Evaluation of climate data sources and investigation of performance prediction models for mechanistic-empirical pavement designs

<p>The Mechanistic-Empirical Pavement Design Guide (MEPDG), a novel procedure for pavement design practice, was developed under National Cooperative Highway Research Program (NCHRP) research study 1-37A. Subsequently, renamed as DarWin-ME in April 2011, and AASHTOWare Pavement ME design (PMED) in February 2013, this tool has been rapidly emerging as the state-of-the-art practice for pavement designs across the United States. Since its release, numerous updates have been made to the software, and some of the most recent enhancements include addition of MERRA climate data (satellite-based data provided through NASA), a reflective-cracking model for overlay performance prediction, a tool to design short jointed plain concrete pavement (SJPCP) over asphalt concrete (AC), and major bugs were resolved to improve computational performance. A comprehensive evaluation of all these new tools was performed and is presented in this study. The results demonstrate the significant impact of distresses predicted by the software compared to predictions using previous versions that warranted the need for re-calibration for state-specific conditions (commonly known as local calibration) using the latest version of the software (version 2.5.5 released in June 2019). Evaluation of nationally-calibrated models is performed for flexible, rigid and asphalt concrete over jointed plain-concrete pavements representing different geographical locations, ages, and traffic levels across the state of Iowa, and locally-calibrated models were developed for Iowa-specific conditions by determining the new set of calibration coefficients for use in PMED software. Multiple advanced optimization approaches were tested for this process and presented in this study, and experiences and recommendations during the entire local calibration process are discussed. Additional analysis is performed to determine the recommended reliability levels by varying layer thicknesses using the locally calibrated models. The overall findings from this study will serve as a useful reference and guide to pavement engineers across the country who plan to test and implement these new tools for their state design practices, along with the complete set of calibration steps required in PMED software version 2.5.5.</p>

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

dissertation

Discipline thesis:degree_discipline

Civil Engineering (Geotechnical Engineering and Civil Engineering Materials)

Department dc:contributor.department

Department of Civil, Construction and Environmental Engineering

Year dc:date.issued

2020

Author dc:creator

• Gopisetti, Leela Sai Praveen

Advisor dc:contributor.advisor

• Halil Ceylan

Language dc:language.iso

en

DOI

https://doi.org/10.31274/etd-20200902-50

Identifier

archive/lib.dr.iastate.edu/etd/18131/

OAI identifier oai:identifier

oai:dr.lib.iastate.edu:20.500.12876/94283