Reducing seismic residual deformations of existing reinforced concrete frames using shape memory alloys

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Previous earthquakes have shown that seismic damage to Reinforced Concrete (RC) frames mainly concentrates in the vicinity of the beam-column joint area. It occurs in different forms including: joint shear failure, flexural failure of beams and/or columns, shear failure of beams and/or columns, and bond slip failure. While frames designed based on older code provisions are susceptible to all mentioned forms of damage, frames designed to current standards are expected to collapse due to flexural failure of their beams. Other forms of damage can co-exist in newly designed frames due to faults in the design and/or construction processes or misuse by occupants (changing the intended use and consequently the applied loads, applying temporary heavy loads, etc.). Retrofitting of existing RC frames has received significant attention from the research community during the past decades. Several retrofitting methods have been proposed. While these methods provide a solution to the flexural and shear deficiencies, they maintain a major deficiency: seismic residual deformations. These deformations result from yielding of the reinforcing bars that is necessary to dissipate the seismic energy. However they complicate post-earthquake retrofitting efforts. The uniqueness of Shape Memory Alloys (SMAs) lies in their ability to undergo large deformations and return to their undeformed shape. The proposed research provides a comprehensive experimental and analytical study that will not only provide solutions to possible deficiencies in existing RC frames, but will also significantly reduce their expected seismic residual deformations. Novel retrofitting techniques that utilize SMAs will be developed. Analytical models capable of predicting the behaviour of the retrofitted structural elements will be developed and validated using experimental tests. These models will be used to analyze full-scale frames to define optimal retrofitting strategies. The proposed research will involve the training of one PhD and three MESc candidates on state-of-the-art experimental and analytical studies. These HQP will be key personnel in shaping the future of smart structures and enhancing the competitiveness of the Canadian construction industry.