Version 1
: Received: 18 April 2017 / Approved: 18 April 2017 / Online: 18 April 2017 (18:28:59 CEST)
Version 2
: Received: 24 August 2017 / Approved: 25 August 2017 / Online: 25 August 2017 (08:01:21 CEST)
Grassl, P. ; Johansson, M.; Leppänen, J. On the Numerical Modelling of Bond for the Failure Analysis of Reinforced Concrete. Engineering Fracture Mechanics2017, doi:10.1016/j.engfracmech.2017.10.008.
Grassl, P. ; Johansson, M.; Leppänen, J. On the Numerical Modelling of Bond for the Failure Analysis of Reinforced Concrete. Engineering Fracture Mechanics 2017, doi:10.1016/j.engfracmech.2017.10.008.
Grassl, P. ; Johansson, M.; Leppänen, J. On the Numerical Modelling of Bond for the Failure Analysis of Reinforced Concrete. Engineering Fracture Mechanics2017, doi:10.1016/j.engfracmech.2017.10.008.
Grassl, P. ; Johansson, M.; Leppänen, J. On the Numerical Modelling of Bond for the Failure Analysis of Reinforced Concrete. Engineering Fracture Mechanics 2017, doi:10.1016/j.engfracmech.2017.10.008.
Abstract
The structural performance of reinforced concrete relies heavily on the bond between reinforcement and concrete. In nonlinear finite element analyses, bond is either modelled by merged, also called perfect bond, or coincident with slip, also called bond-slip, approaches. Here, the performance of these two approaches for the modelling of failure of reinforced concrete was investigated using a damage-plasticity constitutive model in LS-DYNA. Firstly, the influence of element size on the response of tension-stiffening analyses with the two modelling approaches was investigated. Then, the results of the two approaches were compared for plain and fibre reinforced tension stiffening and a drop weight impact test. It was shown that only the coincident with slip approach provided mesh insensitive results. However, both approaches were capable of reproducing the overall response of the experiments in the form of load and displacements satisfactorily for the meshes used.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
