Data-driven strength-based seismic damage index measurement for RC columns using crack image-derived parameters

The identification of the updated damage state of the structural components is crucial following an earthquake for safety assessment and seismic performance evaluation. The lateral strength loss in RC columns following an earthquake is measured in this paper through surface crack image analysis. The generalized fractal indices of the crack textures for damaged RC columns are considered as the quantitative representatives of the complexity and irregularity of the images. The proposed methodology is generated and verified using an extensive collected research databank comprising crack maps from experimental results on cyclic-loaded RC column specimens with varying residual strengths at pre-cap and post-cap regimes. A strength-based damage index is proposed for the measurement of the extent of strength deterioration in RC columns via five regression-based closed-form equations. The sensitivity of the proposed empirical equations to the visual damage features, structural properties, and geometric parameters is investigated. The findings of this study support the efficiency of fractal analysis for post-earthquake strength loss measurement in the RC columns with different failure modes. Finally, the efficiency of the proposed procedure in the measurement of the residual strength is assessed for a real RC column damaged in 2017, MW 7.3, Kermanshah earthquake. The updated strength values derived from the offered procedure can be incorporated in subsequent structural analysis aimed at collapse safety evaluation or potential weak story identification.