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Title: Flexural Capacity Prediction Model For Steel Fibre-Reinforced Concrete Beams

Author(s): Aocheng Zhong, Massoud Sofi, Elisa Lumantarna, Zhiyuan Zhou and Priyan Mendis

Publication: IJCSM

Volume: 15


Appears on pages(s):

Keywords: Steel fibre, Moment capacity, Flexure, Early age concrete

DOI: 10.1186/s40069-021-00461-0

Date: 7/31/2021

Steel fibre (SF) reinforcement has been shown to improve the ductility of high strength concrete (HSC), which is known to be brittle. Research conducted to date on steel fibre reinforced concrete and its effects have emphasised post-failure performance and cracking mechanism. The difficulty in predicting the behaviour of fibres is due to the randomly distributed nature of the material within the matrix leading to a probability distribution of results. Published literature has shown a benefit of adding steel fibres in terms of the ductility performance of structures. Clearly, there is a potential for such material as replacement of conventional steel reinforcement. This study proposes a theoretical model of evaluating the potential of using steel fibres as a replacement material to conventional steel reinforcement bars based on the case study, laboratory and theoretical methodologies. The compressive strength of the concrete at key dates, the effective fibre cross-sectional were measured, and a prediction model was created based on the measurement parameters. The use of four-point flexural testing, standard compressive testing and software image modelling provided the study with relevant data used to analyse and compare to the prediction. Greater ductility performance and toughness were observed with increased fibre volumes, confirming proposed predictions and conclusion drawn from published literature. No consistent or conclusive correlations between fibre volumes and the compressive strength of concrete were found. A relationship between fibre volumes and predicted moment capacities of steel fibre reinforced concrete beams was found based on the proposed theoretical flexural analysis method.