Date of Award
Winter 2010
Project Type
Thesis
Program or Major
Civil Engineering
Degree Name
Master of Science
First Advisor
Jo Daniel
Abstract
Efficient and accurate pavement design is critical to control the costs of new roadway construction and maintenance. The Mechanistic-Empirical Pavement Design Guide (MEPDG) is the most current pavement design procedure used to predict pavement damage and distress. It was calibrated using a national data set that includes data from instrumented pavement sections. The national calibration can be further refined to account for local conditions.
In this research a weather monitoring station and a set of pavement and base layer monitoring sensors were installed and baseline data from these sensors were collected. The measured structural response data from calibrated truck passes were compared to predicted structural response data calculated by comparable pavement analysis programs. It was found that bias and variation exists between the measured and predicted stresses and strains, which is expected to create bias and variation in the distress predictions. Local calibration has the potential to mitigate these effects.
Recommended Citation
Steele, Matthew L., "Sensor installation for the local calibration of the Mechanistic Empirical Pavement Design Guide in New Hampshire" (2010). Master's Theses and Capstones. 614.
https://scholars.unh.edu/thesis/614