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http://dx.doi.org/10.12989/cac.2020.26.6.497

Prediction model for concrete carbonation depth using gene expression programming  

Murad, Yasmin Z (Department of Civil Engineering, University of Jordan)
Tarawneh, Bashar K (Department of Civil Engineering, University of Jordan)
Ashteyat, Ahmed M (Department of Civil Engineering, University of Jordan)
Publication Information
Computers and Concrete / v.26, no.6, 2020 , pp. 497-504 More about this Journal
Abstract
Concrete can lose its alkalinity by concrete carbonation causing steel corrosion. Thus, the determination of the carbonation depth is necessary. An empirical model is proposed in this research to predict the carbonation depth of concrete using Gene expression programming (GEP). The GEP model was trained and validated using a large and reliable database collected from the literature. The model was developed using the six parameters that predominantly control the carbonation depth of concrete including carbon dioxide CO2 concentration, relative humidity, water-to-cement ratio, maximum aggregate size, aggregate to binder ratio and carbonation period. The model was statistically evaluated and then compared to the Jiang et al. model. A parametric study was finally performed to check the proposed GEP model's sensitivity to the selected input parameters.
Keywords
carbonation depth of concrete; gene expression programming; Jiang model;
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Times Cited By KSCI : 11  (Citation Analysis)
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