Mechanistic-empirical Pavement Design Guide Implementation Plan

Mechanistic-empirical Pavement Design Guide Implementation Plan

Author: Todd E. Hoerner

Publisher:

Published: 2007

Total Pages: 324

ISBN-13:

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As AASH is expected to eventually adopt the MEPDG at its primary pavement design method, it is critical that the SDDOT become familiar with the MEPGD documentation and associated design software. The research conducted under this project was a first step toward achieving this goal.


Guide for the Local Calibration of the Mechanistic-empirical Pavement Design Guide

Guide for the Local Calibration of the Mechanistic-empirical Pavement Design Guide

Author:

Publisher: AASHTO

Published: 2010

Total Pages: 202

ISBN-13: 1560514493

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This guide provides guidance to calibrate the Mechanistic-Empirical Pavement Design Guide (MEPDG) software to local conditions, policies, and materials. It provides the highway community with a state-of-the-practice tool for the design of new and rehabilitated pavement structures, based on mechanistic-empirical (M-E) principles. The design procedure calculates pavement responses (stresses, strains, and deflections) and uses those responses to compute incremental damage over time. The procedure empirically relates the cumulative damage to observed pavement distresses.


Local Calibration of the Mechanistic Empirical Pavement Design Guide for Kansas

Local Calibration of the Mechanistic Empirical Pavement Design Guide for Kansas

Author: Abu Ahmed Sufian

Publisher:

Published: 2016

Total Pages:

ISBN-13:

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The Kansas Department of Transportation is transitioning from adherence to the 1993 American Association of State Highway and Transportation Officials (AASHTO) Pavement Design Guide to implementation of the new AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) for flexible and rigid pavement design. This study was initiated to calibrate MEPDG distress models for Kansas. Twenty-seven newly constructed projects were selected for flexible pavement distress model calibration, 21 of which were used for calibration and six that were selected for validation. In addition, 22 newly constructed jointed plain concrete pavements (JPCPs) were selected to calibrate rigid models; 17 of those projects were selected for calibration and five were selected for validation. AASHTOWare Pavement ME Design (ver. 2.2) software was used for design analysis, and the traditional split sampling method was followed in calibration. MEPDG-predicted distresses of Kansas road segments were compared with those from Pavement Management Information System data. Statistical analysis was performed using the Microsoft Excel statistical toolbox. The rutting and roughness models for flexible pavement were successfully calibrated with reduced bias and accepted null hypothesis. Calibration of the top-down fatigue cracking model was not satisfactory due to variability in measured data, and the bottom-up fatigue cracking model was not calibrated because measured data was unavailable. AASHTOWare software did not predict transverse cracking for any projects with global values. Thus thermal cracking model was not calibrated. The JPCP transverse joint faulting model was calibrated using sensitivity analysis and iterative runs of AASHTOWare to determine optimal coefficients that minimize bias. The IRI model was calibrated using the generalized reduced gradient nonlinear optimization technique in Microsoft Excel Solver. The transverse slab cracking model could not be calibrated due to lack of measured cracking data.


Draft User's Guide for UDOT Mechanistic-empirical Pavement Design

Draft User's Guide for UDOT Mechanistic-empirical Pavement Design

Author: Michael I. Darter

Publisher:

Published: 2009

Total Pages: 136

ISBN-13:

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Validation of the new AASHTO Mechanistic-Empirical Pavement Design Guide's (MEPDG) nationally calibrated pavement distress and smoothness prediction models when applied under Utah conditions, and local calibration of the new hot-mix asphalt (HMA) pavement total rutting model, were recently completed as documented in UDOT Research Report No. UT-09.11 Implementation of the Mechanistic-Empirical Pavement Design Guide in Utah: Validation, Calibration, and Development of the UDOT MEPDG User's Guide, dated October 2009. This Draft User's Guide incorporates the findings of the model validation and local calibration report and provides information for use by UDOT's pavement design engineers during trial implementation of the MEPDG. This information includes an overview of the MEPDG procedure, information on installation of the software, guidelines for obtaining all needed inputs, guidance to perform pavement design using the software for new and rehabilitated HMA pavement and jointed plain concrete pavement (JPCP), and pavement design examples for new HMA pavement and new JPCP using the MEPDG software.


Local Calibration of Mechanistic Empirical Pavement Design Guide for North Eastern United States

Local Calibration of Mechanistic Empirical Pavement Design Guide for North Eastern United States

Author: Shariq A. Momin

Publisher:

Published: 2011

Total Pages:

ISBN-13:

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The Mechanistic-Empirical Pavement Design Guide (MEPDG) developed under the National Cooperative Highway Research Program (NCHRP) 1-37A project is based on mechanistic-empirical analysis of the pavement structure to predict the performance of the pavement under different sets of conditions (traffic, structure and environment). MEPDG takes into account the advanced modeling concepts and pavement performance models in performing the analysis and design of pavement. The mechanistic part of the design concept relies on the application of engineering mechanics to calculate stresses, strains and deformations in the pavement structure induced by the vehicle loads. The empirical part of the concept is based on laboratory developed performance models that are calibrated with the observed distresses in the in-service pavements with known structural properties, traffic loadings, and performances. These models in the MEPDG were calibrated using a national database of pavement performance data (Long Term Pavement Performance, LTPP) and will provide design solution for pavements with a national average performance. In order to improve the performance prediction of the models and the efficiency of the design for a given state, it is necessary to calibrate it to local conditions by taking into consideration locally available materials, traffic information and the environmental conditions. The objective of this study was to calibrate the MEPDG flexible pavement performance models to local conditions of Northeastern region of United States. To achieve this, seventeen pavement sections were selected for the calibration process and the relevant data (structural, traffic, climatic and pavement performance) was obtained from the LTPP database. MEPDG software (Version 1.1) simulation runs were made using the nationally calibrated coefficients and the MEPDG predicted distresses were compared with the LTPP measured distresses (rutting, alligator and longitudinal cracking, thermal cracking and IRI). The predicted distresses showed fair agreement with the measured distresses but still significant differences were found. The difference between the measured and the predicted distresses were minimized through recalibration of the MEPDG distress models. For the permanent deformation models of each layer, a simple linear regression with no intercept was performed and a new set of model coefficients (ßr1, ßGB, and ßSG) for asphalt concrete, granular base and subgrade layer models were calculated. The calibration of alligator (bottom-up fatigue cracking) and longitudinal (topdown fatigue cracking) was done by deriving the appropriate model coefficients (C1, C2, and C4) since the fatigue damage is given in MEDPG software output. Thermal cracking model was not calibrated since the measured transverse cracking data in the LTPP database did not increase with time, as expected to increase with time. The calibration of IRI model was done by computing the model coefficients (C1, C2, C3, and C4) based on other distresses (rutting, total fatigue cracking, and transverse cracking) by performing a simple linear regression.


Preparation for Implementation of the Mechanistic-empirical Pavement Design Guide in Michigan

Preparation for Implementation of the Mechanistic-empirical Pavement Design Guide in Michigan

Author: Syed Waqar Haider

Publisher:

Published: 2014

Total Pages:

ISBN-13:

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The main objective of Part 3 was to locally calibrate and validate the mechanistic-empirical pavement design guide (Pavement-ME) performance models to Michigan conditions. The local calibration of the performance models in the Pavement-ME is a challenging task, especially due to data limitations. A total of 108 and 20 reconstruct flexible and rigid pavement candidate projects, respectively, were selected. Similarly, a total of 33 and 8 rehabilitated pavement projects for flexible and rigid pavements, respectively were selected for the local calibration. The selection process considered pavement type, age, geographical location, and number of condition data collection cycles. The selected set of pavement section met the following data requirements (a) adequate number of sections for each performance model, (b) a wide range of inputs related to traffic, climate, design and material characterization, (c) a reasonable extent and occurrence of observed condition data over time. The national calibrated performance models were evaluated by using the data for the selected pavement sections. The results showed that the global models in the Pavement-ME don't adequately predict pavement performance for Michigan conditions. Therefore, local calibration of the models is essential. The local calibrations for all performance prediction models for flexible and rigid pavements were performed for multiple datasets (reconstruct, rehabilitation and a combination of both) and using robust statistical techniques (e.g. repeated split sampling and bootstrapping). The results of local calibration and validation of various models show that the locally calibrated model significantly improve the performance predictions for Michigan conditions. The local calibration coefficients for all performance models are documented in the report. The report also includes the recommendations on the most appropriate calibration coefficients for each of the performance models in Michigan along with the future guidelines and data needs.


Calibrating the Mechanistic-empirical Pavement Design Guide for Kansas

Calibrating the Mechanistic-empirical Pavement Design Guide for Kansas

Author: Xiaohui Sun (Writer on roads)

Publisher:

Published: 2015

Total Pages: 212

ISBN-13:

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The Kansas Department of Transportation (KDOT) is moving toward the implementation of the new American Association of State Highway and Transportation Officials (AASHTO) Mechanistic-Empirical Pavement Design Guide (MEPDG) for pavement design. The MEPDG provides a rational pavement design framework based on mechanistic-empirical principles to characterize the effects of climate, traffic, and material properties on the pavement performance, as compared with the 1993 AASHTO Guide for Design of Pavement Structures. Before moving to the MEPDG, the nationally calibrated MEPDG distress prediction models need to be further validated and calibrated to the local condition. The objective of this research was to improve the accuracy of the MEPDG to predict the pavement performance in Kansas. This objective was achieved by evaluating the MEPDG-predicted performance of Kansas projects, as compared with the pavement performance data from the pavement management system (PMS), and calibrating the MEPDG models based on the pavement performance data. In this study, 28 flexible pavement projects and 32 rigid pavement projects with different material properties, traffic volumes, and climate conditions were strategically selected throughout Kansas. The AASHTO ME Design software (Version 1.3) was used in this study. The comparisons between the MEPDG-predicted pavement performance using the nationally calibrated models and the measured pavement performance indicated the need for the calibration of the MEPDG models to the Kansas conditions. For new flexible pavements, the MEPDG using the nationally calibrated models overestimated the rutting due to the overprediction of the deformation of the subgrade layer. Biases also existed between the predicted top-down cracking, thermal cracking, and International Roughness Index (IRI) and the measured data. The relationship between the measured and the predicted IRIs was more obvious than that for the cracking. Using the coefficients determined through local calibration in this study, the biases and the standard errors were minimized for all the models based on the statistical analysis. For new rigid pavements, very low mean joint faulting was measured in actual projects as compared with the default threshold of the MEPDG. The type of base course had a minor effect on the pavement performance. The traditional splitting data method was adopted in the process of local calibration. After the local calibration, the biases between the predicted pavement performance (mean joint faulting and IRI) and the measured pavement performance were minimized, and the standard errors were reduced.