RETRACTED: Research on Fatigue Prediction Model of Asphalt Mixture with High RAP Content

Qingwei Ma, Zhongyin Guo, Ping Guo, Liangyu Sun, Fayong Yang and Haibin Li
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Qingwei Ma: The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, China
Zhongyin Guo: The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, China
Ping Guo: Xi’an Highway Research Institute Co., Ltd., Xi’an 710065, China
Liangyu Sun: Dongmeng Engineering Co., Ltd. of the Second Public Administration of China Communications, Xi’an 710005, China
Fayong Yang: School of Architecture and Civil Engineering, Xi’an University of Science and Technology, Xi’an 710064, China
Haibin Li: School of Architecture and Civil Engineering, Xi’an University of Science and Technology, Xi’an 710064, China

Sustainability, 2021, vol. 13, issue 14, 1-16

Abstract: Asphalt pavement hot recycling technology can improve resource utilization efficiency, reduce energy waste and CO 2 emissions, and bring huge economic and social benefits, further promoting the realization of “carbon peak and carbon neutrality”. This paper uses single logarithmic regression fitting on the fatigue failure life of recycled asphalt mixture with high RAP content to characterize the influence of RAP content (R), stress ratio (C), loading frequency (H) and test temperature (T) on the fatigue life of recycled asphalt mixture. Subsequently, the relationship between fatigue life and stress ratio of recycled asphalt mixture, under the influence of different RAP content, loading frequency and test temperature was analyzed. The results showed that the fatigue life of recycled asphalt mixture decreased with an increase in RAP content, stress ratio and test temperature, and decreased as loading frequency increased. Fatigue life and stress ratio were found to be approximately logarithmic, and based on the relationship between fatigue equation parameters a, b and R, T, H, the fatigue prediction model for recycled asphalt mixtures with independent variables R, C, H, and T was established.

Keywords: asphalt mixture; RAP; fatigue performance; prediction model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:14:p:7995-:d:596194

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