Technical Papers
Jan 15, 2013

Reliability Analysis of RC Beams Exposed to Fire

Publication: Journal of Structural Engineering
Volume 139, Issue 2

Abstract

A procedure for conducting reliability analysis of RC beams subjected to a fire load is presented. This involves identifying relevant load combinations, specifying critical load and resistance random variables, and establishing a high-temperature performance model for beam capacity. Based on the procedure, an initial reliability analysis is conducted using currently available data. Significant load random variables are taken to be dead load, sustained live load, and fire temperature. Resistance is in terms of moment capacity, with random variables taken as steel yield strength, concrete compressive strength, placement of reinforcement, beam width, and thermal diffusivity. A semiempirical model is used to estimate beam moment capacity as a function of fire exposure time, which is calibrated to experimental data available in the literature. The effect of various beam parameters was considered, including cover, beam width, aggregate type, compressive strength, dead to live load ratio, reinforcement ratio, support conditions, mean fire temperature, and other parameters. Using the suggested procedure, reliability was estimated from zero to 4 h of fire exposure using Monte Carlo simulation. It was found that reliability decreased nonlinearly as a function of time, whereas the most significant parameters were concrete cover; span/depth ratio when axial restraints are present, mean fire temperature, and support conditions.

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Information & Authors

Information

Published In

Go to Journal of Structural Engineering
Journal of Structural Engineering
Volume 139Issue 2February 2013
Pages: 212 - 220

History

Received: May 28, 2011
Accepted: Mar 30, 2012
Published online: Jan 15, 2013
Published in print: Feb 1, 2013

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Authors

Affiliations

Christopher D. Eamon, M.ASCE [email protected]
Associate Professor, Civil and Environmental Engineering, Wayne State Univ., Detroit, MI 48202 (corresponding author). E-mail: [email protected]
Elin Jensen, M.ASCE
Associate Dean of Graduate Studies and Research, Lawrence Technological Univ., Southfield, MI 48075.

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