Prediction and sensitivity analysis of compressive strength in segregated lightweight concrete based on artificial neural network using ultrasonic pulse velocity
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Título: | Prediction and sensitivity analysis of compressive strength in segregated lightweight concrete based on artificial neural network using ultrasonic pulse velocity |
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Autor/es: | Tenza-Abril, Antonio José | Villacampa, Yolanda | Solak, Afonso M. | Baeza Brotons, Francisco |
Grupo/s de investigación o GITE: | Tecnología de Materiales y Territorio (TECMATER) | Modelización Matemática de Sistemas | Ingeniería del Terreno y sus Estructuras (InTerEs) |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Ingeniería Civil | Universidad de Alicante. Departamento de Matemática Aplicada |
Palabras clave: | ANN | Compaction | Concrete | Lightweight | Prediction | Segregation | Vibration |
Área/s de conocimiento: | Ingeniería de la Construcción | Matemática Aplicada |
Fecha de publicación: | 20-nov-2018 |
Editor: | Elsevier |
Cita bibliográfica: | Construction and Building Materials. 2018, 189: 1173-1183. doi:10.1016/j.conbuildmat.2018.09.096 |
Resumen: | Due to the low density of the aggregates used, lightweight aggregate concrete (LWAC) is susceptible to segregation because of the differences between the densities of their components. The segregation in LWAC causes a great variability in the concrete properties causing negative effects in its mechanical properties and durability. Ultrasonic velocity and artificial neural network (ANN) were applied by diagnosis and prediction in the impact of the compressive strength in LWAC specimens. 640 experimental observations were used to select the best ANN model. A sensitivity analysis was performed to observe the response of the model to perturbations in longitudinal wave velocity up to ±10% of the value observed experimentally. ANN was found to be suitable to predict the compressive strength through ultrasonic pulse velocity. This study leads to future research in non-destructive measurements to describe the segregation phenomenon in LWAC. |
Patrocinador/es: | This research was supported by the University of Alicante (GRE13-03) and (VIGROB-256). |
URI: | http://hdl.handle.net/10045/80949 |
ISSN: | 0950-0618 (Print) | 1879-0526 (Online) |
DOI: | 10.1016/j.conbuildmat.2018.09.096 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2018 Elsevier Ltd. |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.1016/j.conbuildmat.2018.09.096 |
Aparece en las colecciones: | INV - INTERES - Artículos de Revistas INV - TECMATER - Artículos de Revistas INV - MMS - Artículos de Revistas INV - BIMAEC - Artículos de Revistas |
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Archivo | Descripción | Tamaño | Formato | |
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2018_Tenza-Abril_etal_ConsBuilMat_final.pdf | Versión final (acceso restringido) | 3,51 MB | Adobe PDF | Abrir Solicitar una copia |
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