Performance Check of Asphalt Mixture Layer Based on Yield Criterion and Normalized Fatigue Equation
Publication: Journal of Materials in Civil Engineering
Volume 34, Issue 5
Abstract
The fatigue resistance of an asphalt mixture is crucial to the pavement’s durability and serviceability of pavement. The pavement structure is in a three-dimensional (3D) stress state. However, the conventional fatigue-resistance design index mostly considers a one-dimensional stress state, which is different from the field conditions. In this paper, the unconfined compression test (UCT), direct tension test (DTT), and splitting test (SPT) were selected to conduct the strength and fatigue tests. Based on the Ayyagari Vural yield criterion, the strength damage surface under various loading rates was established. Furthermore, a normalized fatigue equation was developed in a 3D stress state by determining the fatigue-damaged path based on the yield criterion. Finally, the fatigue-resistance models for the structural design were proposed by combining the strength models (including the octahedral shear stress model and the Ayyagari Vural model) and the normalized fatigue equation. The results indicate that the strength damage surface model is in an elliptic form, and the surface is abducent as the loading rates increase, and the Ayyagari Vural yield criterion can describe the fatigue failure process. Both fatigue-resistance design methods for pavement resistance take the interaction among three principal stresses into consideration and comply with the failure characteristics of actual pavement structures; the equivalent stress as a design index is more feasible in its actual application. This study could provide a reference for the fatigue-resistance design of asphalt mixture layers in a complex stress state and improve the reliability in the pavement structure.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available from the corresponding author by request.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (No. 52078063), the Postgraduate Scientific Research Innovation Project of Hunan Province (No. CX20200822), the Science and Technology Project of Jiangxi Provincial Department of Transportation (No. 2021C0007), the Science and Technology Innovation Project of Shanghai Chengtou (Group) Co., Ltd. (Nos. CTKY-ZDXM-2020-010 and CTKY-PTRC-2018-003), and the Project of Shenzhen Municipal Engineering Corporation (No. 2020zkhx387).
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Received: Jun 2, 2021
Accepted: Sep 16, 2021
Published online: Feb 24, 2022
Published in print: May 1, 2022
Discussion open until: Jul 24, 2022
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