Analytic investigations of snow melting efficiency and temperature field of thermal conductive asphalt concrete combined with electrical-thermal system. (1st May 2023)

• Record Type: Journal Article
• Authors: Jiao, Wenxiu; Sha, Aimin; Liu, Zhuangzhuang; Jiang, Wei; Hu, Liqun; Qin, Wen
• Is Part Of: Journal of cleaner production. Volume 399(2023)
• Publication Date: 2023-05-01
• Subjects: TCAC -- Electrical-thermal system -- Road performance -- Snow melting efficiency -- Road temperature field -- BP Neural Network; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2023.136622
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Electrical-thermal technique is a promising method for asphalt pavement snow melting with minimal external intervention. To employ this technology in practical engineering applications, plenty researches have focused on the electrical-thermal system configuration and design. In this study, an effective method to improve the efficiency of melting by combination of thermal conductive asphalt concrete (TCAC) and electrical-thermal system was proposed. The TCAC is designed with steel slag as the thermal conductive filler and used in the upper layer of the pavement to improve the heat transfer efficiency of the electrical-thermal system. The thermal conductivity (λ), road performance and electrical-thermal snow melting performance were studied in the laboratory. It is demonstrated that the mean λ of TCAC reaches a peak value when the steel slag (3–5 mm) volume content is 60 %, and it increased by 8.23%. The road performance parameters of TCAC, such as dynamic stability, flexural tensile strength, water stability and expansion ratio, can all meet the specification requirements. The snow melting effect of TCAC is better than that of ordinary asphalt concrete (OAC), and the heating rate and the snow melting efficiency of the thermal conductivity slab are increased by 25–50 % and 25–38 %, respectively. In addition, the test road was constructed based on the laboratory results, the temperature field and surface temperature prediction in the practical engineering are further analyzed. Results show that the temperature distribution of the test road is relatively uniform and the surface temperature is 0.8–1.5 °C higher than that of the ordinary section. The surface temperature of test road can be predicted and evaluated well by the Back Propagation (BP) neural network, 87 % of error is within 1 °C, and the fitting coefficient is 0.9325. Highlights: Utilization of steel slags to replace part of the diabase to produce TCAC, and the optimum steel slags content was recommended. Study the surface temperature and snow melting efficiency of TCAC as the upper layer of the electrical-thermal pavement system. Analysis the pavement temperature field of test road and evaluation of the surface temperature by BP neural network.