# Probability-Based Concrete Carbonation Prediction Using On-Site Data
## 5 Application Examples
### Subject Bridges  
The following three different concrete bridges were used to validate the proposed approach in this study: (1) The Gajwa IC viaduct applied in this study was constructed in 1986. It is a type-1 infrastructure with a total length of 500 m. It is located in Gajwadong, Seogu, Incheon. The superstructure is a steel box girder and its substructure is an inverted T-type with a pile foundation. (2) The Noryang bridge (old bridge), which is made of concrete structures is a type-1 infrastructure located in Dongjakgu, Seoul, the center of the city. It was constructed in 1987. Its superstructure is comprised of PSC box girders and its substructure is Rahmen type with pile and well foundations. (3) The Geoje bridge, a concrete structure, is a type-2 infrastructure with a total length of 740 m. It is located in Geoje, Gyeongsangnam-do, Korea. It was constructed in 1971. The superstructure comprises PSC-beams, RC box girders, and steel-plate girders while its substructure is Rahmen type with pile and well foundations.  
As part of an in-depth safety examination, cores were collected from an inverted T-type RC pier from the Gajwa IC viaduct in 1997, 2002, 2005, and 2010. From a pier at the Noryang bridge, cores were collected in 1997, 2004, 2009, and 2014 to measure carbonation. From a girder of the Geoje bridge, cores were collected in 1998, 2005, 2010, and 2015 [30]. To calculate the reliability of the concrete structures, the means and standard deviations of concrete covers under similar environmental conditions with the subject bridges were investigated, as shown in Table 4. These on-site data of concrete structures reflect different environmental conditions. As shown in Table 5, the design variables of carbonation in the subject bridges were considered in the proposed carbonation prediction approach. Random variables of CO\({}_{2}\) diffusion coefficient \(D_{CO_{2}}\), atmospheric CO\({}_{2}\) concentration \(C_{CO_{2}}\), and CO\({}_{2}\) uptake \(a\) with cement hydration \(\alpha_{H}\) were used as design variables to determine durability. Values shown in Table 5 were used due to the absence of data to determine prior probability distribution. Except for the CO\({}_{2}\) diffusion coefficient, each design variable in the proposed approach was applied in the form of a constant using tables and equations for Portland cement (TYPE I) in this study.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Environmental** & **Number of On-Site** & **Mean (mm)** & **Standard Deviation** \\
**Conditions** & **Data** & **Mean (mm)** & **(mm)** \\ \hline On land & 540 & 61.66 & 32.50 \\ \hline Above the river \({}^{*}\) & 399 & 57.17 & 33.73 \\ \hline Above the sea & 117 & 62.44 & 49.57 \\ \hline \end{tabular} \({}^{*}\) Located in the center of the city.  
\end{table}
Table 4: Statistical data of concrete cover thickness of subject bridges according to environmental conditions.  
Figure 6: Sensitivity analysis for the optimized number of on-site data. (**a**) Gajwa IC viaduct; (**b**) Noryang bridge; (**c**) Geoje bridge.  
On-site inspection data of carbonation depth, which is an in-depth safety examination conducted for five year terms, were applied to the proposed approach. In addition, the durability analysis for predicting the remaining life of the subject bridges was carried out through reliability indices.