This paper reviews the localized corrosion of passive Ni-Fe-Cr-Mo-N alloys immersed in seawater using a Bayesian network (BN) method. Making alloy performance decisions using data from the literature on seawater is challenging because a large body of data is generated using various methods in various natural conditions. There is a significant scatter in the data and cross-comparison of data from different techniques is difficult. The BN approach serves to integrate diverse sources of knowledge and data in this area and evaluate the data in a probabilistic manner. The paper shows that the predicted probability of localized corrosion agrees reasonably well with field data. The challenges and opportunities to improve the BN model are discussed.
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1 March 2023
Research Article|
November 03 2022
Localized Corrosion in Seawater: A Bayesian Network-Based Review Available to Purchase
Narasi Sridhar
Narasi Sridhar
‡
‡Corresponding author. E-mail: [email protected]. MC Consult LLC, 31510 Sweetwater Circle, Temecula, California 92591.
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‡Corresponding author. E-mail: [email protected]. MC Consult LLC, 31510 Sweetwater Circle, Temecula, California 92591.
Online ISSN: 1938-159X
Print ISSN: 0010-9312
© 2023, AMPP
2023
CORROSION (2023) 79 (3): 268–283.
Citation
Narasi Sridhar; Localized Corrosion in Seawater: A Bayesian Network-Based Review. CORROSION 1 March 2023; 79 (3): 268–283. https://doi.org/10.5006/4215
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