Simplified Seismic Evaluation of Aged Corrosion Damaged Reinforced Concrete Bridge Columns as Part of Simplified Semi-Quantitative Assessment Framework
DOI:
https://doi.org/10.37256/est.4120231873Keywords:
simplified nonlinear seismic analysis, aged reinforced concrete bridge columns, reinforcement corrosion, semi-quantitative assessment frameworkAbstract
Severe reinforcement corrosion significantly reduces the structural stiffness and load-carrying capacity of Reinforced Concrete (RC) columns. The interactive effects of corrosion-induced damage and repeated traffic load cycles further accelerate bridge columns' load-carrying capacity deterioration. When subjected to seismic excitation, corrosion-affected RC columns could show a dynamic response significantly different from non-affected columns. This paper proposes a Simplified Nonlinear finite element Seismic Analysis approach (SNLSA) based on enhanced inspection of corrosion-damaged RC columns and as a handy tool for evaluating their seismic response, which is a crucial step in a semi-quantitative assessment framework. The SNLSA integrates Nonlinear Sectional Analysis (NLSA), DRAIN-RC computer program for nonlinear time history analysis, and Takeda's hysteretic analysis. The approach provides three options: (i) establish the staged failure mechanism using express analysis simulating quasi-static loading up to failure; (ii) use a more comprehensive analysis simulating cyclic loading developing the hysteretic relationships; and (iii) conduct a nonlinear full time-history analysis. The SNLSA can estimate the significant contraction of the column interaction capacity when subjected to severe corrosion damage for all load-over-capacity ratios. The SNLSA quantitatively predicts the change in the seismic performance of corrosion-affected versus as-built bridge columns. The approach could also be used to select the appropriate design option for bridge columns in seismic-critical zones.
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Copyright (c) 2022 Amina Mohammed, Husham Almansour, Beatriz Martín-Pérez
This work is licensed under a Creative Commons Attribution 4.0 International License.