Proposing a novel double sigmoidal model to fit the master curve for various polymer-modified asphalt

ABSTRACT

Master curve technique is frequently used to characterize the linear viscoelasticity of polymer modified asphalt (PMA), however, there is no widely accepted master curve for PMA. This study aims to propose a novel double sigmoidal model that can be used universally for all asphalts, especially highly modified PMAs. To do so, one plain asphalt and six representative PMAs are examined. Extended temperature sweep tests (−40°C to 140°C) are conducted to grasp the whole picture of the master curve. Three representative mathematical models (CAM, sigmoidal, double sigmoidal) are selected and compared in terms of fitting in both modulus and phase angle. The results suggest that double sigmoidal model suits all types of asphalts for all testing temperature ranges, and it features the ability to model the rubbery state and rubbery-viscous transition of highly modified PMA (RMSE < 0.02). A phase angle expression of the double sigmoidal model is also developed, which shows great potential in characterizing the strength of polymer network within the PMA. Also, it avoids the impact from the partial break of the time-temperature superposition principle (TTSP) and reveals the true shape of the phase angle master curve. Finally, master curve models are recommended based on different testing temperature ranges.

KEYWORDS:

• PMA
• viscoelastic
• master curve
• double sigmoidal model
• phase angle

Acknowledgements

The authors gratefully acknowledge the financial support by the National Natural Science Foundation of China (52008353, 51908426), China Postdoctoral Science Foundation (BX20190240, 2019M660097), Sichuan Youth Science and Technology Innovation Research Team (2021JDTD0023, 2022JDTD0015), Chengdu Technological Innovation R&D Project (2021-YF05-01175-SN).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by China Postdoctoral Science Foundation: [Grant Number BX20190240, 2019M660097]; National Natural Science Foundation of China: [Grant Number 52008353, 51908426]; Chengdu Technological Innovation R& D Project: [Grant Number 2021-YF05-01175-SN]; Sichuan Youth Science and Technology Innovation Research Team: [Grant Number 2021JDTD0023, 2022JDTD0015].