The Comparison and Selection of a Warm Mix Agent for Asphalt Based on Fuzzy Hierarchical Analysis

Warm mix asphalt pavements can effectively reduce construction energy consumption and control environmental pollution compared to conventional asphalt pavements. However, there is no clear test standard for the evaluation of warm mix agents. The selection of a warm mix agent is easily influenced by subjective factors. Moreover, it is difficult to consider quantitative and qualitative factors such as technical indexes and the economy. A fuzzy hierarchical comprehensive evaluation model of warm mix agents is proposed based on fuzzy hierarchical analysis. Four types of indexes, namely, material properties, technical indexes, economy, and construction difficulty, were selected to construct the hierarchical structure of the target, guideline, and indicator layers. The influence weights of all factors were determined by the judgment matrix, and an affiliation judgment matrix was established at the same time. Finally, the comprehensive score of the warm mix agent modification effect was calculated. Three warm mix agents were selected for market research and indoor testing. And the evaluation model was applied to process the data. The calculation results show that the technical indicators have the greatest influence, with a weight proportion of 0.493; WM-2 had the best comprehensive evaluation, with a comprehensive score of 0.96, and its optimal mixing amount was 0.3%. The calculation results further verified the effectiveness of the fuzzy hierarchical comprehensive evaluation model of warm mix agents. Compared with the existing methods, the fuzzy-hierarchical-integrated evaluation model of warm mix agents has a more comprehensive evaluation scope, lower subjective factor bias, and more flexible application scenarios. It provides a more rigorous and convenient idea for the development and evaluation of different warm mix agents. In conclusion, the model has greater application value and popularization value.

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.