Rate dependent moment-curvature relations for the progressive collapse analysis of rc structures


Abstract eng:
This contribution deals with the modeling of reinforced concrete structures in the context of progressive collapse simulations. Depending on the initial triggering event, the progressive collapse phenomenon may involve high strain rates in structural members. Since the behaviour of concrete is sensitive to the strain rate, a numerical representation of the strain rate effects on the material behaviour is needed. A Perzyna viscoplastic model is adopted to couple strain rate effects to the plastic response for both concrete and steel, leading to an increase in the flow properties with respect to the strain rate. The rate dependence in the elastic domain is also accounted for. The parameters of the constitutive laws for concrete and steel have been chosen in such a way that the dynamic increase factors (DIF) -i.e. the ratio of dynamic to static strength- obtained with the proposed constitutive models are in good agreement with the experimental results available in the literature. The introduction of these one-dimensional constitutive laws for concrete and steel in a perfectly-bonded layered beam model provides strain rate dependent relations between the bending moment and the curvature for given RC cross-sections. This multilevel approach is used to compare the structural response of a planar frame subjected to the loss of a vertical load bearing element using rate independent material laws with the one obtained through rate dependent ones.

Contributors:
Publisher:
National Technical University of Athens, 2009
Conference Title:
Conference Title:
COMPDYN 2009 - 2nd International Thematic Conference
Conference Venue:
Island of Rhodes (GR)
Conference Dates:
2009-06-22 / 2009-06-24
Rights:
Text je chráněný podle autorského zákona č. 121/2000 Sb.



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 Record created 2016-11-14, last modified 2016-11-14


Original version of the author's contribution as presented on CD, section: Progress and challenges in collapse prediction - i (MS).:
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