Validating the empirical distress prediction models within the AASHTOWare Pavement Mechanistic-Empirical Design, using Tennessee pavement performance data from the Long Term Pavement Performance database

The Mechanistic-Empirical Pavement Design Guide (MEPDG) represents a recent pavement design approach, developed to address the shortcomings of the 1993 AASHTO Guide for Design of Pavement Structures. The Pavement Mechanistic-Empirical Design (PMED) software is set to operationalize the mechanistic-empirical principles outlined in MEPDG. However, empirical distress prediction models integrated into PMED were developed and calibrated using national data, necessitating validation and local calibration before implementation on a local scale. Moreover, updates to PMED present possibilities for continuous evaluation to account for improvements in the distress prediction models. This study validates PMED version 2.6.2.2’s prediction models using Tennessee pavement performance data from the Long Term Pavement Performance (LTPP) database, along with previously established local and current global calibration coefficients. Findings from statistical evaluations support the need for local calibration and recalibration of the distress prediction models, in order to suit Tennessee conditions.

Grantor dc:publisher

University of Tennessee at Chattanooga

Author dc:creator

• Otieno, Maxine

Contributors dc:contributor

• Onyango, Mbakisya
• Fomunung, Ignatius; Bathi, Jejal Reddy; Owino, Joseph
• College of Engineering and Computer Science

• Pavements, Concrete--Cracking
• Pavements--Design and construction
• Pavements--Performance--United States--Tennessee

Licence

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language

English, eng

Repository record dc:identifier

https://scholar.utc.edu/theses/872

OAI identifier oai:identifier

oai:scholar.utc.edu:theses-2050