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Reliability-Based Collapse Assessment of Wind-Excited Steel Structures within Performance-Based Wind Engineering.
- Source :
- Journal of Structural Engineering; Sep2022, Vol. 148 Issue 9, p1-16, 16p
- Publication Year :
- 2022
-
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 progressive yielding, buckling, and low-cycle fatigue, that are essential for wind induced collapse analysis. In particular, the adopted fatigue model was found to be capable of predicting damage and potential fiber/section fracture associated with non–fully reversing stress-strain cycles that are characteristic of wind loading. Through illustration on a 45-story archetype steel building, critical discussions on the types of observed collapse mechanisms, the difference between along-wind and across-wind nonlinear behavior, reliabilities associated with first yield, and collapse are presented. A probabilistic description of the residual and peak story drifts is also provided through development of fragility functions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 07339445
- Volume :
- 148
- Issue :
- 9
- Database :
- Complementary Index
- Journal :
- Journal of Structural Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 158012802
- Full Text :
- https://doi.org/10.1061/(ASCE)ST.1943-541X.0003444