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Corrosion Assessment in Reinforced Concrete Structures by Means of Embedded Sensors and Multivariate Analysis—Part 1: Laboratory Validation

Reinforced Concrete Structures (RCS) are a fundamental part of a country’s civil infrastructure. However, RCSs are often affected by rebar corrosion, which poses a major problem because it reduces their service life. The traditionally used inspection and management methods applied to RCSs are poorly...

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Autores principales: Ramón-Zamora, José Enrique, Lliso-Ferrando, Josep Ramon, Martínez-Ibernón, Ana, Gandía-Romero, José Manuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10650667/
https://www.ncbi.nlm.nih.gov/pubmed/37960566
http://dx.doi.org/10.3390/s23218869
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author Ramón-Zamora, José Enrique
Lliso-Ferrando, Josep Ramon
Martínez-Ibernón, Ana
Gandía-Romero, José Manuel
author_facet Ramón-Zamora, José Enrique
Lliso-Ferrando, Josep Ramon
Martínez-Ibernón, Ana
Gandía-Romero, José Manuel
author_sort Ramón-Zamora, José Enrique
collection PubMed
description Reinforced Concrete Structures (RCS) are a fundamental part of a country’s civil infrastructure. However, RCSs are often affected by rebar corrosion, which poses a major problem because it reduces their service life. The traditionally used inspection and management methods applied to RCSs are poorly operative. Structural Health Monitoring and Management (SHMM) by means of embedded sensors to analyse corrosion in RCSs is an emerging alternative, but one that still involves different challenges. Examples of SHMM include INESSCOM (Integrated Sensor Network for Smart Corrosion Monitoring), a tool that has already been implemented in different real-life cases. Nevertheless, work continues to upgrade it. To do so, the authors of this work consider implementing a new measurement procedure to identify the triggering agent of the corrosion process by analysing the double-layer capacitance of the sensors’ responses. This study was carried out on reinforced concrete specimens exposed for 18 months to different atmospheres. The results demonstrate the proposed measurement protocol and the multivariate analysis can differentiate the factor that triggers corrosion (chlorides or carbonation), even when the corrosion kinetics are similar. Data were validated by principal component analysis (PCA) and by the visual inspection of samples and rebars at the end of the study.
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spelling pubmed-106506672023-10-31 Corrosion Assessment in Reinforced Concrete Structures by Means of Embedded Sensors and Multivariate Analysis—Part 1: Laboratory Validation Ramón-Zamora, José Enrique Lliso-Ferrando, Josep Ramon Martínez-Ibernón, Ana Gandía-Romero, José Manuel Sensors (Basel) Article Reinforced Concrete Structures (RCS) are a fundamental part of a country’s civil infrastructure. However, RCSs are often affected by rebar corrosion, which poses a major problem because it reduces their service life. The traditionally used inspection and management methods applied to RCSs are poorly operative. Structural Health Monitoring and Management (SHMM) by means of embedded sensors to analyse corrosion in RCSs is an emerging alternative, but one that still involves different challenges. Examples of SHMM include INESSCOM (Integrated Sensor Network for Smart Corrosion Monitoring), a tool that has already been implemented in different real-life cases. Nevertheless, work continues to upgrade it. To do so, the authors of this work consider implementing a new measurement procedure to identify the triggering agent of the corrosion process by analysing the double-layer capacitance of the sensors’ responses. This study was carried out on reinforced concrete specimens exposed for 18 months to different atmospheres. The results demonstrate the proposed measurement protocol and the multivariate analysis can differentiate the factor that triggers corrosion (chlorides or carbonation), even when the corrosion kinetics are similar. Data were validated by principal component analysis (PCA) and by the visual inspection of samples and rebars at the end of the study. MDPI 2023-10-31 /pmc/articles/PMC10650667/ /pubmed/37960566 http://dx.doi.org/10.3390/s23218869 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ramón-Zamora, José Enrique
Lliso-Ferrando, Josep Ramon
Martínez-Ibernón, Ana
Gandía-Romero, José Manuel
Corrosion Assessment in Reinforced Concrete Structures by Means of Embedded Sensors and Multivariate Analysis—Part 1: Laboratory Validation
title Corrosion Assessment in Reinforced Concrete Structures by Means of Embedded Sensors and Multivariate Analysis—Part 1: Laboratory Validation
title_full Corrosion Assessment in Reinforced Concrete Structures by Means of Embedded Sensors and Multivariate Analysis—Part 1: Laboratory Validation
title_fullStr Corrosion Assessment in Reinforced Concrete Structures by Means of Embedded Sensors and Multivariate Analysis—Part 1: Laboratory Validation
title_full_unstemmed Corrosion Assessment in Reinforced Concrete Structures by Means of Embedded Sensors and Multivariate Analysis—Part 1: Laboratory Validation
title_short Corrosion Assessment in Reinforced Concrete Structures by Means of Embedded Sensors and Multivariate Analysis—Part 1: Laboratory Validation
title_sort corrosion assessment in reinforced concrete structures by means of embedded sensors and multivariate analysis—part 1: laboratory validation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10650667/
https://www.ncbi.nlm.nih.gov/pubmed/37960566
http://dx.doi.org/10.3390/s23218869
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