Development of a new Ni voltammetric sensor for hardened concrete conditions estimate
Developing efficient monitoring systems to control reinforced concrete structures (RCS) is still an open research line in the building sector. Thus, in this work was proposed the novelty use of Ni voltammetric sensor to control the concrete conditions by means of PCA model. The efficiency of voltamm...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Consejo General de la Arquitectura Técnica de España (CGATE) |
| Repositorio: | RIARTE |
| OAI Identifier: | oai:www.riarte.es:20.500.12251/3315 |
| Acceso en línea: | http://hdl.handle.net/20.500.12251/3315 https://doi.org/10.1016/j.snr.2023.100155 |
| Access Level: | acceso abierto |
| Palabra clave: | Sector de la vivienda Cloruros Durabilidad Hormigón armado Monitorización estructural Corrosión Sensor electroquímico Aguas residuales Depuradora Ensayos (propiedades o materiales) 3305.05 Tecnología del Hormigón 3303.07 Tecnología de la Corrosión 3312.08 Propiedades de Los Materiales 3312.09 Resistencia de Materiales 3316.13 Productos de Acero Para Construcciones 3312.12 Ensayo de Materiales 3311.02 Ingeniería de Control 3311.06 Instrumentos Eléctricos |
| Sumario: | Developing efficient monitoring systems to control reinforced concrete structures (RCS) is still an open research line in the building sector. Thus, in this work was proposed the novelty use of Ni voltammetric sensor to control the concrete conditions by means of PCA model. The efficiency of voltammetric sensors are verified in other sectors like food or wastewater treatment, where the sensors are used in liquid media, in the study was intended verify the high potential use of this sensors in porous materials such as concrete. With this purpouse the sensor response was characterized in three different concretes (w/c = 0.6, w/c = 0.5 and w/c = 0.4) and three different concrete conditions (water satured conditions, presence of chlorides and concrete carbonation). Then, was developed a PCA model, where was verified the capability of the sensor to classify the concrete state. The validation of the model pointed an acceptance range between 78.3% and 95.4% (with a 95% confidence index). © 2023 |
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