Seismic behavior of concrete-filled wide rectangular steel tubular (CFWRST) stub columns

The concrete-filled wide rectangular steel tube (CFWRST) columns, with the aspect ratio of cross-section greater than 2.0, have attracted much attention in practice. Existing studies on the concrete-filled rectangular steel tube (CFRST) members have shown that the aspect ratio of cross-section is a main parameter controlling their be-haviors under various loads, which means that the behaviors of CFWRST columns may be different from the common CFST members (the aspect ratio of cross-section not greater than 2.0) considered in existing studies. The behaviors of CFWRST columns under the combined constant axial compression and cyclic lateral loadings were investigated in this paper. Six full-scale columns were tested, with which the failure modes, hysteresis curve, skeleton curve, ductility, lateral stiffness and energy dissipation capacity of the specimens were analyzed and discussed in detail. For all tested specimens, the ductility indexes are between 2.028 and 3.433, and the equivalent damping ratios usually exceed 0.3 at the last of loading cycle. The finite element model was also developed and validated using the test results, and the parametric analyses were carried out with the influences of main parameters discussed. Furthermore, comparisons between the predictions of the solution of EC4 for CFST beam-columns and test results show that the solution of EC4 can provide safe predictions for the CFWRST col-umns under constant axial compression and cyclic lateral loading.

Automated summary

This paper investigates the behavior of concrete-filled wide rectangular steel tube columns with an aspect ratio of cross-section greater than 2.0 under combined constant axial compression and cyclic lateral loadings. The failure modes, hysteresis curve, skeleton curve, ductility, lateral stiffness, and energy dissipation capacity of the specimens were analyzed and discussed. The study concludes that the solution of EC4 can provide safe predictions for these columns.