基于均匀化预测含初始缺陷钢纤维混凝土弹性模量

柴正一 ,  盛冬发 ,  秦飞飞 ,  霍晓伟

科学技术与工程 ›› 2024, Vol. 24 ›› Issue (7) :2856-2862

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科学技术与工程 ›› 2024, Vol. 24 ›› Issue (7) :2856-2862 DOI: 10.12404/j.issn.1671-1815.2302635
建筑科学

基于均匀化预测含初始缺陷钢纤维混凝土弹性模量

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Prediction of Elastic Modulus of Steel Fiber Concrete with Initial Defects Based on Homogenization

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摘要

为合理设计利用钢纤维混凝土,将掺钢纤维的混凝土看成由砂浆、骨料、界面、初始缺陷、钢纤维以及界面处较大的孔隙率组成的多相复合材料,采用分步均匀化的方法建立预测混凝土混合夹杂模型,将微分法、Mori-Tanaka方法以及Christensen的三相模型相结合求解混合夹杂模型,模型预测结果与试验结果吻合较好。分析结果表明:骨料性质对钢纤维混凝土弹性模量影响显著,钢纤维混凝土整体弹性模量随水灰比,界面过渡区厚度,孔洞体积分数的增加而降低,随骨料体积分数,骨料弹性模量以及界面的弹性模量的增加而增大。

Abstract

In order to rationally design and utilize steel fiber concrete, the concrete mixed with steel fibers was regarded as a multiphase composite material consisting of mortar, aggregate, interface, initial defects, steel fibers, and large porosity at the interface, and a step-by-step homogenization method was used to establish a predictive concrete mixing model to solve the mixing model by combining the differentiation method, the Mori-Tanaka method, and the Christensen's three-phase model. Mixed inclusions model, the model prediction results and the test results were in good agreement. The analysis results show these as follows. The nature of the aggregate has a significant effect on the modulus of elasticity of the steel fiber concrete, the overall modulus of elasticity of the steel fiber concrete with the increase of the water-cement ratio, the thickness of the transition zone of the interface, the volume fraction of the pores and decrease, with the increase in the volume fraction of the aggregate, the modulus of elasticity of the aggregate, as well as the increase of the elasticity modulus of the interface.

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柴正一, 盛冬发, 秦飞飞, 霍晓伟. 基于均匀化预测含初始缺陷钢纤维混凝土弹性模量[J]. 科学技术与工程, 2024, 24(7): 2856-2862 DOI:10.12404/j.issn.1671-1815.2302635
CHAI Zheng-yi, SHENG Dong-fa, QIN Fei-fei, HUO Xiao-wei. Prediction of Elastic Modulus of Steel Fiber Concrete with Initial Defects Based on Homogenization[J]. Science Technology and Engineering, 2024, 24(7): 2856-2862 DOI:10.12404/j.issn.1671-1815.2302635

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基金资助

国家自然科学基金(11862023)

云南省教育厅科学研究基金(2023Y0772)

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