Fractional Viscoelastic Models for Asphalt Concrete: From Parameter Identification to Pavement Mechanics Analysis
Publication: Journal of Engineering Mechanics
Volume 148, Issue 8
Abstract
The fractional viscoelastic model has been applied to characterize the viscoelasticity of asphalt concrete (AC), but it rarely is adopted in pavement structure analysis due to the complicated calculating process. Therefore, simple methods of applying the fractional viscoelastic models in the pavement mechanic analysis are proposed. First, based on the derived complex modulus expressions of the typical fractional viscoelastic model of AC, combined with the particle swarm optimization and interior-point algorithm, a novel global optimization algorithm for the parameter identification of fractional viscoelastic models is proposed. Then, based on the dynamic modulus and phase angle data obtained in laboratory experiments, the viscoelastic parameters of AC were identified, and the performance of different viscoelastic models was evaluated. Subsequently, based on the Grünwald–Letnikov definition of the fractional operator and the Newton–Raphson integration scheme, the numerical implementation algorithm of some typical fractional viscoelastic models of AC in finite element analysis is proposed, followed by compiled user material subroutines (UMATs). Finally, the thermoviscoelastic analysis of an asphalt pavement structure under impact load was conducted, and the mechanical response laws revealed by different viscoelastic models were investigated. The results showed that the fractional viscoelastic model could yield a more accurate prediction of the viscoelasticity of AC in a wider frequency domain compared with the integer-order viscoelastic model. Moreover, due to the ability to simulate the mechanic behavior of the pavement structure in all temperature ranges with fewer parameters, the modified fractional Zener model is recommended for pavement mechanics analysis.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
This work is supported by the National Key R&D Program of China (2018YFB1600100). The work is also supported by the National Natural Science Foundation of China (U20A20315, 51878228, and 52008139), the China Postdoctoral Science Foundation (2020M670915), the Heilongjiang Provincial Postdoctoral Science Foundation (LBH-Z19222), the Open Research Fund of State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures (KF2020-01), and the Fundamental Research Funds for the Central Universities. Special appreciation is given to Ph.D. Candidate Jie Zhou for his generous assistance in conducting the experiment.
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Journal of Engineering Mechanics
Volume 148 • Issue 8 • August 2022
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© 2022 American Society of Civil Engineers.
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Received: Nov 2, 2021
Accepted: Feb 27, 2022
Published online: May 18, 2022
Published in print: Aug 1, 2022
Discussion open until: Oct 18, 2022
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