（沈阳建筑大学土木工程学院， 沈阳 110168）

［摘要］为改善再生混凝土由于骨料自身缺陷产生的性能不稳定，通过掺入废弃聚丙烯纤维的方式探讨其对再生混凝土碳化深度的影响，同时将分形理论引入到废弃纤维再生混凝土孔隙结构的评价体系中，为定性或定量评定废弃纤维再生混凝土孔结构的复杂性及孔结构与宏观性能的关系开辟新的思路。通过快速碳化试验，以再生骨料掺入量、废弃纤维掺入量、水灰比等为影响因素，结合分形理论对废弃纤维再生混凝土的碳化深度进行研究。结果表明：水灰比、再生骨料掺入量的减小及纤维掺入量的增大均会减小碳化深度；废弃纤维再生混凝土孔隙体积分形维数越小，碳化深度越大。利用孔隙体积分形维数与碳化深度的关系，建立了废弃纤维再生混凝土碳化深度预测模型，模型预测结果与试验值吻合良好。

［关键词］废弃纤维再生混凝土； 碳化深度； 预测模型； 分形维数

中图分类号：TU375．1文献标识码：A文章编号：1002-848X(2019)13-0137-05

Carbonation depth model of waste fiber recycled concrete based on fractal theory

Wang Jianchao, Zhang Xiaofang, Zhou Jinghai, Mei Changzhou, Wang Xindong

(School of Civil Engineering, Shenyang Jianzhu University, Shenyang 110168, China)

Abstract:In order to improve the performance instability of recycled concrete due to the defects of aggregate itself, the influence of waste polypropylene fibers on the carbonation depth of recycled concrete was discussed by adding waste polypropylene fibers. At the same time, fractal theory was introduced into the evaluation system of pore structure of recycled concrete with waste fibers to qualitatively or quantitatively evaluate the pore structure complexity and pore structure of recycled concrete with waste fibers. Through rapid carbonization test, taking the amount of recycled aggregate, waste fiber and water cement ratio as influencing factors, fractal theory was used to study the depth of carbonization performance of recycled concrete with waste fiber. The results show that the carbonization depth decreases with the decrease of water cement ratio, recycled aggregate content and the increase of fiber content, and the smaller the fractal dimension of pore volume of waste fiber recycled concrete, the larger the carbonization depth. Based on the relationship between fractal dimension of pore volume and carbonation depth, a prediction model of carbonation depth of recycled waste fiber concrete was established. The predicted results of the model were in good agreement with the experimental values.

Keywords:waste fiber recycled concrete; carbonation depth; forecasting model; fractal dimension