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

Negar Elhami Khorasani, Paolo Gardoni, Maria Eugenia Moreyra Garlock

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

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.

Original languageEnglish (US)
Article number04015050
JournalJournal of Structural Engineering (United States)
Volume141
Issue number12
DOIs
StatePublished - Dec 1 2015

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Building and Construction
  • Materials Science(all)
  • Mechanics of Materials
  • Mechanical Engineering

Keywords

  • Bayesian methodology
  • Logistic function
  • Member analysis
  • Perimeter column
  • Probabilistic models
  • Structural safety and reliability
  • Thermal load
  • Thermal properties of steel

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