Macro Modeling of Column Removal in RC Frames with Consideration of Importance Factor and Infill Walls

Document Type : Regular Paper

Authors

1 Teacher at Building Cluster, Ministry of Education, Lorestan, Iran

2 Assistant Professor, Department of Civil Engineering, Razi University, Kermanshah, Iran

3 Associate Professor, Department of Civil Engineering, Ayatollah Ozma Borujerdi University, Borujerd, Iran

Abstract

In this study, the effect of importance factor (IF) on RC frames with and without infill walls, in both with and without opening conditions, is evaluated against progressive collapse. For this purpose, RC building with the intermediate moment frame system for three levels of importance factor that these levels are intermediate, high, and very high IF is designed. OpenSees program is utilized for modeling RC frames. For this aim, the accuracy of modeling of column removal and infill walls are compared with experimental researches. In the present study, nonlinear dynamic analysis (NDA) and push-down analysis (PDA) were used for evaluating RC frames against progressive collapse in each column removal scenario. Analysis results showed that the effect of the importance factors in NDA and PDA are reduced to less than 24% and 13% when the infill walls are modeled in the frames. In the frame without infill walls, the influence of the importance factor is increased up to 36.1%. Also, in this study, it was found that the role of importance factors depends on the place of the removed column, which the effect of middle column removal is relatively twice than the corner column removal due to more redundancy. Other results about infill walls effects and opening in infill walls are presented in the paper. Finally, a proposed approach for column removal in NDA via OpenSees program is introduced, and its high accuracy is shown. This developed algorithm can remove any element of structure in different time intervals.

Keywords

Main Subjects

References

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History

  • Receive Date: 20 August 2021
  • Revise Date: 05 July 2022
  • Accept Date: 08 July 2022

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