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A stochastic multiscale model for predicting mechanical properties of fiber reinforced concrete

机译:纤维增强混凝土力学性能的随机多尺度模型

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摘要

A stochastic multiscale computational model for predicting the mechanical properties of fiber reinforced concrete (FRC), subjected to tensile loading, is proposed. It involves the microscale, the mesoscale and the macroscale. On the mesoscale, the heterogeneity of the material is taken into account by a periodic layout of unit cells of matrix-fiber materials, consisting of short fibers and mortar. Material modeling on the microscale is characterized by a periodic layout of unit cells of matrix-aggregate composite materials, consisting of randomly distributed fine aggregate grains and cement matrix. A new unified micromeso-macro homogenization procedure, based on two-scale asymptotic expressions, has been established. It is used for deriving formulae for multiscale analysis of FRC. The numerical results for the elastic modulus of FRC are compared with experimental results. The comparison shows that the proposed stochastic multiscale computational method is useful for determination of this mechanical property. The developed model is also applied to investigating the influence of different fiber materials on the elastic modulus, and Poisson's ratio of FRC. (C) 2014 Elsevier Ltd. All rights reserved.
机译:提出了一种随机多尺度计算模型,用于预测纤维混凝土的拉伸性能。它涉及微观尺度,中尺度尺度和宏观尺度。在中尺度上,基质纤维材料(由短纤维和砂浆组成)的晶胞的周期性排列考虑了材料的异质性。在微观尺度上的材料建模的特征在于基质-骨料复合材料的晶胞的周期性布置,该单元由无规分布的细骨料颗粒和水泥基质组成。建立了一种新的基于微尺度渐近表达式的统一的微观内宏宏均化程序。用于推导FRC多尺度分析的公式。将FRC弹性模量的数值结果与实验结果进行了比较。比较表明,所提出的随机多尺度计算方法对于确定该力学性能是有用的。所开发的模型还用于研究不同纤维材料对FRC的弹性模量和泊松比的影响。 (C)2014 Elsevier Ltd.保留所有权利。

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