Many reinforced concrete (RC) buildings built before the adoption of modern seismic codes in high seismic regions need to be retrofitted to perform well in a major earthquake. This study introduces a new retrofit method for code-deficient reinforced concrete shear walls that are vulnerable to non-ductile failure modes due to improper detailing or lack of well-confined boundary elements. The retrofit method combines weakening of shear walls with a base cut and self-centering of the walls with the addition of external unbonded post-tensioned strands. The retrofitted walls are expected to have controlled rocking behavior as opposed to the original walls that undergo shear and flexure and are expected to have minimized damage caused by earthquakes resulting in shorter repair times and lower repair costs. Three-dimensional finite element models of pre-and post-retrofit shear walls under cyclic lateral loading were used to identify working details of the retrofit method. To transfer shear at base and minimize shear slip, shear keys and other non-straight wall base cut shapes were explored. The contribution of shear, flexure, and rocking to the global response were measured and compared for pre-and postretrofit walls. Results of analysis showed that rocking is the governing behavior for the retrofitted walls and contribution of shear to displacements decreased due to retrofit. Changes in residual displacements, energy dissipation, strength, and secant stiffness due to retrofit were documented.

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This paper presents an innovative method to quantify damage based on surface cracks of reinforced concrete shear walls (RCSWs). The key idea is to use artificial intelligence and convert crack patterns to graphs. In this method, the mathematics of graph theory is used to extract information (graph‐based features) from crack patterns and use them for crack quantification. The proposed graph features are used in linear regression and leave‐one‐out cross‐validation to predict the mechanical features calculated for each RCSW: Park and Ang damage index and the dissipated energy. Among the three general stages of damage, which are safe, questionable, and not safe, this paper focuses on quantifying the second stage. To validate the approach, crack images of three RCSWs are used. The walls had different aspect ratios (0.54, 0.94, and 2.00) and were subject to quasi‐static cyclic loading. Regression results demonstrate low root mean squared errors and high coefficients of determination (R2 scores above 0.845). This proves the ability of the proposed graph‐based method in quantifying damage based on surface crack patterns.

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