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Optimization of Mortar Curing Control Using Artificial Intelligence and Ultrasonics


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DOI: https://doi.org/10.15866/iremos.v16i5.24018

Abstract


The hardening process of mortar is a key element in construction and the quality of the structure. As the mortar solidifies and hardens, its properties and quality evolve, directly affecting the strength and durability of the built structure. In this work, a control that provides essential information on the evolution of mortar hardening over time is carried out. Ultrasonic testing provides an effective non-destructive solution for monitoring the setting and hardening of mortars by measuring its viscoelastic properties. However, this analysis carried out during the 28-day control period can lead to deterioration of the transducers and cables, affecting their performance. In this respect, our research is at the heart of current concerns about sustainable construction and technical efficiency, which implies optimization using a tool based on artificial intelligence neural networks. The aim of this work is to reduce the time and number of measurements carried out by an operator, while maintaining the quality of the mortar control by obtaining reliable data on the evolution of the reflection coefficient of ultrasonic waves. The results obtained in this work show that our neural network based regression model is both powerful and efficient. It is able to easily reproduce existing relationships in the training data and to optimize the experimental work by reducing the number of acquisitions from 828 to 19. All regressions performed by the model show high coefficients of determination, runtimes and success rates, confirming the validity of this model.
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Keywords


Artificial Intelligence; Ultrasonics; Non-Destructive Testing; Mortar; Neural Network; Coefficient of Determination; Reflection Coefficient; Neural Network Regression MLP

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References


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