Local Calibration of MEPDG for Flexible Pavements in New Mexico

• Published in: Journal of transportation engineering Vol. 139; no. 10; pp. 981 - 991
• Main Authors: Tarefder, Rafiqul, Rodriguez-Ruiz, Jose I
• Format: Journal Article
• Language: English
• Published: Reston, VA American Society of Civil Engineers 01.10.2013
• Subjects: Applied sciences; Asphalt pavements; Buildings. Public works; Calibration; Computation methods. Tables. Charts; Cracks; Error analysis; Errors; Exact sciences and technology; Highway construction; Mathematical models; Optimization; Pavement design; Pavements; Road construction. Pavements. Maintenance; Roads & highways; Structural analysis. Stresses; Technical Papers; Transportation engineering; Transportation infrastructure; Transportation planning; United States; New Mexico; North America; America; USA, New Mexico; Performance evaluation; Mechanistic-empirical pavement design guide (MEPDG); Coefficient; Deformation; Empirical method; Roughness; Cracking; Permanent strain; Surface roughness; Calibration; Coefficients; Modeling; Recommendation; Flexible pavement; New Mexico; Mechanistic approach; Pavement analysis; Local calibration; Permanent deformation; Longitudinal cracking; Database; Flexible pavements; Local scope; Alligator cracking
• ISSN: 0733-947X; 1943-5436
• DOI: 10.1061/(ASCE)TE.1943-5436.0000576

AbstractLocal calibration of the mechanistic-empirical pavement design guide (MEPDG) is performed by determining the pavement-performance model coefficients to minimize the difference between the measured and predicted distresses of New Mexico department of transportation (NMDOT) pavements. A total of 24 New Mexico pavement sections, which have all the MEPDG inputs and quantitative-distress values required for MEPDG calibration, were used for calibration. Pavement-performance models such as rutting, alligator cracking, longitudinal cracking, and roughness models were calibrated by an error-minimization algorithm. In the calibration methodology, the target was fixed to reduce the sum of squared errors, defined by the square of the difference between predicted and measured distress, so that any bias was eliminated and precision was increased. The optimized calibration coefficients are: βr1=1.1, βr2=1.1, βr3=0.8, βGB=0.8, and βSG=1.2 for the rutting model; C1=0.625, C2=0.25, and C3=6,000 for alligator cracking; C1=3, C2=0.3, and C3=1,000 for longitudinal cracking; and site factor = 0.015 for roughness. The results show that these calibration coefficients reduce error in the MEPDG prediction and assist better design of flexible pavements using MEPDG in New Mexico.