Probabilistic capacity model and fragility estimates for composite floor systems subjected to column loss

This paper presents probabilistic capacity models for composite floor systems subjected to column loss. The probabilistic capacity models are formulated by adding explanatory terms to an existing deterministic model. The explanatory terms are selected to correct the bias in deterministic capacity model. After that, virtual experiment data generated from finite element simulations are used to calibrate the model parameters. The finite element models consider the effect of axial loading on steel connection and the slab membrane action. The calibration of model parameters is conducted using the Bayesian inference approach. As an application and validation of the probabilistic capacity models, fragility analyses of typical composite floor systems are carried out. The developed fragility curves are compared with those from finite element analysis cooperated with Monte Carlo simulation. The comparison results show that the proposed capacity models are considered reasonable in predicting the resistance capacity of the composite floor and seek a compromise between model accuracy and computational efficiency. The proposed capacity models can be used to carry out a rapid fragility analysis against progressive collapse.