Evaluation of service-life prediction model for reinforced concrete structures in chloride-laden environments

• Published in: Journal of building pathology and rehabilitation Vol. 4; no. 1
• Main Authors: Silvestro, L., Andrade, J. J. O., Dal Molin, D. C. C.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.12.2019
• Subjects: Building Materials; Building Pathology: Diagnosis and Intervention; Building Repair and Maintenance; Energy Efficiency; Engineering; Engineering Thermodynamics; Heat and Mass Transfer; Research Article; Structural Materials; Service-life prediction; Concrete; Chloride penetration; Modeling
• ISSN: 2365-3159; 2365-3167
• DOI: 10.1007/s41024-019-0059-3

Reinforced concrete structures are subjected to several degradation processes that often occur early, especially due to reinforcements corrosion. Therefore, the use of representative models for an accurate service-life prediction of reinforced concrete structures becomes indispensable. Thus, this study is aimed at evaluating the model proposed by Andrade to efficiently predict the chloride penetration in concrete structures. In addition, the input variables of this model, as well as the challenges in obtaining them are analyzed. Andrade’s model was applied in some case studies to verify their efficiency in predicting the chloride penetration in reinforced concrete structures in marine environments. The results indicate that for data with small exposure times, the model yielded similar responses to the chloride penetration in situ, with good results within an error range of 35%, associated with a maximum difference of only 4.6 mm between observed and calculated values. For the data with higher exposure times, the differences were significant, indicating the need for an alteration in order to best determine the increase in surface chloride concentration over time. Thus, it is suggested that the model undergoes modifications, mainly in relation to two fundamental aspects, (i) adopt the growth of the chloride surface concentration over time and (ii) consider the variability of the concrete characteristics and exposure conditions through a probabilistic approach.