Reliability-Based Collapse Assessment of Wind-Excited Steel Structures within Performance-Based Wind Engineering
Srinivasan Arunachalam, Seymour M.J. Spence

TL;DR
This paper develops a probabilistic framework combining high-fidelity nonlinear structural modeling and stochastic wind loads to assess the collapse risk of wind-excited steel structures, accounting for uncertainties and damage mechanisms.
Contribution
It introduces a novel probabilistic collapse assessment method integrating detailed nonlinear models with wind load simulations for steel structures.
Findings
The models effectively capture progressive yielding, buckling, and fatigue phenomena.
Fatigue modeling predicts damage and fiber/section fracture under wind loading.
Fragility functions describe residual and peak story drift probabilities.
Abstract
As inelastic design for wind is embraced by the engineering community, there is an increasing demand for computational tools that enable the investigation of the nonlinear behavior of wind-excited structures and subsequent development of performance criteria. To address this need, a probabilistic collapse assessment framework for steel structures is proposed in this paper. The framework is based on the integration of a high-fidelity fiber-based nonlinear structural modeling environment with a wind-tunnel-informed stochastic wind load model to perform nonlinear time history analysis. General uncertainty is propagated using a stratified sampling scheme enabling the efficient estimation of reliabilities associated with rare events. The adopted models for simulating high-fidelity nonlinear structural behavior were found, in general, to be adequate for capturing phenomena, including…
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