Durability evaluation of GFRP rebars in harsh alkaline environment using optimized tree-based random forest model

•Random forest optimized model is developed to investigate the tensile strength retention of GFRP bars in harsh environments.•The model was developed from 772 tested specimens of conditioned GFRP bars under accelerating aging.•Common statistical indices such as RMSE and R2 were used to evaluate the...

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Published inJournal of ocean engineering and science Vol. 7; no. 6; pp. 596 - 606
Main Authors Iqbal, Mudassir, Zhang, Daxu, Jalal, Fazal E.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.12.2022
Elsevier
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ISSN2468-0133
2468-0133
DOI10.1016/j.joes.2021.10.012

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Summary:•Random forest optimized model is developed to investigate the tensile strength retention of GFRP bars in harsh environments.•The model was developed from 772 tested specimens of conditioned GFRP bars under accelerating aging.•Common statistical indices such as RMSE and R2 were used to evaluate the optimized models.•The effect of GFRP bar size is significant factor in the degradation.•The existing recommendations about environmental reduction factor is conservative. GFRP bars reinforced in submerged or moist seawater and ocean concrete is subjected to highly alkaline conditions. While investigating the durability of GFRP bars in alkaline environment, the effect of surrounding temperature and conditioning duration on tensile strength retention (TSR) of GFRP bars is well investigated with laboratory aging of GFRP bars. However, the role of variable bar size and volume fraction of fiber have been poorly investigated. Additionally, various structural codes recommend the use of an additional environmental reduction factor to accurately reflect the long-term performance of GFRP bars in harsh environments. This study presents the development of Random Forest (RF) regression model to predict the TSR of laboratory conditioned bars in alkaline environment based on a reliable database comprising 772 tested specimens. RF model was optimized, trained, and validated using variety of statistical checks available in the literature. The developed RF model was used for the sensitivity and parametric analysis. Moreover, the formulated RF model was used for studying the long-term performance of GFRP rebars in the alkaline concrete environment. The sensitivity analysis exhibited that temperature and pH are among the most influential attributes in TSR, followed by volume fraction of fibers, duration of conditioning, and diameter of the bars, respectively. The bars with larger diameter and high-volume fraction of fibers are less susceptible to degradation in contrast to the small diameter bars and relatively low fiber's volume fraction. Also, the long-term performance revealed that the existing recommendations by various codes regarding environmental reduction factors are conservative and therefore needs revision accordingly.
ISSN:2468-0133
2468-0133
DOI:10.1016/j.joes.2021.10.012