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Fiber-reinforced concrete significantly enhances the structural and nonstructural properties of traditional concrete by incorporating fibers like steel, glass, and polymers. These fibers, varying from natural ones such as sisal and cellulose to manufactured ones like polypropylene and Kevlar, are mixed into hydraulic cement with aggregates. Steel fibers, often preferred for their robustness, contribute to improved ductility, toughness, and post-cracking performance. The concrete is classified...
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Simulating Fiber-Reinforced Concrete Mechanical Performance Using CT-Based Fiber Orientation Data.

Vladimir Buljak1, Tyler Oesch2, Giovanni Bruno3,4

  • 1Faculty of Mechanical Engineering, University of Belgrade, Kraljice Marije 16, 11120 Belgrade 35, Serbia. vladimir.buljak@polimi.it.

Materials (Basel, Switzerland)
|March 3, 2019
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Summary

This study enhances fiber-reinforced concrete (FRC) modeling by using X-ray computed tomography (CT) to map local fiber orientations. This approach accurately predicts mechanical performance, improving structural simulations.

Keywords:
Fiber-reinforced concreteX-ray computed tomography (CT)anisotropic fiber orientationinverse analysis

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Area of Science:

  • Materials Science
  • Civil Engineering
  • Computational Mechanics

Background:

  • Realistic modeling of fiber-reinforced concrete (FRC) is hindered by local material property variations.
  • Existing constitutive models struggle to incorporate these localized variations for reliable structural-level simulations.
  • Accurate prediction of FRC mechanical behavior is crucial for structural integrity and design.

Purpose of the Study:

  • To develop a novel method for accurately simulating the mechanical performance of FRC components.
  • To address the challenge of localized material property variations in FRC through advanced pre-processing.
  • To validate the proposed modeling approach using experimental data.

Main Methods:

  • Utilized X-ray computed tomography (CT) to measure pre-test fiber orientations in a notched FRC beam.
  • Developed a numerical model incorporating an orthotropic damage model with element-specific coordinate systems aligned to local fiber orientations.
  • Employed inverse analysis with experimental load-displacement data to determine constitutive damage model parameters.

Main Results:

  • The CT-based numerical model accurately predicted the mechanical behavior of FRC under progressive damage.
  • Ultimate strength was predicted with an error of approximately 6%.
  • Work-of-load was predicted within a 4% error margin, demonstrating high fidelity.

Conclusions:

  • The proposed method effectively resolves the issue of localized material variation in FRC modeling.
  • This CT-based approach offers a reliable way to predict the mechanical performance of FRC components.
  • The findings highlight the potential for improved structural-level simulations of FRC materials.