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The bond behavior between reinforcement and concrete has a significant influence on the load‐bearing behavior and serviceability of the composite material. This paper focuses on the characterization of the bond behavior between fine‐grained concrete and mineral‐impregnated carbon‐fiber reinforcement. In this study, the influence of different bond lengths on local bond behavior was experimentally investigated. To predict the bond stress along the bond length, an analytical bond stress‐slip model was specified, and its model parameters were determined based on the experimental tests using an iterative approximation approach. Based on the defined bond stress‐slip model, a numerical bond model was developed and adjusted for the first time. A three‐dimensional (3D) finite element analysis (FEA) allows the simulation of the local bond stress along the bond length. Finally, the results of the 3D FEA were compared with the results of the experimental investigations to validate the developed numerical model. [ABSTRACT FROM AUTHOR]

This work was dedicated to the simulation of fiber composite structures consisting of carbon fibers and mineral impregnation. The aim of this study was to generate a micromodel that predicts the properties of a mineral-impregnated carbon fiber reinforcement. The numerical characterization was based on the discrete microscopic modeling of the individual phases using a representative volume element. In addition, the stochastic nature of the fiber strength, the anisotropic damage mechanisms of the brittle matrix, and the non-linear bonding behavior between the filaments and the matrix were considered in the material models. The material models were adjusted based on the literature sources and our own experimental investigations. This was followed by the validation of the representative volume element, quantifying the evolution of stiffness and damage under longitudinal tensile loading. The numerical results of material stiffness, as well as the tensile strength of the representative volume element, were compared with the results of the experimental investigations. To verify the robustness of the numerical model, significant model parameters were subjected to a sensitivity analysis. [ABSTRACT FROM AUTHOR]

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