Probabilistic Seismic Demand Models for Shape Memory Alloy Retrofitted RC Bridge Columns

Abstract

This numerical study aimed to develop probabilistic seismic demand models for RC bridge columns, vulnerable to failure due to lack of flexural ductility, that have been retrofitted using a newly emerging active confinement technique. The new technique involved the application of thermally prestressed spirals made of a shape memory alloy (SMA) at the plastic hinge region of the columns. Columns with different fundamental time periods were chosen, and retrofitting schemes corresponding to three confinement levels were explored. The performance of the retrofitted columns under ground motion records was assessed using four demand measures (DMs)—maximum drift, residual drift, energy-based concrete damage index, and low cycle fatigue based steel damage index The suitability of eight intensity measures (IMs) for the development of probabilistic demand models to predict the DMs was explored. The final demand models, developed using IMs that predicted the DMs with least dispersion, were presented and compared to understand the effect of lateral active confinement. The results indicated that increasing the confinement reduced the damage in concrete substantially, whereas the damage associated with low-cycle fatigue of steel was also reduced. Higher levels of active confinement were also seen to be effective in reducing the residual drifts of long-period columns.