Accuracy of Pavement ME Methodology in Predicting Strain Responses under Multiple Axle Loadings in Flexible Pavements

The mechanistic-empirical pavement design method (Pavement ME) uses linear-elastic analysis to calculate the strain responses induced by single and multiple axle loadings, and the method relies on the concept of equivalent or predominant loading frequency to determine the representative elastic modulus of the asphalt concrete (AC) layer. An investigation of the characteristics of multiple axle loading frequencies and the accuracy of predicting critical strains under both single and multiple axle loadings using the same frequency (e.g., Pavement ME) is presented. This paper compares the Pavement ME frequency with several other loading frequencies derived from single, tandem, and tridem axle loading scenarios in 12 cases with combinations of different AC layer thicknesses, moduli, and temperatures, as well as different vehicle speeds. The validity of these frequencies was determined by comparing the strain responses simulated by linear-elastic analysis using each of the frequencies with the results obtained from full dynamic viscoelastic analysis. The study showed that a lower loading frequency needs to be used for multiple axle configurations especially for AC layers with low to moderate stiffness if one wants to achieve a high accuracy of vertical stain prediction; the accuracy of maximum horizontal strains predicted by all loading frequencies is acceptable and is independent of axle configurations or frequency methods in general.

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Publication Details

Journal
Journal of Transportation Engineering Part B Pavements
Published
2024-12-04
DOI
https://doi.org/10.1061/jpeodx.pveng-1632
Primary Topic
Asphalt Pavement Performance Evaluation
Type
article
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article

Accuracy of Pavement ME Methodology in Predicting Strain Responses under Multiple Axle Loadings in Flexible Pavements

Bora Çetin, Karim Chatti, Peng Chen
Journal of Transportation Engineering Part B Pavements
Asphalt Pavement Performance Evaluation
article

Accuracy of Pavement ME Methodology in Predicting Strain Responses under Multiple Axle Loadings in Flexible Pavements

Bora Çetin, Karim Chatti, Peng Chen
article en

Abstract

The mechanistic-empirical pavement design method (Pavement ME) uses linear-elastic analysis to calculate the strain responses induced by single and multiple axle loadings, and the method relies on the concept of equivalent or predominant loading frequency to determine the representative elastic modulus of the asphalt concrete (AC) layer. An investigation of the characteristics of multiple axle loading frequencies and the accuracy of predicting critical strains under both single and multiple axle loadings using the same frequency (e.g., Pavement ME) is presented. This paper compares the Pavement ME frequency with several other loading frequencies derived from single, tandem, and tridem axle loading scenarios in 12 cases with combinations of different AC layer thicknesses, moduli, and temperatures, as well as different vehicle speeds. The validity of these frequencies was determined by comparing the strain responses simulated by linear-elastic analysis using each of the frequencies with the results obtained from full dynamic viscoelastic analysis. The study showed that a lower loading frequency needs to be used for multiple axle configurations especially for AC layers with low to moderate stiffness if one wants to achieve a high accuracy of vertical stain prediction; the accuracy of maximum horizontal strains predicted by all loading frequencies is acceptable and is independent of axle configurations or frequency methods in general.

Journal of Transportation Engineering Part B PavementsVol. 151(1)
Michigan State University (US)
Climate action
Openalex Percentile: Top 75%
Asphalt Pavement Performance Evaluation
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Accuracy of Pavement ME Methodology in Predicting Strain Responses under Multiple Axle Loadings in Flexible Pavements — Bora Çetin, Karim Chatti, et al. · Journal of Transportation Engineering Part B Pavements (2024) | TGRS Research Map | TGRS