Affiliation:
1. School of Civil Engineering, Northeast Forestry University, Harbin 150040, China
2. School of Highway, Chang’an University, Xi’an 710064, China
3. Key Laboratory for Special Area Highway Engineering of Ministry of Education, Chang’an University, Xi’an 710064, China
Abstract
Elastic pavements, low-freezing point pavements, and energy exchange pavements meet the function of road ice and snow melting but may damage the pavement performance. To solve the above problems, this study intends to develop a noncontact snow-melting pavement by using induction heating technology. The steel wool asphalt mixture was prepared, and the effects of steel wool on road performances including the high-temperature performance, low-temperature performance, water stability, and fatigue performance were studied. The influence of the asphalt mixture’s factors, environmental factors, and human factors on the ice-melting characteristics of steel wool asphalt mixture was analyzed. A prediction model of the ice-melting rate of steel wool asphalt mixture based on a double-hidden layer backpropagation (BP) neural network was established. The results show that the road performance of the asphalt mixture mixed with steel wool mostly meets the requirements of the specification. The increase in steel wool content and length can improve the road performance to a certain extent. In terms of ice-melting performance, the content and length of steel wool have a beneficial effect on the ice-melting rate. The lower the ambient temperature or the thicker the ice layer, the slower the ice-melting rate. The greater the heating intensity, the faster the ice-melting rate. The average absolute error of the melting ice prediction model is 0.016, so the melting ice effect can be well predicted by this model.
Funder
Natural Science Foundation of Heilongjiang Province
Subject
Civil and Structural Engineering
Cited by
2 articles.
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