Statistical distribution of seismic performance criteria of retrofitted multi-column bridge bents using incremental dynamic analysis: a case study

Abstract

Probabilistic performance assessment requires the development of probability distributions that can predict different performance levels of structures with reasonable accuracy. This study evaluates the performance of a non-seismically designed multi-column bridge bent retrofitted with four different alternatives, and based on their performance under an ensemble of earthquake records it proposes accurate prediction models and distribution fits for different performance criteria as a case study. Here, finite element methods have been implemented where each retrofitting technique has been modeled and numerically validated with the experimental results. Different statistical distributions are employed to represent the variation in the considered performance criteria for the retrofitted bridge bents. The Kolmogorov-Smirnov goodness-of-fit test was carried out to compare different distributions and find the suitable distribution for each performance criteria. An important conclusion drawn here is that the yield displacement of CFRP, steel, and ECC jacketed bridge bents are best described by a gamma distribution. The crushing displacement and crushing base shear of all four retrofitted bent follow a normal and Weibull distribution, respectively. A probabilistic model is developed to approximate the seismic performance of retrofitted bridge bents. These probabilistic models and response functions developed in this study allow for the performance prediction of retrofitted bridge bents.