Corrosion is a major cause of deterioration in steel-reinforced concrete structures. Existing models present two major challenges: they require detailed corrosion data that are not readily accessible during non-destructive inspections, and many are derived from limited data sets, which compromises their predictive accuracy when applied at a larger scale. This study proposes a simple regression-based model that utilises easily measurable simple parameters (specifically crack width and cover-to-diameter ratio) as primary inputs to estimate the residual reinforcement area, supporting preliminary assessment of reinforced concrete (RC) structures. A database of 465 experimental data points was compiled and reduced from 17 to six parameters. Sensitivity analysis identified the crack width and cover-to-diameter ratio as the primary input parameters of the developed model. This model predicts the penetration depth and the corresponding residual bar diameter. Comparative evaluation against existing models demonstrated better predictive accuracy. The proposed model provides a practical tool for structural engineers to estimate the remaining uncorroded bar area and obtain a preliminary upper-bound estimate of the residual load-carrying capacity of RC members for preliminary assessment. The model assumes uniform corrosion and does not account for localised pitting, bond degradation or ductility reduction, and therefore is not intended to replace a detailed structural assessment.
Musa et al. (Mon,) studied this question.