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Coupled Systems Mechanics
  Volume 10, Number 6, December 2021 , pages 509-520
DOI: https://doi.org/10.12989/csm.2021.10.6.509
 

Data driven inverse stochastic models for fiber reinforced concrete
Ivica Kozar, Natalija Bede, Anton Bogdanic and Silvija Mrakovcic

 
Abstract
    Fiber-reinforced concrete (FRC) is a composite material where small fibers made from steel or polypropylene or similar material are embedded into concrete matrix. In a material model each constituent should be adequately described, especially the interface between the matrix and fibers that is determined with the 'bond-slip' law. 'Bond-slip' law describes relation between the force in a fiber and its displacement. Bond-slip relation is usually obtained from tension laboratory experiments where a fiber is pulled out from a matrix (concrete) block. However, theoretically bond-slip relation could be determined from bending experiments since in bending the fibers in FRC get pulled-out from the concrete matrix. We have performed specially designed laboratory experiments of three-point beam bending with an intention of using experimental data for determination of material parameters. In addition, we have formulated simple layered model for description of the behavior of beams in the three-point bending test. It is not possible to use this 'forward' beam model for extraction of material parameters so an inverse model has been devised. This model is a basis for formulation of an inverse model that could be used for parameter extraction from laboratory tests. The key assumption in the developed inverse solution procedure is that some values in the formulation are known and comprised in the experimental data. The procedure includes measured data and its derivative, the formulation is nonlinear and solution is obtained from an iterative procedure. The proposed method is numerically validated in the example at the end of the paper and it is demonstrated that material parameters could be successfully recovered from measured data.
 
Key Words
    experimental data inversed model; FBM; FRC; layered model; three-point beam bending
 
Address
Ivica Kozar, Natalija Bede, Anton Bogdanic and Silvija Mrakovcic: Faculty of Civil Engineering, University of Rijeka, R. Matejcic 3, Rijeka, Croatia
 

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