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A Study on the Effects of Punch-to-Span Ratio and Longitudinal Reinforcement Eigenvalues on the Bearing Capacity of RC Slab–Column Connections

Author(s):
ORCID



Medium: journal article
Language(s): English
Published in: Buildings, , n. 1, v. 14
Page(s): 208
DOI: 10.3390/buildings14010208
Abstract:

The region of the RC slab–column connection is subject to complex forces and is susceptible to localized damage, leading to progressive collapse incidents, which has raised considerable concern among the engineering community. At present, the research on slab–column connections exhibits several shortcomings, including a limited number of specimens, incomplete consideration of various factors, and unclear boundaries in defining failure modes. A comprehensive consideration of the punch–span ratio (a/h0) and longitudinal reinforcement eigenvalues (ρƒy/ƒc) is lacking, and the calculation formula for load bearing is not subdivided based on distinct failure modes. In this study, finite element software is utilized to construct 42 models of slab–column connections. The variables considered encompass three factors: the punch–span ratio, the longitudinal reinforcement ratio, and concrete strength. The examination and evaluation encompass the analysis of the load–displacement curve, reinforcement stress change curve, section crack distribution pattern, and stress contour map obtained through model loading. The primary parameters defining the boundaries of the three failure modes in the slab–column connection are the punch–span ratio and longitudinal reinforcement eigenvalues. Utilizing the punch–span ratio and longitudinal reinforcement eigenvalues as key parameters, a punching and flexural failure model for slab–column connections without abdominal bars is formulated. The calculation formula for bearing capacity, encompassing flexural, flexural and punching, and punching shear failure, is derived. A comparison between the revised formula and the standard formulas from major countries indicates that the revised formula is more comprehensive, providing a more accurate and secure prediction within the scope of this study.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10760339
  • Published on:
    23/03/2024
  • Last updated on:
    25/04/2024
 
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