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Inverse Analysis of Concrete Meso-constitutive Model Parameters Considering Aggregate Size Effect
Science and Engineering of Composite Materials ( IF 1.5 ) Pub Date : 2020-11-17 , DOI: 10.1515/secm-2020-0043
Lixia Guo 1, 2, 3, 4 , Song Li 1 , Ling Zhong 1, 2, 3 , Lei Guo 1, 2, 3 , Lunyan Wang 1, 2, 3
Affiliation  

Abstract The meso numerical simulation has become an important method to study the characteristics of materials; however, the key to its further application is determining the parameters of meso-constitutive model. Considering that the meso-scale parameters of materials are hard to measure, this paper took into account the aggregate size effect and proposed a meso-parameter identification method by combining random aggregate numerical simulation and genetic algorithm. First, a random aggregate model of concrete was established, and its meso-model parameters were analyzed. The Morris method was used to analyze the sensitivity of meso-component parameters to the macro-responses, and results showed that the elastic modulus of mortar matrix, interface and large aggregates had a great effect on the peak strain and that the elastic modulus, Poisson’s ratio and tensile strength of interface and mortar matrix, as well as the Poisson’s ratio of large aggregates and the elastic modulus of small aggregates all had an effect on the peak stress, among which the interface tensile strength produced the greatest effect. Second, a parametric inversion and optimization function was established. The uniaxial compression numerical simulation test and genetic algorithm were combined to invert the meso-parameters, and results showed that compared with the single-aggregate parameter inversion curve, the multi-aggregate inversion stress-strain curve was much closer to the measured curve. That was because the aggregates of small size had lower elastic modulus, easing the stress concentration at the interface between aggregates and cement stone, and delaying the formation and growth of cracks.

中文翻译:

考虑骨料尺寸效应的混凝土细观本构模型参数反分析

摘要 细观数值模拟已成为研究材料特性的重要方法;然而,其进一步应用的关键是确定细观本构模型的参数。针对材料细观参数难以测量的问题,考虑骨料尺寸效应,提出了一种随机骨料数值模拟与遗传算法相结合的细观参数识别方法。首先,建立了混凝土的随机骨料模型,并对其细观模型参数进行了分析。采用Morris法分析细观组分参数对宏观响应的敏感性,结果表明砂浆基体、界面和大骨料的弹性模量对峰值应变有很大影响,弹性模量、界面与砂浆基体的泊松比和抗拉强度,以及大骨料的泊松比和小骨料的弹性模量都对峰值应力有影响,其中界面抗拉强度的影响最大。其次,建立了参数反演和优化函数。结合单轴压缩数值模拟试验和遗传算法对细观参数进行反演,结果表明,与单骨料参数反演曲线相比,多骨料反演应力应变曲线更接近实测曲线。这是因为小尺寸的骨料弹性模量较低,缓解了骨料与水泥石界面处的应力集中,延缓了裂缝的形成和扩展。
更新日期:2020-11-17
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