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The online version of the Mechanistic-Empirical Pavement Design Guide (ME-PDG) is available to anyone with Internet access who has an interest in evaluating the guide and software. The pavement design guide is provided in an Adobe PDF format that is read-only, non-save, non-printable, and non-editable. The software can be downloaded for installation on a local drive in executable form, but its copy-protection feature requires access to the Internet to check for a specific file on the Transportation Research Board web server at each use. Certain supporting technical reports from Project 1-37A are available online in an unrestricted PDF format. This version will expire when the guide and software are available from AASHTO or at another time determined by NCHRP. NCHRP may revise this version as necessary and provide updates on the Internet.
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The spreadsheet program, a manual of practice, and a readme file can be downloaded at following links: -22_AMPT_QA_Program.zip; -22_AMPT_QA_SoftwareManualOfPractice.pdf; and -22_ReadMe-AMPT_QA_Program.docx
This software is offered as is, without warranty or promise of support of any kind either expressed or implied. Under no circumstance will the National Academy of Sciences or the Transportation Research Board (collectively "TRB") be liable for any loss or damage caused by the installation or operation of this product. TRB makes no representation or warranty of any kind, expressed or implied, in fact or in law, including without limitation, the warranty of merchantability or the warranty of fitness for a particular purpose, and shall not in any case be liable for any consequential or special damages.
Integrating the National Database of Subgrade Soil-Water Characteristic Curves and Soil Index Properties With the MEPDG Project DataFunds: $85,000Research Agency:Arizona State UniversityPrincipal Investigator:Claudia ZapataEffective Date:8/27/2010Completion Date:8/31/2012OBJECTIVE The objective of this research was to integrate an enhanced version of the GIS-enabled national database of soil index properties and soil-water characteristic curves developed in Project 9-23A with the MEPDG software.The project final report is available for download at -23B_FR.pdf. Appendixes A-D are available on request to NCHRP.
With the release of the new Mechanistic-Empirical Pavement Design Guide (MEPDG) in the USA, there is a big shift in pavement analysis and design and many state highway agencies are undertaking initiatives to implement the MEPDG. The Iowa Department of Transportation (DOT) is one such highway agency in the USA interested in implementing the MEPDG. In order to effectively and efficiently transition to the MEPDG from the current empirical approach and accelerate its adoption, the Iowa DOT needs a detailed implementation and training strategy. In support of the MEPDG implementation initiatives, sensitivity studies were conducted using the MEPDG software to identify design inputs pertaining to flexible pavements that are of particular sensitivity in Iowa. Based on a study of the MEPDG design components, the results of sensitivity analyses and past experience, this paper, which is the second of the two companion papers, presents key initiatives for implementing the MEPDG in Iowa. The need for implementing the MEPDG at Iowa DOT and the results of rigid pavement input parameter sensitivity analysis are discussed in detail in the first paper.
Although the MEPDG was nationally calibrated using representative pavement test sites across North America, the application of the models to the full range of construction methods, materials, pavement preservation and maintenance practices, and climatic conditions is likely to significantly affect distress and performance. These local effects should be addressed through local calibration studies to adjust, if necessary, the calibration coefficients of transfer functions in the ME Design software.
If local calibration is warranted, it is important that it addresses both the potential bias and precision of each transfer function in the Pavement ME Design software. Figure 1 illustrates how the bias and precision terms can be improved during the local calibration process. In practical terms, bias is the difference between the 50% reliability predicted distress and the measured distress. Precision dictates how far the predicted values at a specified design reliability level would be from the corresponding predicted values at the 50% reliability prediction. The locally calibrated models are then validated using an independent set of data. The models are considered successfully validated to local conditions if the bias and precision statistics of the models are similar to those obtained from model calibration when applied to a new dataset.
While the AASHTO calibration guide details a step-by-step procedure for conducting local calibration, researchers have found that the actual procedures utilized vary from agency to agency. This is partially due to the timing of the publication relative to the initiation of such efforts and the release of new versions of the software. This presents challenges for state agencies, as local calibration is a cumbersome and intensive process and the software and embedded distress models are evolving faster than local calibrations can be completed.
It is recommended that the statistical analyses outlined in the Guide for the Local Calibration of the MEPDG be utilized, as they enable a quantitative assessment of the calibration results. Specifically, such parameters help to determine if local calibration has reduced bias and improved precision and if implementation is warranted. This will also help identifying any weaknesses that may exist in the model that must be considered during the design process. The MEPDG and the AASHTOWare® Pavement ME software have the potential to improve pavement design. Local calibration and validation of the performance models are essential to the implementation of this design framework, however it is an ongoing effort as models continue to be refined, and unconventional materials utilized. 2b1af7f3a8