Numerical investigation on progressive collapse resistance of steel-concrete composite floor systems

Abstract

Steel-concrete composite floor systems are commonly used in steel buildings. Stability under gravity and lateral loading depends on these systems. To better understand the design parameters that govern the progressive collapse behaviour of steel-concrete composite floor systems, high-resolution finite-element analyses (FEA) is conducted. Steel fracture and concrete damage are explicitly considered in the finite-element model (FEM). The model is validated using full-scale test data including comparison of the measured response and failure modes. The validated model is used to conduct a parametric study to investigate untested parameters including (i) concrete strength, (ii) horizontal constraint, (iii) steel deck thickness, (iv) reinforcement ratio in the composite slab, and (v) the number of the shear studs. The simulation results are used to determine the optimum design to increase progressive collapse resistance. Specifically, it is found that increasing the continuity and the horizontal constraint of the steel deck, the steel deck thickness, and number of shear studs increase this resistance. Considering the steel consumption and the common practice in the construction, improving the continuity and the horizontal constraint of the steel deck are the best choices to improve the collapse resistance.

Keywords:

• Composite slabs
• disproportionate collapse
• finite element method
• floor systems
• progressive collapse
• membrane action

Acknowledgements

Any opinions, findings, conclusions, and recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the sponsors.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The research presented in this paper was sponsored by the State Key Laboratory of Disaster Reduction in Civil Engineering (Tongji University) through Grant Nos. SLDRCE19-A-03 and Natural Science Foundation of China (NSFC) through Grant No. 51378380.