Case Studies in Construction Materials (Dec 2023)
Predicting asphalt mixture fatigue life via four-point bending tests based on viscoelastic continuum damage mechanics
Abstract
A more technically accurate approach to predict fatigue life of asphalt mixtures can enhance the precision of performance evaluation for asphalt pavements. This study applied the viscoelastic continuum damage mechanics (VECD) to investigate the fatigue behavior of asphalt mixtures. The fatigue life of typical asphalt mixtures was evaluated through four-point bending tests under various conditions. The strain-modulus empirical equation was firstly employed to fit the experimental data. However, it was noted that this equation was not entirely suitable for all conditions, as factors like temperature and loading frequency can influence fatigue life not only through the dynamic modulus but also via the damage properties of asphalt mixtures. To address this limitation and achieve a comprehensive fatigue life prediction equation, the Time-Strain Superstition Principle (TSSP) and Frequency-Strain Superstition Principle (FSSP) were introduced to characterize the impact of temperature and loading frequency on fatigue life, which can reduce fitting errors. Additionally, a mechanical prediction equation was also derived by the VECD approach, and its applicability under different conditions was explored. The results revealed that the damage characteristic curve (C-S curve) remained unaffected by loading frequency and strain level but was highly dependent on temperature. Significant fitting errors were observed in different temperatures when employing the VECD method for fatigue life prediction, as the VECD method did not account for the influence of temperature on the viscoelastic properties of asphalt mixtures, which in fact plays a critical role in fatigue life. In response, temperature adjustment coefficients were introduced into the derived equation. The predicted results demonstrated that the newly modified method significantly improved prediction precision, yielding an error of less than 20%.
