Probabilistic Sensitivity Analysis of Fire-Induced Failure in Steel Columns

Please note that this recording is from an earlier date.

Webinar  - 0.075 CEU

Duration: 50 m

Presented by Ramla Qureshi, Ph.D.

In North America, fire resistance design of steel structures is largely prescriptive in nature, and may not explicitly account for the variability in material properties, fire exposure, and structural demand.

This study presents a reliability-based sensitivity analysis to quantify the impact of these uncertainties on the probability of failure for axially loaded steel columns under fire conditions. Using a probabilistic limit-state framework, we incorporate stochastic models for fire severity, load ratio, insulation effectiveness, and high-temperature steel degradation. Global sensitivity analysis is performed using Sobol indices and Latin Hypercube sampling to assess the influence of each input variable, such as load ratio, thermal protection performance, material degradation, and fire duration, on the overall uncertainty in structural performance and on the probability of failure.

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