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Prediction of Chloride Distribution for Offshore Concrete Based on Statistical Analysis

Chloride-induced corrosion is the main threat to the service life of concrete structures. In order to better investigate chloride distribution in offshore concrete, this study proposed a new prediction model based on statistical analysis as well as a large body of experimental results collected from...

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Autores principales: Liu, Qing-feng, Hu, Zhi, Lu, Xian-yang, Yang, Jian, Azim, Iftikhar, Sun, Wenzhuo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6982216/
https://www.ncbi.nlm.nih.gov/pubmed/31906365
http://dx.doi.org/10.3390/ma13010174
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author Liu, Qing-feng
Hu, Zhi
Lu, Xian-yang
Yang, Jian
Azim, Iftikhar
Sun, Wenzhuo
author_facet Liu, Qing-feng
Hu, Zhi
Lu, Xian-yang
Yang, Jian
Azim, Iftikhar
Sun, Wenzhuo
author_sort Liu, Qing-feng
collection PubMed
description Chloride-induced corrosion is the main threat to the service life of concrete structures. In order to better investigate chloride distribution in offshore concrete, this study proposed a new prediction model based on statistical analysis as well as a large body of experimental results collected from various sources. A detailed discussion found that the key influential parameters, such as diffusion coefficient ([Formula: see text]), surface chloride concentration ([Formula: see text]) and penetration depth ([Formula: see text]) are all highly time-dependent. The exposure zone, water–cement ratio and service time were also considered as relevant factors. The proposed model is then validated by two alternative tests and the results suggest that it is feasible in predicting the chloride content and penetration depth of concrete structures in a marine environment under chloride attack.
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spelling pubmed-69822162020-02-07 Prediction of Chloride Distribution for Offshore Concrete Based on Statistical Analysis Liu, Qing-feng Hu, Zhi Lu, Xian-yang Yang, Jian Azim, Iftikhar Sun, Wenzhuo Materials (Basel) Article Chloride-induced corrosion is the main threat to the service life of concrete structures. In order to better investigate chloride distribution in offshore concrete, this study proposed a new prediction model based on statistical analysis as well as a large body of experimental results collected from various sources. A detailed discussion found that the key influential parameters, such as diffusion coefficient ([Formula: see text]), surface chloride concentration ([Formula: see text]) and penetration depth ([Formula: see text]) are all highly time-dependent. The exposure zone, water–cement ratio and service time were also considered as relevant factors. The proposed model is then validated by two alternative tests and the results suggest that it is feasible in predicting the chloride content and penetration depth of concrete structures in a marine environment under chloride attack. MDPI 2020-01-01 /pmc/articles/PMC6982216/ /pubmed/31906365 http://dx.doi.org/10.3390/ma13010174 Text en © 2020 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
Liu, Qing-feng
Hu, Zhi
Lu, Xian-yang
Yang, Jian
Azim, Iftikhar
Sun, Wenzhuo
Prediction of Chloride Distribution for Offshore Concrete Based on Statistical Analysis
title Prediction of Chloride Distribution for Offshore Concrete Based on Statistical Analysis
title_full Prediction of Chloride Distribution for Offshore Concrete Based on Statistical Analysis
title_fullStr Prediction of Chloride Distribution for Offshore Concrete Based on Statistical Analysis
title_full_unstemmed Prediction of Chloride Distribution for Offshore Concrete Based on Statistical Analysis
title_short Prediction of Chloride Distribution for Offshore Concrete Based on Statistical Analysis
title_sort prediction of chloride distribution for offshore concrete based on statistical analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6982216/
https://www.ncbi.nlm.nih.gov/pubmed/31906365
http://dx.doi.org/10.3390/ma13010174
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