Quantifying the response modification factor of RC buildings: A comparative study using nonlinear pushover analysis

Earthquake-resistant design relies on controlled inelastic structural behavior, typically incorporated into seismic codes through the response modification factor (R), which reduces elastic force demands by accounting for ductility, overstrength, and energy dissipation. However, extensive research indicates that the assumed ductility levels in code-based R values are often not representative of older reinforced concrete (RC) buildings lacking proper seismic detailing, particularly in high-risk regions such as Istanbul. This study evaluates the applicability of conventional R-factor assumptions for an existing six-story RC residential building constructed in the 1980s in Istanbul’s Kadıköy district. Nonlinear static pushover analysis was employed to assess the building’s lateral load capacity and inelastic performance under two contrasting scenarios: a code-based high ductility assumption (R = 8) and a reduced, more conservative value (R = 3).
Results demonstrate that the higher R value leads to seismic demand estimates slightly below the structural capacity, falsely indicating adequate performance and safety, which contradicts observed earthquake damage patterns in the studied structure. In contrast, the lower R value produces demand levels significantly exceeding the building’s capacity, aligning more closely with real damage observations and highlighting deficiencies in ductility and torsional resistance due to structural irregularities. These findings are consistent with prior studies emphasizing the sensitivity of R to detailing quality and structural configuration. The study underscores that adopting high R values for substandard existing buildings can result in unconservative and potentially unsafe design assessments. It is therefore recommended that reduced R values—on the order of 3 or lower—be adopted for existing RC structures in high seismic zones to better reflect their actual inelastic capacity and ensure more reliable performance evaluation.