Abstract
SMC (Styreneic Methyl Copolymers) is a novel normal temperature asphalt modifier with superior performance. It has the advantages of a low construction temperature, good road performance, good energy savings and an emission reduction effect, and can improve the performance of an asphalt mixture. The fatigue performance of an asphalt mixture is one of the important technical parameters in the structural design of asphalt pavements. The fatigue performance of an asphalt mixture under specific traffic and environmental conditions has an important guiding significance and normative function for the design, construction, and maintenance of asphalt pavement. In this paper, the mixture of an SMC normal-temperature-modified asphalt and styrene–butadiene styrene block copolymer (SBS)-modified asphalt (SMCSBS) compound-modified asphalt was investigated, and an SMCSBS composite modified asphalt mixture with a different SMC content was prepared. A semi-circular bending fatigue test (SCB) was conducted to analyze and compare the fatigue properties of the modified asphalt mixture. On this basis, this paper proposes a fatigue life prediction model of an SMCSBS composite modified asphalt mixture based on a particle swarm optimization support vector machine (PSO-SVM). SMC content (SMC accounts for the mass percentage of SMCSBS composite modified asphalt)/%, asphalt aggregate ratio, stress ratio and loading frequency/Hz were used as training data to establish the prediction model, and RMSE and R2 were used to evaluate the performance of the model. Experimental results show that the prediction results of the PSO-SVM method are more accurate than the experimental observation data and can effectively improve the prediction accuracy of the model. Compared with the M5′ model tree (M5′), artificial neural network (ANN), and support vector machine (SVM) method, the PSO-SVM method can achieve better prediction performance and a better prediction effect.
Highlights
With increasing traffic volume and heavy load traffic, a large number of reflection cracks appear in a traditional pavement structure under fatigue load, and the service life of a road is greatly shortened [1]
The results show that the effect of Styreneic Methyl Copolymers (SMC) content on fatigue performance is that the fatigue life of the mixture was the largest when the SMC content was 10%
The results show that the effect of 6SoMf 1C4 content on fatigue performance is that the fatigue life of the mixture was the largest when the SMC content was 10%
Summary
With increasing traffic volume and heavy load traffic, a large number of reflection cracks appear in a traditional pavement structure under fatigue load, and the service life of a road is greatly shortened [1]. Fatigue failure is one of the main forms of current asphalt pavement damage. Zhesheng Ge used the grey relational analysis method to study the influence of load interval time, loading frequency, test temperature, void fraction, asphalt penetration, and asphalt content on the fatigue performance of a mixture, and found that the order of influence degree from large to small is as follows: Load interval time, test temperature, asphalt type, gradation type, asphalt content, and loading frequency [9]. Hongzhou Zhu evaluated the influence of asphalt property, aggregate gradation, and mixture volume on fatigue performance by using a grey correlation. The research showed that the mixture saturation, the mixture void fraction, the rubber powder mass ratio, and the asphalt film thickness have a great influence on fatigue performance [10]. The fatigue life of the asphalt mixture specimen decreased after long-term aging [11]
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