Fire behaviour and design of hybrid fibre reinforced high-performance concrete columns subjected to uniaxial bending

This paper presents an experimental programme and a fire design model on hybrid fibre reinforced high-performance concrete (HPC) columns under ISO 834 heating curve. To date, there are very few experimental works on HPC columns subjected to eccentric loading under fire conditions. Therefore, a total...

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Bibliographic Details
Main Authors: Du, Panwei, Yang, Yaowen, Tan, Kang Hai
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2022
Subjects:
Online Access:https://hdl.handle.net/10356/159857
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Institution: Nanyang Technological University
Language: English
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Summary:This paper presents an experimental programme and a fire design model on hybrid fibre reinforced high-performance concrete (HPC) columns under ISO 834 heating curve. To date, there are very few experimental works on HPC columns subjected to eccentric loading under fire conditions. Therefore, a total of six specimens are tested to investigate the effects of load eccentricity and slenderness ratio on spalling and structural behaviour of HPC columns. Material properties including compressive strength, residual flexural strength and spalling behaviour under unstressed state but subject to transient heating are presented to get an overview of the performance of HPC. Following that, the test results of column specimens are discussed in terms of temperature distribution, mid-height deflection, axial deformation, failure mode and fire endurance. No spalling is observed in all the specimens owing to the synergistic effect of hybrid polypropylene and steel fibres. Test results show that mid-height deflection and axial contraction increase with an increase of load eccentricity. A simplified fire design model incorporating fibre reinforced concrete design is adopted based on 500 °C isotherm method. The model is verified with test data and it shows that 400 °C isotherm depth could provide safe and accurate predictions for HPC columns.