An Investigation of the Behavior of Structural Systems with Modeling Uncertainties

Abstract

Recent advancements in earthquake engineering have caused a movement toward a probabilistic quantification of the behavior of structural systems. Analysis characteristics, such as ground motion records, material properties, and structural component behavior are defined by probabilistic distributions. The response is also characterized probabilistically, with distributions fitted to analysis results at intensity levels ranging from the maximum considered earthquake ground motion to collapse. Despite the progress toward a probabilistic framework, the variability in structural analysis results due to modeling techniques has not been considered.

This work investigates the uncertainty associated with modeling geometric nonlinearities and Rayleigh damping models on the response of planar frames at multiple ground motion intensity levels. First, an investigation is presented on geometric nonlinearity approaches for planar frames, followed by a critical review of current damping models. Three frames, a four-story buckling restrained braced frame, a four-story steel moment resisting frame, and an eight-story steel moment resisting frame, are compared using two geometric nonlinearity approaches and five Rayleigh damping models. Static pushover analyses are performed on the models in the geometric nonlinearities study, and incremental dynamic analyses are performed on all models to compare the response at the design based earthquake ground motion (DBE), maximum considered earthquake ground motion (MCE), and collapse intensity levels. The results indicate noticeable differences in the responses at the DBE and MCE levels and significant differences in the responses at the collapse level. Analysis of the sidesway collapse mechanisms indicates a shift in the behavior corresponding to the different modeling assumptions, though the effects were specific to each frame.

The FEMA P-695 Methodology provided a framework that defined the static and dynamic analyses performed during the modeling uncertainties studies. However, the Methodology is complex and the analyses are computationally expensive. To expedite the analyses and manage the results, a toolkit was created that streamlines the process using a set of interconnected modules. The toolkit provides a program that organizes data and reduces mistakes for those familiar with the process while providing an educational tool for novices of the Methodology by stepping new users through the intricacies of the process.

The collapse margin ratio (CMR), calculated in the Methodology, was used to compare the collapse behavior of the models in the modeling uncertainties study. Though it provides a simple scalar quantity for comparison, calculation of the CMR typically requires determination of the full set of incremental dynamic analysis curves, which require prohibitively large analysis time for complex models. To reduce the computational cost of calculating the CMR, a new parallel computing method, referred to as the fragility search method, was devised that uses approximate collapse fragility curves to quickly converge on the median collapse intensity value. The new method is shown to have favorable attributes compared to other parallel computing methods for determining the CMR.