01668812

Component

https://doi.org/10.1177/0361198118768522

Pavement performance prediction after maintenance and rehabilitation is important to pavement management. A two-parameter exponential international roughness index (IRI) regression model for thin hot mix asphalt overlay was developed based on information from the U.S. Long Term Pavement Performance (LTPP) database. The model influence parameters a and ß, which represent the initial IRI as the thin overlay completion and shape factor of IRI deterioration curve, were statistically analyzed. The results suggested that the IRI deterioration trends in high-temperature and low-temperature regions are different. This is because ß was mainly affected by the structural strength and equivalent single axle loads in the high and medium temperature region and mainly affected by the average annual precipitation in low temperature region. In-situ data from LTPP database was used to verify the IRI prediction model, and it was found that the predicted IRI and measured IRI exhibited similar trends.

18-00933

English

pp 7-13

2018-12

Transportation Research Record: Journal of the Transportation Research Board

Digital/other

Figures (5) ; Maps; References (18) ; Tables (10)

Bituminous overlays; Databases; Flexible pavements; Hot mix asphalt; Mathematical models; Pavement performance

International Roughness Index; Long-Term Pavement Performance Program

Performance prediction; Thin overlays

Highways; Maintenance and Preservation; Materials; Pavements

TRIS, TRB, ATRI

Dec 22 2017 10:34AM

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