Evaluation of high temperature performance of asphalt mastic sealing layer for hydraulic engineering

The ramp flow behavior of hydraulic asphalt mastic at high temperatures is critical to its stability and waterproofing performance in hydraulic structures . However, existing test methods lack quantitative indicators, making accurate high-temperature performance assessment challenging. This study aims to predict the high-temperature performance of hydraulic asphalt mastic based on established asphalt performance indicators. Various hydraulic and modified asphalts were tested for high-temperature properties, including the creep recovery rates ( R 0.1 , R 3.2 ), non-recoverable creep compliance ( Jnr 0.1 , Jnr 3.2 ), high-temperature Superpave Performance Grading (PG), complex modulus (G*), phase angel (δ), the rutting factor (G*/sinδ), zero shear viscosity (ZSV), and Brookfield viscosity at 135°C and 175°C. A Monte Carlo simulation combined with Grey Relational Analysis was proposed to examine the correlation between these parameters and the slope flow temperature (SFT) and root mean square (RMS) of surface changes derived from 3D modeling. Results indicate that asphalt type and filler content are key factors influencing the high-temperature performance of asphalt mastic. Brookfield viscosity and high-temperature PG show strong correlations with slope flow resistance, with correlation coefficients close to 0.8. In particular, Brookfield viscosity at 135 °C achieved an average predictive accuracy of 0.82 for both SFT and RMS, demonstrating its effectiveness in evaluating slope flow behavior. ZSV exhibits stable prediction performance and the experimental principle has clear similarities with slope flow, further supporting its use as a reliable high temperature indicator . • A refined slope flow test with 3D modeling improves deformation assessment. • Brookfield viscosity at 135°C and PG grade strongly correlate with flow resistance. • Zero-shear viscosity (ZSV) reliably predicts high-temperature flow behavior. • Monte Carlo and Grey Relational Analysis establish quantitative correlations.