PSI - Issue 70

Edavalath Nadeem et al. / Procedia Structural Integrity 70 (2025) 19–26

25

Table 2. Median values of fragility ( AvgSa (g) ) DS1 DS2 DS3

DS4 3.35 9.35 2.95

Component Fragility for µ ϕ -m Component Fragility for µ ϕ -r Combined Fragility ( µ ϕ -mr )

0.13 0.09 0.07

0.80 1.20 0.59

1.97 4.38 1.65

Fig. 5. Median values of fragility ( AvgSa(g) ).

7. Conclusions This study presents a comprehensive seismic fragility assessment of a representative RC bridge, incorporating both maximum and residual column curvature ductility as critical Engineering Demand Parameters. A detailed nonlinear finite element model is developed in OpenSees, capturing realistic material behavior, boundary conditions, and seismic interactions. Nonlinear time history analyses conducted using a robust suite of ground motion records revealed a significant correlation between maximum and residual column curvature ductility responses. This correlation enabled the derivation of damage state thresholds for residual column curvature ductility, which are subsequently used to develop fragility curves. By employing the first-order reliability method, the individual fragilities are integrated into a combined fragility framework. The proposed dual-parameter approach provides a more holistic representation of seismic performance by accounting for both immediate and residual structural demands. It enhances the predictive capability for post-earthquake damage evaluation and can inform more resilient bridge design and retrofit strategies. Further for any given damage state, the combined fragility median value yields lower numerical values in terms of average spectral acceleration compared to the other two cases, indicating the relevance and effectiveness of this approach. Lower the median values larger is the seismic vulnerability. For example, for damage state 4, the normalized median fragility values for maximum and residual curvature ductility are 3.35 and 9.35, respectively. However, in the combined case, this value decreases to 2.95. 8. References Aditya, P. A., Navvar, K. M., Bahubali, J. K., Pandikkadavath, M. S., Mangalathu, S., 2025. Near-fault seismic vulnerability assessment of corrosion inflicted steel moment resisting frames. Journal of Constructional Steel Research, 229, 109527. Anand, T., Pandikkadavath, M. S., Mangalathu, S., 2024. Near-field seismic response assessment of buckling-restrained braced frames for different engineering demand parameters. Journal of Constructional Steel Research, 216, 108583. Baker, J. W., 2015. Efficient analytical fragility function fitting using dynamic structural analysis. Earthquake Spectra, 31(1), 579 – 599. Baker, J. W., Ling, T., Shahi, S. K., Jayaram, N., 2011. New Ground Motion Selection Procedures and Selected Motions for the PEER Transportation Research Program, Draft Report, Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA. Bianchini, M., Diotallevi, P.P., Baker, J.W., 2010. Prediction of inelastic structural response using an average of spectral accelerations. International Conference on Structural Safety and Reliability 1317,2164 – 2171. Caltrans seismic design criteria., 2019. California Department of Transportation, Sacramento, California. Chang, G.A., Mander, J.B., 1994. Seismic Energy Based Fatigue Damage Analysis of Bridge Columns: Part 1 Evaluation of Seismic Capacity, Technical Report NCEER-94 – 0006, State University of New York, Buffalo, New York. Chang, K.C., Chang, D.W., Tsai, M.H., Sung, Y.C., 2000. Seismic performance of highway bridges. Earthquake Engineering and Engineering Seismology 2, 55-77. Chen, X., 2020. System fragility assessment of Tall-Pier bridges subjected to Near-Fault ground motions. Journal of Bridge Engineering, 25(3).