Optimization of induction heating parameters for improving Self-healing performance of asphalt mixture through partial least square model

The self-healing capacity of asphalt mixture based on induction heating, determined by induction heating pa-rameters, has been the key issue regarding asphalt mixture's self-healing. This study tried to investigate how induction heating parameters determine asphalt mixture's self-healing concerning parameters' coupling effect. AC-13 asphalt mixtures consisting of steel fiber and steel slag were prepared for induction heating. Dynamic stability, low-temperature cracking resistance, and moisture stability were studied. Single-parameter (SP) method and multi-parameter (MP) method considering the coupling effect were separately used to achieve the optimum parameter combinations for improving the healing ratio (HR). A functional relationship by the MP method between HR and induction heating parameters was established based on partial least square through Data Processing System software (DPS). Results verified the coupling effect among parameters. Asphalt mixture with 8 % steel fiber content showed optimum pavement performance. The optimum parameter combination of SP method for HR was: 8 % steel fiber content, 5 mm, 180 s, and 16 kW for induction distance, time, and power respectively, and the optimum HR based on SP method was 69 %. The optimum parameter combination of MP method was: 8.8 %, 5 mm, 107 s, and 24 kW, while its predicted HR was 77 % and the actual HR was 75 %. Therefore, the MP method based on partial least square showed a greater improvement of HR than SP method, which proved that coupling effects of induction heating parameters affect asphalt mixture's self-healing capacity.