Residual service life of reinforced fly ash recycled aggregate concrete structures subject to carbonation

• Published in: Journal of Building Engineering Vol. 99; p. 111553
• Main Authors: Sundharam Paulpandian, Murali Kannan, Neves, Rui
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.04.2025
• Subjects: Carbonation; EnvStats package; Fly ash (FA); Gamma process; R software; Recycled aggregate concrete (RAC); Carbonation; R software; Fly ash (FA); Gamma process; EnvStats package; Recycled aggregate concrete (RAC)
• ISSN: 2352-7102; 2352-7102
• DOI: 10.1016/j.jobe.2024.111553

In fly ash recycled aggregate concrete (RAC), the stochastic reliability of carbonation is examined. This work implemented the gamma process in predicting the carbonation depth and checked with the comprehensive data collated from the literature. The parameters of the gamma process were estimated using a freeware R package named EnvStats. A case study was employed to validate the methodology and afterwards, to study the influence of updated results by fly ash in recycled aggregate concrete on the stochastic reliability of carbonation behavior by computing the probability of failure. The findings confirmed that the gamma process is suitable to study the carbonation of RAC incorporating fly ash. This process allows a full probabilistic approach, and its application is simpler than other full probabilistic methods. Guidelines for the appraisal of reinforced concrete structures shall include the gamma process as a mean to the estimate residual service life and recommend regular update of the estimation based on periodic measurements of concrete field carbonation depths. •This study focuses on the modelling of residual service life of fly ash recycled aggregate concrete.•Gamma process was implemented to provide a probabilistic analysis of carbonation for recycled aggregate concrete with fly ash.•Parameters of the gamma process were estimated using a freeware R package named EnvStats.•Gamma process enables a comprehensive probabilistic approach and is easier to apply than other full probabilistic methods.•The larger the interval in measurement of carbonation depth, the more accurate the predictions become, was observed.