Reviewing machine learning of corrosion prediction in a data-oriented perspective

Vincent Vangrunderbeek; Leonardo Bertolucci Coelho; Yves Van Ingelgem; Herman Terryn; Ann Nowe; Denis Steckelmacher; Dawei Zhang

doi:https://doi.org/10.1038/s41529-022-00218-4

Reviewing machine learning of corrosion prediction in a data-oriented perspective

Vincent Vangrunderbeek, Leonardo Bertolucci Coelho, Yves Van Ingelgem, Herman Terryn, Ann Nowe, Denis Steckelmacher, Dawei Zhang

Onderzoeksoutput: Conference paper

118 Citaten (Scopus)

Samenvatting

This work provides a data-oriented overview of the rapidly growing research field covering machine learning (ML) applied to predicting electrochemical corrosion. Our main aim was to determine which ML models have been applied and how well they performed depending on the corrosion topic considered. From an extensive review of corrosion articles presenting comparable performance metrics, a ‘Machine learning for corrosion database’ was created, guiding corrosion experts and model developers in their applications of ML to corrosion. Potential research gaps and recommendations are discussed, and a broad perspective for future research paths is provided.

Originele taal-2	English
Titel	Reviewing machine learning of corrosion prediction in a data-oriented perspective
Uitgeverij	npj materials degradation
Pagina's	56-72
Aantal pagina's	1
Volume	6
Uitgave	1
DOI's	https://doi.org/10.1038/s41529-022-00218-4
Status	Published - dec 2022
Evenement	EurCorr 2022 - Berlin, Germany Duur: 28 aug 2022 → 1 sep 2022 https://eurocorr.org/2022.html

Publicatie series

Naam	npj Materials Degradation
Uitgeverij	Nature Research
ISSN van geprinte versie	2397-2106

Conference

Conference	EurCorr 2022
Land/Regio	Germany
Stad	Berlin
Periode	28/08/22 → 1/09/22
Internet adres	https://eurocorr.org/2022.html

Bibliografische nota

Funding Information:
The author L.B. Coelho is a Postdoctoral Researcher of the Fonds de la Recherche Scientifique – FNRS which is gratefully acknowledged.

Publisher Copyright:
© 2022, The Author(s).

Copyright:
Copyright 2022 Elsevier B.V., All rights reserved.

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https://doi.org/10.1038/s41529-022-00218-4

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Vangrunderbeek, V., Bertolucci Coelho, L., Van Ingelgem, Y., Terryn, H., Nowe, A., Steckelmacher, D., & Zhang, D. (2022). Reviewing machine learning of corrosion prediction in a data-oriented perspective. In Reviewing machine learning of corrosion prediction in a data-oriented perspective (1 redactie, Vol. 6, blz. 56-72). (npj Materials Degradation). npj materials degradation. https://doi.org/10.1038/s41529-022-00218-4

Vangrunderbeek, Vincent ; Bertolucci Coelho, Leonardo ; Van Ingelgem, Yves ; Terryn, Herman ; Nowe, Ann ; Steckelmacher, Denis ; Zhang, Dawei. / Reviewing machine learning of corrosion prediction in a data-oriented perspective. Reviewing machine learning of corrosion prediction in a data-oriented perspective. Vol. 6 1. redactie npj materials degradation, 2022. blz. 56-72 (npj Materials Degradation).

@inproceedings{2c1c08dfb9b9487796cd819028288af6,

title = "Reviewing machine learning of corrosion prediction in a data-oriented perspective",

abstract = "This work provides a data-oriented overview of the rapidly growing research field covering machine learning (ML) applied to predicting electrochemical corrosion. Our main aim was to determine which ML models have been applied and how well they performed depending on the corrosion topic considered. From an extensive review of corrosion articles presenting comparable performance metrics, a {\textquoteleft}Machine learning for corrosion database{\textquoteright} was created, guiding corrosion experts and model developers in their applications of ML to corrosion. Potential research gaps and recommendations are discussed, and a broad perspective for future research paths is provided.",

author = "Vincent Vangrunderbeek and {Bertolucci Coelho}, Leonardo and {Van Ingelgem}, Yves and Herman Terryn and Ann Nowe and Denis Steckelmacher and Dawei Zhang",

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language = "English",

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Vangrunderbeek, V , Bertolucci Coelho, L , Van Ingelgem, Y , Terryn, H , Nowe, A , Steckelmacher, D & Zhang, D 2022, Reviewing machine learning of corrosion prediction in a data-oriented perspective. in Reviewing machine learning of corrosion prediction in a data-oriented perspective. 1 edn, vol. 6, npj Materials Degradation, npj materials degradation, blz. 56-72, EurCorr 2022, Berlin, Germany, 28/08/22. https://doi.org/10.1038/s41529-022-00218-4

Reviewing machine learning of corrosion prediction in a data-oriented perspective. / Vangrunderbeek, Vincent ; Bertolucci Coelho, Leonardo ; Van Ingelgem, Yves ; Terryn, Herman ; Nowe, Ann ; Steckelmacher, Denis; Zhang, Dawei.

Reviewing machine learning of corrosion prediction in a data-oriented perspective. Vol. 6 1. redactie npj materials degradation, 2022. blz. 56-72 (npj Materials Degradation).

Onderzoeksoutput: Conference paper

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AU - Van Ingelgem, Yves

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AU - Steckelmacher, Denis

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Vangrunderbeek V , Bertolucci Coelho L , Van Ingelgem Y , Terryn H , Nowe A , Steckelmacher D et al. Reviewing machine learning of corrosion prediction in a data-oriented perspective. In Reviewing machine learning of corrosion prediction in a data-oriented perspective. 1 redactie Vol. 6. npj materials degradation. 2022. blz. 56-72. (npj Materials Degradation). https://doi.org/10.1038/s41529-022-00218-4

Reviewing machine learning of corrosion prediction in a data-oriented perspective

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