Simplified proposal for the temperature field of steel-reinforced CFST columns exposed to fire

Abstract

Concrete-filled steel tubular (CFST) columns are composite sections that may contribute to reduce the environmental impact in construction through a more efficient use of resources. By embedding a steel profile inside a CFST section, a new typology is generated, the so-called steel-reinforced concrete-filled steel tubular (SR-CFST) columns, which may enhance not only the structural capacity of these composite columns at room temperature but also their fire performance. This paper focuses on studying the thermal behaviour of SR-CFST columns under fire conditions, for which purpose a two-dimensional finite element model was developed by the authors and validated by comparing the temperature distribution results with experimental tests available in the literature. Subsequently, parametric studies were carried out to analyse the influence of the relevant parameters – cross-section shape, outer tube thickness, inner steel profile dimensions, section factor – over the cross-sectional capacity of SR-CFST columns exposed to a standard ISO 834 fire. Using the data obtained from the parametric studies, a simplified temperature distribution proposal was derived. In the presented proposal, the composite section was divided onto four components (hollow steel tube, concrete infill, inner steel profile web and flanges) and simplified equations and tables were developed through statistical data processing in order to find the representative equivalent temperature of each part of the section. By doing so, the reduced cross-sectional capacity of a SR-CFST column at a given fire resistance period can be easily evaluated by using a single strength and stiffness value for each component of the section corresponding to its assigned equivalent temperature. This simplified approach may be helpful for practitioners in the fire design process of SR-CFST columns, for which the current provisions in Eurocode 4 Part 1.2 do not provide guidance in predicting the temperature field.