Behavior Of BFRP-recycled Aggregate Concrete-steel Double-skin Tubular Columns Under Cyclic Axial Compression

The recycling of waste concrete can reduce the exploitation of natural resources and make full use of resources. Therefore, the application of recycled aggregate concrete (RAC) in construction is in conformation with the strategy of sustainable development. With excellent structural and ductility performance, Hybrid FRP-concrete-steel double skin tubular columns (DSTCs) attract the attentions of many scholars. A new form of DSTCs (i.e. Hybrid FRP-recycled aggregate concrete-steel double skin tubular columns) is the combination of DSTCs and recycled aggregate concrete. This new form of hybrid members which have the same advantages of DSTCs can improve the performance of recycled aggregate concrete and promote the application of recycled aggregate concrete in civil engineering. It’s necessary to have a clear understanding of the behavior of Hybrid FRP-recycled aggregate concrete-steel double skin tubular columns under cyclic axial compression before this new form of DSTCs can be adopted as earthquake-resistant columns.This paper presents an experimental study on the behavior of Hybrid FRP-recycled aggregate concrete-steel double skin tubular columns under cyclic axial compression. The experimental program included 15 Hybrid FRP-recycled aggregate concrete-steel double skin tubular columns. The key parameters considered were RAC replacement ratio and loading schemes. The experimental results show that RAC replacement ratio and loading schemes mentioned in this paper have little effect on the new DSTCs. Besides, the residual plastic strain of RAC in DSTCs is linearly related to the envelope unloading strain and the relationships between the envelope unloading strain and the residual plastic strain were not affected by RAC replacement ratio and the loading schemes. The experimental stress-strain curves of RAC in DSTCs are then compared with predictions from two existing models. The comparison suggests that Yu’s model can give reasonably accurate predictions of unloading path and that the modified Li’s model can predict the reloading path.