealistic linear model is discretized by finite elements and studied numerically.

Original language	English
Pages (from-to)	B243-B270
Number of pages	28
Journal	SIAM Journal on Scientific Computing
Volume	43
Issue number	2
DOIs	https://doi.org/10.1137/20M1329986
Publication status	Published - Mar 2021
MoE publication type	A1 Journal article-refereed

Funding

\ast Submitted to the journal's Computational Methods in Science and Engineering section April 6, 2020; accepted for publication (in revised form) November 30, 2020; published electronically March 1, 2021. https://doi.org/10.1137/20M1329986 \bfF \bfu \bfn \bfd \bfi \bfn \bfg : This work was supported by the Academy of Finland through grants 312124 and 312340 and by the Aalto Science Institute (AScI). \dagger Department of Mathematics and Systems Analysis, Aalto University, P.O. Box 11100, 00076 Aalto, Finland ([email protected], [email protected], [email protected]).

Keywords

Bayesian inversion
Electric machine
Inverse source problem
Iron loss
Optimal experimental design

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10.1137/20M1329986

Inverse Heat Source Problem and Experimental Design for Determining Iron Loss DistributionFinal published version, 4.2 MB

Cite this

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title = "Inverse heat source problem and experimental design for determining iron loss distribution",

abstract = "Iron loss determination in the magnetic core of an electrical machine, such as a motor or a transformer, is formulated as an inverse heat source problem. The sensor positions inside the object are optimized in order to minimize the uncertainty in the reconstruction in the sense of the A-optimality of Bayesian experimental design. This paper focuses on the problem formulation and an efficient numerical solution of the discretized sensor optimization and source reconstruction problems. A semirealistic linear model is discretized by finite elements and studied numerically.",

keywords = "Bayesian inversion, Electric machine, Inverse source problem, Iron loss, Optimal experimental design",

author = "Antti Hannukainen and Nuutti Hyvonen and Lauri Perkki{\"o}",

year = "2021",

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AU - Hannukainen, Antti

AU - Hyvonen, Nuutti

AU - Perkkiö, Lauri

PY - 2021/3

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N2 - Iron loss determination in the magnetic core of an electrical machine, such as a motor or a transformer, is formulated as an inverse heat source problem. The sensor positions inside the object are optimized in order to minimize the uncertainty in the reconstruction in the sense of the A-optimality of Bayesian experimental design. This paper focuses on the problem formulation and an efficient numerical solution of the discretized sensor optimization and source reconstruction problems. A semirealistic linear model is discretized by finite elements and studied numerically.

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KW - Electric machine

KW - Inverse source problem

KW - Iron loss

KW - Optimal experimental design

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ER -

Inverse heat source problem and experimental design for determining iron loss distribution

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Centre of Excellence of Inverse Modelling and Imaging

Centre of Excellence of Inverse Modelling and Imaging

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Inverse heat source problem and experimental design for determining iron loss distribution

Abstract

Funding

Keywords

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Centre of Excellence of Inverse Modelling and Imaging

Centre of Excellence of Inverse Modelling and Imaging

Cite this