Abstract
Column removal failure is a common failure type of reinforced concrete (RC) structures subjected to progressive collapse. Thus, it is widely adopted to use the experimental/numerical column removal scenario to assess the progressive collapse capacity of RC structures. However, most of existing studies neglect the uncertainties involved in the structures, e.g., geometric size and material properties, while it may have great influence on the overall behavior of the structure under progressive collapse. In this paper, a probabilistic analysis of RC beam-column sub-assemblage under column removal scenario is performed. An efficient numerical model based on the finite element software OpenSEES is firstly developed for progressive collapse analysis of RC structures. The model adopts fiber beam-column element with co-rotational formulation to simulate the extreme behavior of frame members under column removal scenario, and uses a Min-Max material to apply the material failure criterion. Then the probability density evolution method (PDEM) is employed to conduct the probabilistic failure analysis. Two benchmark column removal tests of RC sub-assemblages are selected as the numerical case study examples. The deterministic analysis results indicates that the proposed finite element model is effective to reproduce the typical behavior of the sub-assemblages, while the probabilistic analysis provides mean values, standard variations and probability density functions (PDFs) of the whole progressive collapse process. Finally, the influence (or sensitivity) of the uncertain parameters on the global and local behaviors of RC beam-column sub-assemblage under column removal are quantified.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.