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A probabilistic mechanical model for prediction of aggregates' size distribution effect on concrete compressive strength

Abstract : To predict aggregates' size distribution effect on the concrete compressive strength, a probabilistic mechanical model is proposed. Within this model, a Voronoi tessellation of a set of non-overlapping and rigid spherical aggregates is used to describe the concrete microstructure. Moreover, aggregates' diameters are defined as statistical variables and their size distribution function is identified to the experimental sieve curve. Then, an inter-aggregate failure criterion is proposed to describe the compressive-shear crushing of the hardened cement paste when concrete is subjected to uniaxial compression. Using a homogenization approach based on statistical homogenization and on geometrical simplifications, an analytical formula predicting the concrete compressive strength is obtained. This formula highlights the effects of cement paste strength and aggregates' size distribution and volume fraction on the concrete compressive strength. According to the proposed model, increasing the concrete strength for the same cement paste and the same aggregates' volume fraction is obtained by decreasing both aggregates' maximum size and the percentage of coarse aggregates. Finally, the validity of the model has been discussed through a comparison with experimental results (15 concrete compressive strengths ranging between 46 and 106 MPa) taken from literature and showing a good agreement with the model predictions. (C) 2012 Elsevier B.V. All rights reserved.
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Contributeur : Navier Bibliothèque <>
Soumis le : mardi 15 mai 2012 - 16:26:40
Dernière modification le : mercredi 28 octobre 2020 - 12:12:02

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Karim Miled, Oualid Limam, Karam Sab. A probabilistic mechanical model for prediction of aggregates' size distribution effect on concrete compressive strength. Physica A: Statistical Mechanics and its Applications, Elsevier, 2012, 391 (12), pp.3366-3378. ⟨10.1016/j.physa.20/2.01.051⟩. ⟨hal-00697573⟩

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