Investigation on modeling parameters of concrete beams reinforced with basalt FRP bars

Jordan CARTER, Aikaterini S. GENIKOMSOU

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PDF(1565 KB)
Front. Struct. Civ. Eng. ›› 2019, Vol. 13 ›› Issue (6) : 1520-1530. DOI: 10.1007/s11709-019-0580-0
RESEARCH ARTICLE
RESEARCH ARTICLE

Investigation on modeling parameters of concrete beams reinforced with basalt FRP bars

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Abstract

Fiber-reinforced polymer (FRP) bars are widely used as internal reinforcement replacing the conventional steel bars to prevent from corrosion. Among the different types of FRP bars, basalt FRP (BFRP) bars have been used in different structural applications and, herein, three already tested concrete beams reinforced with BFRP bars are analyzed using three-dimensional (3-D) finite element analysis (FEA). The beams were tested in four-point bending. In the FEA the behavior of concrete is simulated using the “Concrete-Damaged Plasticity” model offered in ABAQUS software. The research presented here presents a calibrated model for nonlinear FEA of BFRP concrete beams to predict their response considering both the accuracy and the computational efficiency. The calibration process showed that the concrete model should be regularized using a mesh-dependent characteristic length and material-dependent post-yield fracture and crushing energies to provide accurate mesh-size independent results. FEA results were compared to the test results with regard to failure load and crack patterns. Both the test results and the numerical results were compared to the design predictions of ACI 440.1R-15 and CSA S806-12, where CSA S806-12 seems to overestimate the shear strength for two beams.

Keywords

basalt Fiber-reinforced polymer bars / reinforced concrete beams / finite element analysis / damaged plasticity model / design codes

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Jordan CARTER, Aikaterini S. GENIKOMSOU. Investigation on modeling parameters of concrete beams reinforced with basalt FRP bars. Front. Struct. Civ. Eng., 2019, 13(6): 1520‒1530 https://doi.org/10.1007/s11709-019-0580-0

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Acknowledgements

This research was funded by the Department of Civil Engineering, Queen’s University. The authors would like to thank the Centre for Advanced Computing for the high performance computing resources that were used.

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2019 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature
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