ABSTRACT

Using high contents of the RAP material in newly produced asphalt mixtures leads to a reduction in the crack resistance of the mixtures. This shortcoming can be compensated using some methods such as polymer modification, rejuvenation, fibre-reinforcement, etc. In this paper, the effect of Cyclogen as a rejuvenator and glass fibre was investigated on the cracking behaviour of recycled asphalt mixtures. For this aim, the fracture energy and critical value of J integral (Jc)of semi-circular bending (SCB) asphalt specimens in terms of RAP content, Fibre content and testing temperature were investigated in this study and the results were used to develop an experimental model to predict the crack resistance of asphalt mixtures in terms of temperature and fibre and RAP content using the artificial neural network (ANN) and the multiple regression methods. The results indicated that the fracture energy and Jc valueof asphalt mixtures declined by increasing the RAP contentat intermediate temperatures. However, the reduction in fracture energy and Jc valuecould be compensated using the fibres. Both investigated models were appropriate for predicting the cracking behaviour of fibre-reinforced recycled asphalt mixtures. Nevertheless, the level of correlation was much higher for the ANN approach than the multiple regression model.

摘要

在新生产的沥青混合物中使用高含量的 RAP 材料会导致混合物的抗裂性降低。这一缺点可以通过聚合物改性、再生、纤维增强等方法加以弥补。本文研究了Cyclogen作为再生剂和玻璃纤维对再生沥青混合料开裂行为的影响。为此，本研究研究了半圆弯曲 (SCB) 沥青试样在 RAP 含量、纤维含量和测试温度方面的断裂能和 J 积分 (Jc) 临界值，并将结果用于开发一种使用人工神经网络 (ANN) 和多元回归方法预测沥青混合料在温度、纤维和 RAP 含量方面的抗裂性的实验模型。结果表明，中温下随着RAP含量的增加，沥青混合料的断裂能和Jc值下降。然而，断裂能和 Jc 值的降低可以使用纤维进行补偿。两种研究模型都适用于预测纤维增强再生沥青混合物的开裂行为。然而，ANN 方法的相关性水平远高于多元回归模型。