Application of machine learning to stress corrosion cracking risk assessment-Reference-Cited by-同舟云学术

Application of machine learning to stress corrosion cracking risk assessment

Published:2022-12 Issue:4 Volume:31 Page:11-21
ISSN:1110-0621
Container-title:Egyptian Journal of Petroleum
language:en
Short-container-title:Egyptian Journal of Petroleum

Author:

Alamri Aeshah H.

Publisher

Elsevier BV

Subject

Organic Chemistry,Process Chemistry and Technology,Geochemistry and Petrology,Fuel Technology,Renewable Energy, Sustainability and the Environment,Catalysis

Reference98 articles.

1. Corrosion of additively manufactured stainless steels—process, structure, performance: A review;Schindelholz;Corrosion,2021

2. The novel polythiadiazole polymer and its composite with α-Al (OH) 3 as inhibitors for steel alloy corrosion in molar H2SO4: Experimental and computational evaluations;Abd El-Lateef;J. Ind. Eng. Chem.,2022

3. Novel carbon dots as efficient green corrosion inhibitor for mild steel in HCl solution: Electrochemical, gravimetric and XPS studies;Saraswat;J. Phys. Chem. Solids,2022

4. Elucidating structure-property relationships in aluminum alloy corrosion inhibitors by machine learning;Galvão;J. Phys. Chem. C,2020

5. A machine learning-based data fusion approach for improved corrosion testing;Völker;Surv. Geophys.,2020

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