Optimization of Asphalt-Mortar-Aging-Resistance-Modifier Dosage Based on Second-Generation Non-Inferior Sorting...

Steel slag powder has been proposed as a filler substitute in asphalt mortar to enhance concrete performance and promote steel slag utilization. However, the aging resistance of steel-slag powder-modified asphalt remains a challenge. Prior research has shown that steel slag can improve mechanical properties, but its long-term durability under thermal and UV exposure is unclear. It was already known that antioxidants and UV absorbers could mitigate oxidation and UV damage. This gap motivated the investigation of modifier dosages to improve aging resistance. That uncertainty drove the need for an optimization method to balance multiple performance indicators. No prior work had resolved how to optimally combine antioxidants and UV absorbers for asphalt mortar. This study aimed to address these limitations through a novel algorithmic approach.

The aim was to optimize the dosage of modifiers in steel-slag powder-asphalt mortar to improve its resistance to thermal-oxidation and UV aging. The specific problem addressed was the lack of an efficient method to balance multiple performance parameters. The motivation stemmed from the need to enhance asphalt durability while using industrial byproducts. The study focused on finding the optimal modifier combination that maximizes aging resistance. The researchers proposed using a second-generation non-inferior sorting genetic algorithm to achieve this. The problem required evaluating both thermal and UV aging effects simultaneously. The study also aimed to assess the impact of modifiers on heavy-metal leaching risk. This approach was selected to ensure both performance and environmental safety.

The study used a second-generation non-inferior sorting genetic algorithm (NSGA-II) to optimize modifier dosages. Steel-slag powder was substituted for traditional fillers in asphalt mortar. Antioxidants and UV absorbers were introduced as modifiers. Fourier-Transform Infrared Spectroscopy was used to identify functional groups. A dynamic shear rheometer evaluated rheological properties. A heavy-metal-ion-leaching test assessed toxicity risks. The algorithm was applied to determine optimal dosages of two modifiers, x₁ and x₂. The method combined computational optimization with experimental validation. The approach allowed for multi-objective optimization of aging resistance and leaching risk.

The results showed a significant correlation between modifier dosage and G*, δ, and softening point. The first peak for G* occurred at x₁ = 2.15% and x₂ = 0.25%. For δ, the peak was at x₁ = 1.0% and x₂ = 0.76%. The softening point peak was at x₁ = 1.1% and x₂ = 0.38%. The NSGA-II algorithm yielded optimal dosages of x₁ = 1.2% and x₂ = 0.5%. The asphalt provided a physical seal against heavy-metal ion release. UV and oxygen exposure altered the asphalt structure. Inferior coating performance increased leaching risk.

The NSGA-II algorithm successfully optimized modifier dosages for improved aging resistance. The optimal x₁ dosage was 1.2% and x₂ was 0.5%. The study demonstrated that antioxidants and UV absorbers could enhance thermal-oxidation and UV resistance. The asphalt structure changed under UV and oxygen exposure. Heavy-metal leaching risk increased with poor coating performance. The results suggest that modifier selection and dosage are critical for durability. The findings may guide future applications of steel-slag powder in asphalt. The approach may be adapted for other material optimization problems.