Numerical modeling study demonstrates physics-guided stiffness degradation prediction in reinforced concrete frames, highlighting improved structural assessment during seismic loading.
Peak secant stiffness degradation in reinforced concrete (RC) columns governs how lateral stiffness is redistributed and where deformation concentrates during repeated earthquake loading. Fixed stiffness-reduction factors and prescribed degradation functions cannot simultaneously account for member properties and deformation demand. This study develops a hierarchical framework for predicting the deformation-dependent peak secant stiffness of rectangular RC columns. Separate specimen-level models estimate the first-reference peak secant stiffness, K0, and the drift capacity, θu, from mechanical descriptors. A physics-guided cumulative sequence model then predicts the normalized stiffness-degradation path, with deformation demand normalized by the predicted drift capacity, θu. Non-negative degradation increments ensure bounded, monotonic stiffness loss. On the test set, the selected K0 predictor achieved R2 = 0.935, MAE = 4.098 kN/mm, and RMSE = 7.666 kN/mm; the selected θu predictor achieved R2 = 0.927, MAE = 0.346 percentage points, and RMSE = 0.512 percentage points. With normalization based on predicted drift capacity, the degradation submodel achieved R2 = 0.9272, MAE = 0.0542, and RMSE = 0.0788, substantially outperforming constant, linear, exponential, and power-law global functions. At frame level, the predicted K^0, θ^u, and degradation ratio are incorporated into an equivalent secant-stiffness procedure. Column shear is obtained directly from the updated stiffness and interstory displacement, without a separate strength-degradation law. Comparisons with OpenSeesPy fiber-frame analyses of 12 two-, three-, and four-story frames yielded mean errors of 8.26–21.88% for base shear, 11.42–24.54% for story shear, and 10.19–23.51% for column shear; the mean absolute error in structural stiffness ratio ranged from 0.019 to 0.068. These comparisons establish a numerical consistency benchmark for the adopted frame configurations and modeling assumptions. The method is intended for stiffness-based peak-response assessment, not as a complete hysteretic constitutive model.
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Huang et al. (2026) studied this question.
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