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Quantitative analysis of the influence of synthetic fibres on plastic shrinkage cracking using digital image correlation

机译:利用数字图像相关技术定量分析合成纤维对塑性收缩开裂的影响

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The plastic shrinkage cracking behaviour of restrained mortar overlays on a concrete substrate was studied with the aim of quantifying the influence of commercially available polypropylene (PP) fibres and recycled polyethylene (R-PE) fibres obtained from discarded fishing nets. The use of R-PE fibres was investigated with a view to creating a more eco-friendly construction material. The plastic shrinkage behaviour was evaluated on the basis of a non-contact 2D digital image correlation (DIC) technique that enables the automated detection of surface displacements and strains with high precision. Based on the DIC data, the degree of surface cracking was quantitatively analysed using a MATLAB post-processing procedure and presented in detailed histograms showing the crack width distribution of the entire specimen surface. Using this data, the effect of fibre reinforcement on crack control was objectively quantified and evaluated. The results indicate that while the addition of 2.0% of R-PE is effective in controlling shrinkage cracking in the mortars, the commercial PP fibres perform better even at volume fractions as low as 0.1%. These findings show that the recycled fibres can be used to reduce plastic shrinkage cracking behaviour compared to unreinforced materials, while a waste material is being reused, though, a much larger volume fraction of R-PE fibres than of commercially available PP fibres is necessary to achieve a similar effect. (C) 2018 Elsevier Ltd. All rights reserved.
机译:为了量化市售聚丙烯(PP)纤维和从废弃渔网中获得的再生聚乙烯(R-PE)纤维的影响,研究了约束砂浆覆盖物在混凝土基材上的塑性收缩开裂行为。研究了R-PE纤维的用途,目的是创造一种更加环保的建筑材料。基于非接触式2D数字图像关联(DIC)技术对塑性收缩行为进行了评估,该技术可实现高精度的表面位移和应变的自动检测。基于DIC数据,使用MATLAB后处理程序对表面开裂的程度进行了定量分析,并以详细的直方图显示了整个样品表面的裂缝宽度分布。利用这些数据,可以客观地量化和评估纤维增强对裂缝控制的影响。结果表明,尽管添加2.0%的R-PE可以有效地控制砂浆中的收缩开裂,但商用PP纤维即使在体积分数低至0.1%时也表现更好。这些发现表明,与未增强材料相比,再生纤维可用于减少塑料收缩开裂的行为,而废料则可以被再利用,尽管如此,R-PE纤维的体积分数要比市售PP纤维大得多。达到类似的效果。 (C)2018 Elsevier Ltd.保留所有权利。

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