On a volume averaged measure of macroscopic reinforcement slip in two‐scale modeling of reinforced concrete. (21st December 2019)

• Record Type: Journal Article
• Authors: Sciegaj, Adam; Larsson, Fredrik; Lundgren, Karin; Runesson, Kenneth
• Is Part Of: International journal for numerical methods in engineering. Volume 121:Number 8(2020)
• Page Start: 1822
• Page End: 1846
• Publication Date: 2019-12-21
• Subjects: bond slip -- computational homogenisation -- cracking -- Lagrange multipliers -- multiscale -- reinforced concrete; Numerical analysis -- Periodicals; Engineering mathematics -- Periodicals; 620.001518
• DOI: 10.1002/nme.6288
• Languages: English
• ISSNs: 0029-5981

Abstract

SUMMARY: A two‐scale model for reinforced concrete, in which the large‐scale problem formulation is enriched by an effective reinforcement slip variable, is derived from the single‐scale model describing the response of plain concrete, reinforcement steel, and the bond between them. The subscale problem on the representative volume element (RVE) is correspondingly defined as finding the response of the RVE subjected to effective variables (strain, slip, and slip gradient) imposed from the large scale. A novel volumetric definition of effective reinforcement slip and its gradient is devised, and the corresponding subscale problem is formulated. The newly defined effective variables are imposed on the RVE in a weak sense using Lagrange multipliers. The response of the RVEs of different sizes was investigated by means of pull‐through tests, and the novel boundary condition type was used in FE 2 analyses of a deep beam. Locally, prescribing the macroscopic reinforcement slip and its gradient in the proposed manner resulted in reduced RVE‐size dependency of effective work conjugates, which allows for more objective description of reinforcement slip in two‐scale modeling of reinforced concrete. Globally, this formulation produced more consistent amplitudes of effective slip fluctuations and more consistent maximum crack width predictions.