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September 12, 2017 @ 9:00 am - 12:00 pm

AASHTOWare Pavement ME Design is the next generation of pavement design software, which builds upon the NCHRP mechanistic-empirical pavement design guide, and expands and improves the features of the original prototype computational software. Microsoft PowerPoint - TRB 2009 MEPDG Workshop - AASHTOWare Compatibility Mode Author: lpierce Created Date: 1/27/2009 7:37:04 AM.

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VDOT is moving towards implementing a new pavement design method named Mechanistic Empirical Pavement Design Guide (MEPDG) to design interstate and primary routes effective from January 1, 2018. In order to create a general situational awareness and provide some broad understanding, VDOT, in conjunction with VTCA, is offering a session on MEPDG. This session is designed to provide overview/information in regards to the new design procedure for members of industry who are involved in pavement design/analysis as well as the appropriate contracting communities.

Upon completion of the training, participants will be able to:

Be familiar with MEPDG concept and development.
Understand basic difference between MEPDG and AASHTO 93 design procedures.
Be familiar with VDOT MEPDG implementation efforts.
Determine the need for further in-depth, hands-on training on MEPDG software.
Identify the required resource to design pavements using MEPDG procedure (staff, software, and subgrade investigation practice).

This training is intended for consultants, contractors, design-builders, and geotechnical firms who are involved in pavement design/analysis and conducting geotechnical investigation for pavement. In addition, the training will benefit managers who are involved in managing and directing pavement design and geotechnical investigation sections.

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Civil Engineering ETDs

Title

Author

Publication Date

2-8-2011

Abstract

Recently, pavement design has changed from old method based on empirical relation to a new method called Mechanistic Empirical Pavement Design Guide (MEPDG). It is essential to perform a detailed sensitivity analysis of MEPDG outputs to input variables. In particular, MEPDG inputs need to be classified based on their influence on MEPDG outputs for New Mexico pavement conditions. In this study, sensitivity analyses are performed to identify a list of input variables that have significant impacts on the MEPDG outputs considering New Mexico pavement conditions. Sensitivity analyses are performed in two steps. In the first step, a preliminary sensitivity analysis is carried out by varying one input variable at a time while keeping the other inputs constant. The purpose of the preliminary sensitivity analysis is to prepare a short-list of significant input variables out of more than hundreds of variables in MEPDG. In the second step, sensitivity analyses are performed using advanced statistical approaches that consider interactions among the input variables. Parametric procedures such as tests for nonrandomness in scatterplots, linear and nonlinear regression analyses, and nonparametric procedures such as multivariate adaptive regression spline, gradient boosting machine are employed to identify and rank the significant input variables. Results show that predicted pavement performances are sensitive to traffic input variables such as Annual Average Daily Truck Traffic (AADTT) and percent of trucks in design lane. Both asphalt surface layer and total rutting are shown to be the most severe cases among all distresses for New Mexico pavements. Both AC and total rutting are highly sensitive to AADTT, percent of trucks in design lane, and bottom AC layer thickness. Outputs such as terminal IRI, longitudinal cracking, and alligator cracking are highly sensitive to bottom AC layer thickness. MEPDG outputs are also sensitive to HMA mix properties such as thickness, percent air void, binder content and PG grade. Longitudinal and transverse cracking are sensitive to base course material type, modulus and thickness. Depth of water table did not affect the MEPDG outputs at all. Transverse cracking and total rutting are sensitive to subgrade modulus, material properties, and gravimetric water content. MEPDG predicted outputs are found to be moderately sensitive to percent of trucks in design direction, traffic growth factor, and base thickness. Operational speed, depth of ground water table, and design lane width have very little to no effect to MEPDG predicted distresses. Finally, a list of significant variables is made for New Mexico pavement conditions. The list of significant inputs can be useful to pavement engineers to optimize pavement designs and analyze performances as well as for local calibration of MEPDG.

Keywords

MEPDG Sensitivity

Document Type

Thesis

Language

English

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Degree Name

Civil Engineering

Level of Degree

Masters

Department Name

Civil Engineering

First Advisor

Tarefder, Rafiqul A

First Committee Member (Chair)

Storlie, Curtis B

Second Committee Member

Stormont, John C

Recommended Citation

Sumee, Nasrin. 'Sensitivity of MEPDG Using Advanced Statistical Analyses.' (2011). https://digitalrepository.unm.edu/ce_etds/39

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