Technical Papers
Mar 16, 2015

Probabilistic Fire Analysis: Material Models and Evaluation of Steel Structural Members

Publication: Journal of Structural Engineering
Volume 141, Issue 12

Abstract

This paper provides a methodology to perform probabilistic analysis of steel structural members under fire loading. As part of developing the methodology, probabilistic models are proposed for mechanical and thermal properties of steel and thermal properties of insulating materials. The two important mechanical properties of steel that significantly influence the results are (1) yield strength, and (2) modulus of elasticity. The models developed for thermal properties include specific heat, thermal conductivity, and thermal strain of steel; and density, thermal conductivity and specific heat for insulating materials. A Bayesian statistical approach is used to develop the proposed probabilistic models using the data available in the literature. The proposed probabilistic models are compared to the available deterministic models from codes and standards. After models are developed for temperature-dependent material properties, a procedure to perform probabilistic analysis of a steel member and an application of the developed models for material properties is explained. A probabilistic analysis of the member makes it possible to calculate the probability of failure and the cumulative distribution function for failure time of the member. The procedure is illustrated with a case study, where the probabilistic performance of a steel perimeter column is examined under thermal loading.

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Go to Journal of Structural Engineering
Journal of Structural Engineering
Volume 141Issue 12December 2015

History

Received: Jul 5, 2014
Accepted: Jan 14, 2015
Published online: Mar 16, 2015
Discussion open until: Aug 16, 2015
Published in print: Dec 1, 2015

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Negar Elhami Khorasani [email protected]
Graduate Student, Dept. of Civil and Environmental Engineering, Princeton Univ., Princeton, NJ 08544 (corresponding author). E-mail: [email protected]
Paolo Gardoni, M.ASCE [email protected]
Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of Illinois, Urbana-Champaign, IL 61801. E-mail: [email protected]
Maria Garlock, M.ASCE [email protected]
Associate Professor, Dept. of Civil and Environmental Engineering, Princeton Univ., Princeton, NJ 08544. E-mail: [email protected]

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