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This paper aims to develop a framework to assess the reliability of structures subject to a fire following an earthquake (FFE) event. The proposed framework is implemented in one seamless programming environment and is used to analyze an example nine-story steel moment-resisting frame (MRF) under an FFE. The framework includes uncertainties in load and material properties at elevated temperatures and evaluates the MRF performance based on various limit states.

Specifically, this work models the uncertainties in fire load density, yield strength and modulus of elasticity of steel. The location of fire compartment is also varied to investigate the effect of story level (lower vs higher) and bay location (interior vs exterior) of the fire on the post-earthquake performance of the frame. The frame is modeled in OpenSees to perform non-linear dynamic, thermal and reliability analyses of the structure.

Results show that interior bays are more susceptible than exterior bays to connection failure because of the development of larger tension forces during the cooling phase of the fire. Also, upper floors in general are more probable to reach specified damage states than lower floors because of the smaller beam sizes. Overall, results suggest that modern MRFs with a design that is governed by inter-story drifts have enough residual strength after an earthquake so that a subsequent fire typically does not lead to results significantly different compared to those of an event where the fire occurs without previous seismic damage. However, the seismic damage could lead to larger fire spread, increased danger to the building as a whole and larger associated economic losses.

Although the paper focuses on FFE, the proposed framework is general and can be extended to other multi-hazard scenarios.

This paper aims to present a reliability analysis of the slab panel method (SPM) for the design of composite steel floors in severe fires. Rather than seeking to accurately define failure levels, this paper highlights areas of uncertainty in design and their effect on design results, whilst providing approximate reliability levels.

A Monte Carlo simulation has been conducted using the SPM design procedure to produce probability density functions of floor capacity for various floor layouts. Statistical input variables were obtained from the literature. Different configurations, geometries and fire severities are included to demonstrate how predicted floor capacities are influenced.

From the research presented, it is clear that the predicted reliability of SPM systems varies relative to a large number of criteria, but especially parameters related to fire loading. Predicted capacities are shown to be conservative compared to results of furnace and large-scale natural fire tests, which exhibit higher fire resistance. Due to distinct fire hazard categories with associated input values, there are step discontinuities in capacity graphs.

Limited research has been done to date on the reliability of structures in fire as discussed in this paper. It is important to verify the reliability levels of systems to ensure that partial and global factors of safety are adequate. Monte Carlo simulations are shown to be effective for calculating the average floor capacities and associated standard deviations. The presentation of probability density functions for composite floors in severe fires is novel.