Infrastructure and transportation facilities have increased rapidly over the years. The progress has been accompanied by an increasing number of vehicle collisions with structures. This type of collision might lead to the damage, and often, collapse of the structure. In reinforced concrete (RC) structures, columns are usually the most vulnerable members exposed to collisions. However, the existing design guidelines and provisions for protection of these members against collision of vehicles are not adequate. In particular, the desired behavior and the associated performance levels of a structure during a vehicle collision are not defined. Therefore, there is need to assess the vulnerability of structures against such collisions. This research aims to develop a framework for the performance-based analysis and design of RC columns subject to vehicle impact. It helps mitigate maximum damage and achieve an economical design. The current research takes into account performance-based analysis and design as opposed to only collapse prevention design. The performance level is tied to the impact levels to estimate the reliability of the RC column for the desired performance objectives. The performance-based probabilistic models for estimating shear resistance of RC column and shear demand on RC column are developed. The reliability of the RC column subject for selected performance levels is evaluated. The performance levels are tied to impact demand and load and resistance factors are proposed to achieve desired performance objectives of the RC column subject to vehicle collision.

There has been increasing interest in evaluating the performance of existing reinforced concrete (RC) bridges just after natural disasters or man-made events especially when the defects are invisible, or in quantifying the improvement after rehabilitations. In order to obtain an accurate assessment of the reliability of a RC bridge, it is critical to incorporate information about its current structural properties, which reflects the possible aging and deterioration. This dissertation proposes to develop an adaptive reliability analysis of RC bridges incorporating the damage detection information obtained from nondestructive testing (NDT). In this study, seismic fragility is used to describe the reliability of a structure withstanding future seismic demand. It is defined as the conditional probability that a seismic demand quantity attains or exceeds a specified capacity level for given values of earthquake intensity. The dissertation first develops a probabilistic capacity model for RC columns and the capacity model can be used when the flexural stiffness decays nonuniformly over a column height. Then, a general methodology to construct probabilistic seismic demand models for RC highway bridges with one single-column bent is presented. Next, a combination of global and local NDT methods is proposed to identify in-place structural properties. The global NDT uses the dynamic responses of a structure to assess its global/equivalent structural properties and detect potential damage locations. The local NDT uses local measurements to identify the local characteristics of the structure. Measurement and modeling errors are considered in the application of the NDT methods and the analysis of the NDT data. Then, the information obtained from NDT is used in the probabilistic capacity and demand models to estimate the seismic fragility of the bridge. As an illustration, the proposed probabilistic framework is applied to a reinforced concrete bridge with a one-column bent. The result of the illustration shows that the proposed framework can successfully provide the up-to-date structural properties and accurate fragility estimates.