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Improvement, analytical verification and application of RC frame beam-column joint models

  • Fan, Guoxi (School of Engineering, Ocean University of China) ;
  • Wang, Debin (School of Civil and Safety Engineering, Dalian Jiaotong University) ;
  • Jia, Jing (School of Engineering, Ocean University of China)
  • Received : 2017.10.01
  • Accepted : 2018.02.21
  • Published : 2018.03.25

Abstract

Previous experimental researches indicate that reinforced concrete beam-column joints play an important role in the mechanical properties of moment resisting frame structures, so as to require proper design. In order to get better understanding of the beam-column joint performance, a rational model needs to be developed. Based on the former considerations, two typical models for calculating the shear carrying capacity of the beam-column joint including the inelastic reinforced concrete joint model and the softened strut-and-tie model are selected to be introduced and analyzed. After examining the applicability of two typical models mentioned earlier to interior beam-column joints, several adjustments are made to get better predicting of the test results. For the softened strut-and-tie model, four adjustments including modifications of the depth of the diagonal strut, the inclination angle of diagonal compression strut, the smeared stress of mild steel bars embedded in concrete, as well as the softening coefficient are made. While two adjustments for the inelastic reinforced concrete joint model including modifications of the confinement effect due to the column axial load and the correction coefficient for high concrete are made. It has been proved by test data that predicted results by the improved softened strut-and-tie model or the modified inelastic reinforced concrete joint model are consistent with the test data and conservative. Based on the test results, it is also not difficult to find that the improved beam-column joint model can be used to predict the joint carrying capacity and cracks development with sufficient accuracy.

Keywords

Acknowledgement

Supported by : Central Universities, National Natural Science Foundation

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