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An Empirical Component-Based Model for Shear Behavior in High-Strength Bolts at Elevated Temperatures

Published

Author(s)

Jonathan M. Weigand, Luiz Viera, Rafaela Peixoto, Joseph A. Main, Mina S. Seif

Abstract

Steel buildings subjected to structurally significant fires experience thermal assault comprising elevated temperatures and non-uniform thermal gradients, which may induce both temperature-dependent degradation and large unanticipated loads in the steel connections. These effects of the fire on the connections are important because, in addition to resisting gravity loads, the steel connections provide critical lateral bracing to the columns, and consequently, failure of connections could lead to column instability potentially resulting in local or widespread collapse. High-strength bolts are used in nearly every steel beam-to-column connection in typical steel buildings. Thus, accurately modeling the behavior of the bolts under elevated temperatures is crucial for properly assessing the connection capacity, and by extension, is also important in evaluating the strength and stability of steel buildings subjected to fires. This paper describes a new component-based model for high-strength bolts developed based on data from high-temperature shear tests of A325 and A490 high-strength bolts. Component-based models are computationally efficient, facilitating large building-level analyses where high-fidelity modeling of the bolts would be infeasible. The component-based model is shown to accurately account for the temperature-dependent degradation of bolt shear strength and stiffness, while also providing the capability to model load reversal and bolt-shear rupture.
Citation
Journal of Constructional Steel Research
Volume
147

Keywords

Bolts, Steel, Shear, Elevated temperatures, Fire

Citation

Weigand, J. , Viera, L. , Peixoto, R. , Main, J. and Seif, M. (2018), An Empirical Component-Based Model for Shear Behavior in High-Strength Bolts at Elevated Temperatures, Journal of Constructional Steel Research, [online], https://doi.org/10.1016/j.jcsr.2018.03.034 (Accessed March 19, 2024)
Created August 1, 2018, Updated November 10, 2018