Prediction Model for the Carbonation of Post-Repair Materials in Carbonated RC Structures
AbstractConcrete carbonation damages the passive film that surrounds reinforcement bars, resulting in their exposure to corrosion. Studies on the prediction of concrete carbonation are thus of great significance. The repair of pre-built reinforced concrete (RC) structures by methods such as remodeling was recently introduced. While many studies have been conducted on the progress of carbonation in newly constructed buildings and RC structures fitted with new repair materials, the prediction of post-repair carbonation has not been considered. In the present study, accelerated carbonation was carried out to investigate RC structures following surface layer repair, in order to determine the carbonation depth. To validate the obtained results, a second experiment was performed under the same conditions to determine the carbonation depth by the Finite Difference Method (FDM) and Finite Element Method (FEM). For the accelerated carbonation experiment, FDM and FEM analyses, produced very similar results, thus confirming that the carbonation depth in an RC structure after surface layer repair can be predicted with accuracy. The specimen repaired using inhibiting surface coating (ISC) had the highest carbonation penetration of 19.81, while this value was the lowest for the corrosion inhibiting mortar (IM) with 13.39 mm. In addition, the carbonation depth predicted by using the carbonation prediction formula after repair indicated that that the analytical and experimental values are almost identical if the initial concentration of Ca(OH)2 is assumed to be 52%. View Full-Text
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Lee, H.-M.; Lee, H.-S.; Singh, J.K. Prediction Model for the Carbonation of Post-Repair Materials in Carbonated RC Structures. Materials 2017, 10, 492.
Lee H-M, Lee H-S, Singh JK. Prediction Model for the Carbonation of Post-Repair Materials in Carbonated RC Structures. Materials. 2017; 10(5):492.Chicago/Turabian Style
Lee, Hyung-Min; Lee, Han-Seung; Singh, Jitendra K. 2017. "Prediction Model for the Carbonation of Post-Repair Materials in Carbonated RC Structures." Materials 10, no. 5: 492.
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