Cyclic behaviour of precast beam-to-column connections: An experimental and numerical investigation

2022-01-01
Torra-Bilal, Ines
Mahamid, Mustafa
Baran, Eray
The main objective of this study is to examine the behavior of hybrid beam-column connections with numerous detailing methods to be incorporated in precast moment resisting frames under simulate reversed cyclic loading, which will lead to better understanding of their performance and safer seismic applications. To accomplish the research objectives, an integrated experimental and numerical study was conducted. The experimental part consisted of reversed cyclic loading of precast concrete beam-column specimens with six different anchorage details used in beam element, as well as monolithically cast companion specimens. In the numerical part, a nonlinear finite element analysis (FEA) approach was proposed to reproduce the experimental response of a specific type of moment resisting precast concrete beam-column connection exposed to reversed cyclic load tests. To prove the validity of the proposed finite element approach, three-dimensional (3D) finite element models were built using ABAQUS, a nonlinear finite element analysis tool, for a reference monolithic and various precast hybrid beam-column connections. The models intend to lead to comprehensive investigation of concrete and steel behavior reaching failure. A modified Concrete Damage Plasticity model (CDP) that accounts for compression-softening and tension-stiffening effect was adopted for concrete in order to reproduce the typical cyclic behavior of cracked reinforced concrete. Kinematic Bilinear Elasto-Plastic nonlinear model was used to model all steel parts with the addition of bond-slip effect for all reinforcing bars embedded in concrete.

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Citation Formats
I. Torra-Bilal, M. Mahamid, and E. Baran, “Cyclic behaviour of precast beam-to-column connections: An experimental and numerical investigation,” STRUCTURES, vol. 35, pp. 939–957, 2022, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/95023.