An Integrated Sensitivity and Uncertainty Quantification of Fragility Functions in RC Frames

Abstract

Uncertainty quantification is a challenging task in the risk-based assessment of buildings. This paper aims to compare reliability-based approaches to simulating epistemic and aleatory randomness in reinforced concrete (RC) frames. Ground motion record-to-record variability is combined with modeling uncertainty which is propagated by either an approximate first-order second-moment or Latin Hypercube sampling methods. The sources of uncertainties include post-yield hardening stiffness, cyclic energy dissipation capacity, and the plastic and post-cap rotation capacities of beam-column elements. All nonlinear simulations are performed with two methods: detailed incremental dynamic analysis, and the simplified SPO2IDA. The combination of all parametric methods is used to analyze two RC frames (four-story and eight-story), and the results are further post-processed to drive fragility functions. Several assumptions were investigated in curve fitting, functional form, uncertainty, and confidence intervals. The results indicate the importance of modeling uncertainty in higher seismic intensity levels. While there is a negligible difference in fragility curve fitting, its variability due to optimal intensity measure parameters is dominant.