Development of a new Ni voltammetric sensor for hardened concrete conditions estimate
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2023Materia/s
Materia/s Unesco
3305.05 Tecnología del Hormigón
3303.07 Tecnología de la Corrosión
3312.08 Propiedades de Los Materiales
3312.09 Resistencia de Materiales
Resumen
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
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





