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A Study to Improve the Reliability of High-Strength Concrete Strength Evaluation Using an Ultrasonic Velocity Method

The ultrasonic pulse velocity (UPV) technique, which is an efficient technique for concrete quality evaluation, can be affected by several factors. Many studies have proposed compressive-strength prediction models based on UPV in concrete; however, few studies have investigated the factors resulting...

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Detalles Bibliográficos
Autores principales: Kim, Wonchang, Lee, Taegyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10608696/
https://www.ncbi.nlm.nih.gov/pubmed/37895781
http://dx.doi.org/10.3390/ma16206800
Descripción
Sumario:The ultrasonic pulse velocity (UPV) technique, which is an efficient technique for concrete quality evaluation, can be affected by several factors. Many studies have proposed compressive-strength prediction models based on UPV in concrete; however, few studies have investigated the factors resulting in statistically different UPV results for different models. This study examined the difference between compressive strengths of various concrete specimens calculated by age-dependent and temperature-dependent UPV-based prediction models. Furthermore, a statistical analysis was conducted to evaluate the influence of aggregates and water/cement ratio (design compressive strength), which are said to affect UPV, on the compressive-strength prediction models. The experimental results revealed that the residual compressive strength of concrete after high-temperature exposure was about 9.5 to 24.8% higher than the age-dependent compressive strength. By contrast, after high-temperature exposure, UPV tended to be about 34.5% lower. The compressive strengths and UPVs were significantly different with respect to high temperature, aggregate density, and design compressive strength. The compressive-strength prediction model derived from the regression analysis showed a high R(2) (average 0.91) and mean error converged to zero compared to the compressive-strength prediction model without considering these factors. Finally, the differences between the age- and temperature-based compressive-strength prediction models were analyzed according to the corresponding microstructures.