Seismic performance of reinforced concrete columns with an assembled UHPC stay-in-place formwork

Existing studies on columns with a stay-in-place formwork mostly focus on those with integrated formwork. A few researchers have mainly studied the axial compression performance or eccentric compression performance of composite columns with stay-in-place formwork. However, existing research on the seismic performance of composite columns is quite limited. This paper presents an experimental study to investigate the seismic performance of composite columns with an assembled UHPC stay-in-place formwork. Six column specimens with various assembly methods and surface treatments of a UHPC stay-in-place formwork and one reference specimen for reinforced concrete (RC) columns built by temporary formworks were designed. The seismic performances of the composite columns were investigated through quasi-static tests, and the results were analyzed in terms of seismic performance indices, such as failure mode, hysteresis curve, bearing capacity, energy dissipation capacity, and ductility. The damage evolution process of the composite columns was analyzed by using the seismic damage assessment model suitable for cyclic loading. The results show that the assembled formwork with greater flexibility is more convenient for fabrication and transport. It is possible to form an integrated stressed member with the composition of the UHPC stay-in-place formwork and post-cast concrete that jointly provides structural resistance. The UHPC stay-in-place formwork can effectively improve the ductility and bearing capacity of the members. Compared with the RC specimen, the ductility coefficient and bearing capacity of the composite columns were improved by 28 ? 84 % and 30 ? 43 %, respectively. The damage assessment model can reflect the damage state of the specimen during loading and is suitable for engineering applications.

» Author: Peng Wang, Jie Huang, Yi Tao, Qingxuan Shi, Chong Rong

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This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement Nº 768737


                   




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