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A Numerical Mesoscopic Method for Simulating Mechanical Properties of Fiber Reinforced Concrete

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Computational and Experimental Simulations in Engineering (ICCES 2019)

Part of the book series: Mechanisms and Machine Science ((Mechan. Machine Science,volume 75))

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Abstract

The mechanical properties of steel fiber reinforced concrete are affected by aggregate gradation and content of steel fiber, mortar and aggregate. Appropriate stochastically distributed aggregate model is rather physically correct for numerical simulation of steel fiber reinforced concrete meso-structures. This paper proposes a numerical method to analyze the static mechanical properties of fiber reinforced concrete based on a multiscale perspective. The geometric relationship between penetration and intrusion of polygonal aggregates is investigated, and as consequence an algorithm of the generation of polygonal aggregates is developed. Considering the stochastic distribution of steel fibers and aggregates, a two-dimensional mesoscopic model is presented in a purely geometric context. Damage and failure behavior of steel fiber reinforced concrete specimens under uniaxial tension load is simulated base on the FEM. The finite-element analysis is found to agree well with the experimental data, showing validity of the proposed numerical method for the modeling of static mechanical properties of fiber reinforced concrete. The results provide insight into the mechanical relationship among multiscale structures of multi-phase quasi-brittle material.

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Acknowledgements

This paper is funded by the national natural science foundation of China (NSFC) for “strengthening method of self-repairing UHPC bonded steel bridge deck based on multi-scale optimization and verification” (project approval no. 51778466).

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Correspondence to Wenzhao Wang .

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Zeng, Z., Chen, W., Wang, W. (2020). A Numerical Mesoscopic Method for Simulating Mechanical Properties of Fiber Reinforced Concrete. In: Okada, H., Atluri, S. (eds) Computational and Experimental Simulations in Engineering. ICCES 2019. Mechanisms and Machine Science, vol 75. Springer, Cham. https://doi.org/10.1007/978-3-030-27053-7_68

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  • DOI: https://doi.org/10.1007/978-3-030-27053-7_68

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27052-0

  • Online ISBN: 978-3-030-27053-7

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