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Corroded RC beam experiences different deterioration problems that affect its load-carrying capacity, namely loss of bond between reinforcement bars and the surrounding concrete, cracking or spalling of concrete cover, and loss in diameter of the rebar. This paper describes a study on three-dimensional (3D) finite element (FE) modeling carried out on the ABAQUS platform for the prediction of the static flexure load-carrying capacity of non-corroded and corroded reinforced concrete (RC) simply supported beams. The effectiveness of this three-dimensional (3D) finite element (FE) model was assessed by validating the simulation results with experimental test results available in the literature. In the present study, corrosion caused damages like bond loss, loss in the concrete cover region, loss in reinforcement area, and loss in reinforcement strength considered in the modeling of corroded beams. The cohesive surface interaction approach was used to simulate the critical bond behavior between rebars and concrete for both non-corroded and corroded RC beams. The modeling procedure in ABAQUS is cumbersome and requires significant attention if done using software GUI. In this study, to make the RC beam modeling procedure convenient and faster, a Python programming script was developed. The results show that the degradation in corroded rebars had a more significant effect on the load-carrying capacity of the member as compared to that of degradation of the concrete due to cracking and the degradation of bond-slip performance between the rebar and concrete. Degradation of the concrete cover region did not have a significant effect on the flexure load-carrying capacity while it had a significant impact on the corresponding deflection of the beam. The FE modeling results (including crack pattern, flexural strength, and stiffness) were found to be in close agreement with the corresponding experimental test results. The developed Python algorithm (script) alleviates significant modeling time with minimum inputs compared to that of ABAQUS GUI.

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Analytical Evaluation of Load-Carrying Capacity of Corroded Reinforced Concrete Beams

  • 会议论文

  • 发表日期：

    2025年

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  • Jaykumar Viradiya,
  • Rishi Gupta,
  • Urmil Dave

摘要

Corroded RC beam experiences different deterioration problems that affect its load-carrying capacity, namely loss of bond between reinforcement bars and the surrounding concrete, cracking or spalling of concrete cover, and loss in diameter of the rebar. This paper describes a study on three-dimensional (3D) finite element (FE) modeling carried out on the ABAQUS platform for the prediction of the static flexure load-carrying capacity of non-corroded and corroded reinforced concrete (RC) simply supported beams. The effectiveness of this three-dimensional (3D) finite element (FE) model was assessed by validating the simulation results with experimental test results available in the literature. In the present study, corrosion caused damages like bond loss, loss in the concrete cover region, loss in reinforcement area, and loss in reinforcement strength considered in the modeling of corroded beams. The cohesive surface interaction approach was used to simulate the critical bond behavior between rebars and concrete for both non-corroded and corroded RC beams. The modeling procedure in ABAQUS is cumbersome and requires significant attention if done using software GUI. In this study, to make the RC beam modeling procedure convenient and faster, a Python programming script was developed. The results show that the degradation in corroded rebars had a more significant effect on the load-carrying capacity of the member as compared to that of degradation of the concrete due to cracking and the degradation of bond-slip performance between the rebar and concrete. Degradation of the concrete cover region did not have a significant effect on the flexure load-carrying capacity while it had a significant impact on the corresponding deflection of the beam. The FE modeling results (including crack pattern, flexural strength, and stiffness) were found to be in close agreement with the corresponding experimental test results. The developed Python algorithm (script) alleviates significant modeling time with minimum inputs compared to that of ABAQUS GUI.