Dynamic Performance of Multi-Column Removal Framed Structures Subjected to Impact and Heaped Loads

Abstract

The dynamic performance of a multi-column removal frame (MCRF) suffering from accidental impacts and uniform superstructure loads has largely been neglected in previous studies. To this end, a one-fifth scaled test model was set up to study the MCRF failure state and collapse mechanism. A numerical model was established and validated according to the collapse experiment. Parametric studies were conducted to investigate the effect of the impact height, heaped load (static uniform pressure on the slab), and frame storey on the MCRF dynamic response. The results indicated that: (i) the tension membrane, compressive arch and catenary effect were the main anti-collapse mechanisms in MCRF structures; (ii) according to the peak impact force under the increased collapse impact height (1.5 ∼ 2.5 m), a stronger local response and a slightly enhanced dynamic performance were successively presented on the hammer–concrete interaction; (iii) when the heaped load was increased, the structural plastic deformation capacity provided by the catenary action was better than that given by the compressive arch effect; (iv) the transient impact interaction was almost independent of the frame storey, but the MCRF anti-collapse performance was greatly affected by it. Finally, a collapse prediction method was given to evaluate the ultimate anti-collapse capacity of MCRF structures.

Keywords:

• dynamic performance
• multi-column removal
• reinforced concrete structure
• experimental study
• numerical simulation
• collapse prediction method

Disclosure Statement

No potential conflict of interest was reported by the authors.

Data Availability Statement

The data supporting the results of this study are available from the corresponding author upon request.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [Grant Number 51874118]; the Fundamental Research Funds for the Central Universities [Grant Number 2018B667X14]; the Postgraduate Research & Practice Innovation Program of Jiangsu Province [Grant Number KYCX18_0567].