Evaluation of the Accuracy of Pavement ME Methodology in Calculating Equivalent Loading Frequency and Its Effect on Strain Response Predictions in Flexible Pavements

The prediction of strain responses under axle loadings is critical for flexible pavement design by the mechanistic-empirical approach. The mechanistic-empirical pavement design (pavement ME) method uses linear-elastic analysis to simulate the strain responses under axle loadings, and it relies on the concept of equivalent loading frequency to determine the elastic modulus of the asphalt concrete (AC) layer from the dynamic modulus master curve. The pavement ME method has a simplified procedure to calculate this frequency. The main goal of this study is to evaluate the accuracy of axle loading frequency calculated by the pavement ME method. This paper first introduces the concepts of predominant and equivalent frequencies, provides a brief explanation of the difference between them, and then proposes three predominant frequency methods for evaluation. The accuracy of the pavement ME method and the other methods of calculating the predominant frequency is evaluated in terms of frequency, modulus, and strain by comparing their results with those from dynamic viscoelastic analysis with moving loads. Results show that the time–frequency relationship for predominant frequency is closer to f=1/(2t) than f=1/t, assuming that the pulse duration t is accurate. Nevertheless, using f=1/t with the approximate pulse duration as calculated by the pavement ME method gives reasonable predictions of the maximum tensile strain. On the other hand, while it gives reasonable predictions of vertical strains with increasing depth, the pavement ME method can underestimate them near the surface by up to 55%. Overall, even though the procedure for pavement ME frequency calculation is highly simplified, its general performance appears to be acceptable.

Language

  • English

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  • Accession Number: 01908559
  • Record Type: Publication
  • Files: TRIS, ASCE
  • Created Date: Feb 20 2024 9:17AM