Corrosion prediction for bulk carrier via data fusion of survey and experimental measurements

Corrosion prediction for bulk carrier via data fusion of survey and experimental measurements

Accurate corrosion predictions are vital to safe and optimised designs of marine assets. Traditional approaches, including those used to develop rule requirements, seek to use empirical regressions to model corrosion, but most are solely time-dependent. This may lead to conservative damage estimates...

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Bibliographic Details
Main Authors: Z. Wang, A.J. Sobey, Y. Wang
Format: Article
Language:English
Published: Elsevier 2021-10-01
Series:Materials & Design
Subjects:
Carbon steels
Immersion and atmospheric corrosion
Artificial neural network
Interpretable machine learning
Marine environments
Bulk carrier ballast tanks
Online Access:http://www.sciencedirect.com/science/article/pii/S0264127521004639

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http://www.sciencedirect.com/science/article/pii/S0264127521004639

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