Novel empirical model for predicting residual flexural capacity of corroded steel reinforced concrete beam

Abstract

In this study, a total of 177 flexural experimental tests of corroded reinforced concrete (CRC) beams were collected from the published literature. The database of flexural capacity of CRC beam was established by using unified and standardized experimental data. Through this database, the effects of various parameters on the flexural capacity of CRC beams were discussed, including beam width, the effective height of beam section, ratio of strength between longitudinal reinforcement and concrete, concrete compressive strength, and longitudinal reinforcement corrosion ratio. The results indicate that the corrosion of longitudinal reinforcement has the greatest effect on the residual flexural capacity of CRC beams, while other parameters have much less effect. In addition, six available empirical models for calculating the residual flexural strength of CRC beams were also collected and compared with each other based on the established database. It indicates that though five of six existing empirical models underestimate the flexural capacity of CRC beams, there is one model overestimating the flexural capacity. Finally, a newly developed empirical model is proposed to provide accurate and effective predictions in a large range of corrosion ratio for safety assessment of flexural failure of CRC beams confirmed by the comparisons.

Keywords

CRC beams / flexural capacity / steel corrosion / database / empirical models

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Acknowledgements

The authors acknowledge the research supports from the National Natural Science Foundation of China (Grant Nos. 51820105014, 51738001, U1934217) and the research funds from Australian Research Council (DE150101751) and ARC Industrial Transformation Research Hub Component Project “Nano-geopolymer composites for underground prefabricated structures” with Wuhan Zhihe Geotechnical Engineering Co., Ltd. The authors are also grateful for the financial supports of the University of Technology Sydney Research Academic Program at Tech Laboratory (UTS RAPT) and University of Technology Sydney Tech Laboratory Blue Sky Research Scheme.

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