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Prediction of First-Year Corrosion Losses of Carbon Steel and Zinc in Continental Regions

Dose-response functions (DRFs) developed for the prediction of first-year corrosion losses of carbon steel and zinc (K(1)) in continental regions are presented. The dependences of mass losses on SO(2) concentration, K = f([SO(2)]), obtained from experimental data, as well as nonlinear dependences of...

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Autores principales: Panchenko, Yulia M., Marshakov, Andrey I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5507004/
https://www.ncbi.nlm.nih.gov/pubmed/28772784
http://dx.doi.org/10.3390/ma10040422
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author Panchenko, Yulia M.
Marshakov, Andrey I.
author_facet Panchenko, Yulia M.
Marshakov, Andrey I.
author_sort Panchenko, Yulia M.
collection PubMed
description Dose-response functions (DRFs) developed for the prediction of first-year corrosion losses of carbon steel and zinc (K(1)) in continental regions are presented. The dependences of mass losses on SO(2) concentration, K = f([SO(2)]), obtained from experimental data, as well as nonlinear dependences of mass losses on meteorological parameters, were taken into account in the development of the DRFs. The development of the DRFs was based on the experimental data from one year of testing under a number of international programs: ISO CORRAG, MICAT, two UN/ECE programs, the Russian program in the Far-Eastern region, and data published in papers. The paper describes predictions of K(1) values of these metals using four different models for continental test sites under UN/ECE, RF programs and within the MICAT project. The predictions of K(1) are compared with experimental K(1) values, and the models presented here are analyzed in terms of the coefficients used in the models.
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spelling pubmed-55070042017-07-28 Prediction of First-Year Corrosion Losses of Carbon Steel and Zinc in Continental Regions Panchenko, Yulia M. Marshakov, Andrey I. Materials (Basel) Article Dose-response functions (DRFs) developed for the prediction of first-year corrosion losses of carbon steel and zinc (K(1)) in continental regions are presented. The dependences of mass losses on SO(2) concentration, K = f([SO(2)]), obtained from experimental data, as well as nonlinear dependences of mass losses on meteorological parameters, were taken into account in the development of the DRFs. The development of the DRFs was based on the experimental data from one year of testing under a number of international programs: ISO CORRAG, MICAT, two UN/ECE programs, the Russian program in the Far-Eastern region, and data published in papers. The paper describes predictions of K(1) values of these metals using four different models for continental test sites under UN/ECE, RF programs and within the MICAT project. The predictions of K(1) are compared with experimental K(1) values, and the models presented here are analyzed in terms of the coefficients used in the models. MDPI 2017-04-18 /pmc/articles/PMC5507004/ /pubmed/28772784 http://dx.doi.org/10.3390/ma10040422 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Panchenko, Yulia M.
Marshakov, Andrey I.
Prediction of First-Year Corrosion Losses of Carbon Steel and Zinc in Continental Regions
title Prediction of First-Year Corrosion Losses of Carbon Steel and Zinc in Continental Regions
title_full Prediction of First-Year Corrosion Losses of Carbon Steel and Zinc in Continental Regions
title_fullStr Prediction of First-Year Corrosion Losses of Carbon Steel and Zinc in Continental Regions
title_full_unstemmed Prediction of First-Year Corrosion Losses of Carbon Steel and Zinc in Continental Regions
title_short Prediction of First-Year Corrosion Losses of Carbon Steel and Zinc in Continental Regions
title_sort prediction of first-year corrosion losses of carbon steel and zinc in continental regions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5507004/
https://www.ncbi.nlm.nih.gov/pubmed/28772784
http://dx.doi.org/10.3390/ma10040422
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