Volume 23 Issue 4
Aug.  2023
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HAN Zhen-qiang, HU Li-qun, SHA Ai-min. Calibration method of asphalt pavement fatigue damage prediction model based on accelerated pavement test[J]. Journal of Traffic and Transportation Engineering, 2023, 23(4): 258-270. doi: 10.19818/j.cnki.1671-1637.2023.04.019
Citation: HAN Zhen-qiang, HU Li-qun, SHA Ai-min. Calibration method of asphalt pavement fatigue damage prediction model based on accelerated pavement test[J]. Journal of Traffic and Transportation Engineering, 2023, 23(4): 258-270. doi: 10.19818/j.cnki.1671-1637.2023.04.019

Calibration method of asphalt pavement fatigue damage prediction model based on accelerated pavement test

doi: 10.19818/j.cnki.1671-1637.2023.04.019
Funds:

National Natural Science Foundation of China 52108393

National Key Research and Development Program of China 2021YFB2601300

Fundamental Research Funds for the Central Universities 300102211307

More Information
  • Author Bio:

    HAN Zhen-qiang(1991-), male, assistant professor, PhD, jasonhan029@126.com

    SHA Ai-min(1964-), male, professor, PhD, ams@chd.edu.cn

  • Received Date: 2023-02-21
    Available Online: 2023-09-08
  • Publish Date: 2023-08-25
  • To improve the reliability of fatigue damage prediction model for asphalt pavements in engineering applications, a calibration method of the model was proposed based on the small-scale-specimen test and full-scale accelerated pavement test (APT). The evolution characteristics of asphalt pavement fatigue damage were analyzed to establish a cumulative fatigue damage analysis method by the nonlinear incremental recursive (NIR) method, which was suitable for the shift and extrapolation of the fatigue damage prediction model from small-scale test to full-scale test. The fatigue damage prediction model for the full-scale asphalt mixture layer was established based on the fatigue life prediction model obtained by small-scale specimen test, and the transfer equation of the fatigue life prediction model was used as the tool to predict the fatigue damage under the full-scale APT condition. In order to determine the model transfer equation, the fatigue damage calibration equation based on the APT was proposed, and the calibration methods of the undetermined coefficients were derived. The APT was carried out by the heavy vehicle simulator on the full-scale asphalt pavement test sections with graded-crushed stone composite base. The fatigue damage prediction model of asphalt mixture layer was calibrated and validated by integrating the dynamic modulus test and the four-points-bending-fatigue test results of the core samples drilled from the APT sections. Research results show that the NIR method can consider the impacts of material nonlinearity, performance decay, and loading history on the fatigue damage accumulation of asphalt pavement structure, conforming to the actual evolution law of the pavement fatigue damage. The calibrated fatigue damage prediction model can be used to predict the cumulative fatigue damages of the asphalt mixture layers of test sections in different loading intervals, and 50% and 90% of the predicted results have an error of less than 3.1% and 20.0% compared to the measured results, respectively, indicating that the calibrated prediction model has certain reliability. Therefore, the proposed model calibration method can be taken as a reference for the establishment of fatigue damage prediction model of asphalt pavement based on the APT and provide more reliable performance prediction models for the decision-making on pavement design and maintenance.

     

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