A simplified approach for predicting temperature in reinforced concrete members exposed to standard fire

• Published in: Fire safety journal 2013-02, Vol.56, p.39-51
• Main Authors: Kodur, V.K.R., Yu, Baolin, Dwaikat, M.M.S
• Format: Article
• Language: English
• Subjects: Applied sciences; Building structure; Building technical equipments; Buildings; Buildings. Public works; Computation methods. Tables. Charts; Concrete temperatures; Construction (buildings and works); Exact sciences and technology; Finite element analysis; Fire behavior of materials and structures; Fire protection; Fire resistance; Heat transfer thermal analysis; Reinforced concrete; Reinforced concrete structure; Structural analysis. Stresses
• ISSN: 0379-7112
• DOI: 10.1016/j.firesaf.2012.12.004

For evaluating fire resistance of a reinforced concrete member, temperature profile in the cross section of the member is required. Current simplified approaches and design graphs do not yield reliable temperature predictions in rebar and concrete. In this paper, a simplified approach is proposed for evaluating cross-sectional temperatures in fire-exposed reinforced concrete members. The approach is derived through statistical nonlinear regression analysis, utilizing data generated from finite element analysis. The parameters that were varied in the finite element analysis include sectional geometry, concrete characteristics and fire exposure conditions. The validity of the approach for different types of concrete is established by comparing predictions from the proposed equation with data from fire tests and finite element analysis. Through these comparisons it is shown that the proposed equation gives better predictions of temperatures in reinforced concrete members. The applicability of the proposed approach in design situations is illustrated though a numerical example. The simplicity of the proposed method makes it attractive for use in design situations and for incorporation in design standards. ► An approach for predicting temperatures in fire-exposed RC members is proposed. ► The temperature expression is derived through regression analysis of FE results. ► The proposed temperature expression is applicable for wide range of scenarios. ► The expression gives better predictions of temperatures than other similar methods.