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Calculation Model for Steel Fibre Reinforced Concrete Punching Zones of Bridge Superstructure and Foundation Slabs
Author(s) -
Gediminas Marčiukaitis,
Remigijus Šalna,
Bronius Jonaitis,
Juozas Valivonis
Publication year - 2011
Publication title -
the baltic journal of road and bridge engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.259
H-Index - 21
eISSN - 1822-4288
pISSN - 1822-427X
DOI - 10.3846/bjrbe.2011.25
Subject(s) - structural engineering , punching , reinforcement , materials science , fiber reinforced concrete , shear strength (soil) , reinforced concrete , finite element method , composite material , engineering , geology , soil science , soil water
The usage of steel fiber reinforced concrete in monolithic joins is well known as a good alternative of additional reinforcement because of chaotic distribution of steel fibers in complex stress and strain state. Unfortunately, the analysis of well known design codes and different models even in punching case without steel fibers shows that there is no common theory in calculating punching shear strength. Existing models of punching shear strength with steel fibers are mainly based on empirical coefficients, or require direct tests, what makes the design of such structures more complicated. Besides, the analysis of elastic and plastic characteristics of steel fiber reinforced concrete is incomplete, because there is no unified, well-grounded theory to evaluate them. The aim of this paper is to present a steel fiber reinforced concrete punching shear strength model. Suggested steel fibers reinforced concrete punching shear strength model estimates the main factors, such as concrete strength, longitudinal reinforcement, steel fibers volume, type, geometric and anchoring characteristics, and also plastic strains of steel fiber reinforced concrete. The comparison of suggested model with tests results demonstrates good accuracy of the suggested model for steel fiber reinforced concrete slabs (mean value – 1.12, standard deviation – 0.08 coefficient of variation – 7%).

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