Diagnosis of Historic Reinforced Concrete Buildings: A Literature Review of Non-Destructive Testing (NDT) Techniques

Boccacci, Giulia; Frasca, Francesca; Bertolin, Chiara; Siani, Anna Maria

doi:10.1016/j.prostr.2024.02.021

Procedia Structural Integrity

2024

DOI: 10.1016/j.prostr.2024.02.021

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Diagnosis of Historic Reinforced Concrete Buildings: A Literature Review of Non-Destructive Testing (NDT) Techniques

Giulia Boccacci,

Francesca Frasca,

Chiara Bertolin

et al.

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2024

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Cited by 2 publications

References 23 publications

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Novel approach to detect encasement failures in the anchorage system of guyed transmission towers by distribution of relaxation times

Scheffer de Matos,

Franke Portella,

Luiz Henke

et al. 2024

Engineering Failure Analysis

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Novel approach to detect encasement failures in the anchorage system of guyed transmission towers by distribution of relaxation times

Scheffer de Matos,

Franke Portella,

Luiz Henke

et al. 2024

Engineering Failure Analysis

View full text Add to dashboard Cite

AI-Driven Prediction of Compressive Strength in Self-Compacting Concrete: Enhancing Sustainability through Ultrasonic Measurements

Benaicha

2024

Sustainability

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This study investigates the application of artificial intelligence (AI) to predict the compressive strength of self-compacting concrete (SCC) through ultrasonic measurements, thereby contributing to sustainable construction practices. By leveraging advancements in computational techniques, specifically artificial neural networks (ANNs), we developed highly accurate predictive models to forecast the compressive strength of SCC based on ultrasonic pulse velocity (UPV) measurements. Our findings demonstrate a clear correlation between higher UPV readings and improved concrete quality, despite the general trend of decreased compressive strength with increased air-entraining admixture (AEA) concentrations. The ANN models show exceptional effectiveness in predicting compressive strength, with a correlation coefficient (R2) of 0.99 between predicted and actual values, providing a robust tool for optimizing SCC mix designs and ensuring quality control. This AI-driven approach enhances sustainability by improving material efficiency and significantly reducing the need for traditional destructive testing methods, thus offering a rapid, reliable, and non-destructive alternative for assessing concrete properties.

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Diagnosis of Historic Reinforced Concrete Buildings: A Literature Review of Non-Destructive Testing (NDT) Techniques

Cited by 2 publications

References 23 publications

Novel approach to detect encasement failures in the anchorage system of guyed transmission towers by distribution of relaxation times

Novel approach to detect encasement failures in the anchorage system of guyed transmission towers by distribution of relaxation times

AI-Driven Prediction of Compressive Strength in Self-Compacting Concrete: Enhancing Sustainability through Ultrasonic Measurements

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