1. Water sorptivity prediction model for concrete with all coarse recycled concrete aggregates.
- Author
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Aragoncillo, Ariel Miguel, Cleary, Douglas, Thayasivam, Umashanger, and Lomboy, Gilson
- Subjects
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RECYCLED concrete aggregates , *MORTAR , *PREDICTION models , *ELECTRICAL resistivity , *MULTIPLE regression analysis , *CONCRETE - Abstract
[Display omitted] • RAC has higher water sorptivity than natural aggregate concrete. • Water sorptivity has a strong negative linear relation with electrical resistivity. • The air content of RCA affects the sorptivity of RAC. • RAC sorptivity and saturation rate can be predicted using electrical resistivity. This paper examines the water sorptivity of recycled aggregate concrete (RAC) and shows how sorptivity can be predicted using electrical resistivity as the main predictor. The measurements in 48 RAC specimens show that RAC has higher water sorptivity and lower electrical resistivity than regular concrete. RAC sorptivity and rate of saturation prediction models were developed using multiple linear regression analysis. The prediction models include electrical resistivity, percent volume of coarse recycled concrete aggregates, and air content of residual mortar as explanatory variables. A graphical calculating device based on the sorptivity regression models was also created. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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