Download or read book Calibrating the Mechanistic empirical Pavement Design Guide for Kansas written by Xiaohui Sun (Writer on roads) and published by . This book was released on 2015 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Local Calibration of the Mechanistic Empirical Pavement Design Guide for Kansas written by Abu Ahmed Sufian and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Guide for the Local Calibration of the Mechanistic empirical Pavement Design Guide written by and published by AASHTO. This book was released on 2010 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Local Calibration of Mechanistic Empirical Pavement Design Guide for North Eastern United States written by Shariq A. Momin and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Mechanistic empirical Pavement Design Guide written by American Association of State Highway and Transportation Officials and published by AASHTO. This book was released on 2008 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Enhancement and Local Calibration of Mechanistic empirical Pavement Design Guide written by Hongren Gong and published by . This book was released on 2018 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Mechanistic-Empirical Pavement Design Guide (MEPDG) represents the state-of-art procedure for pavement design. However, after more than a decade since its publication, the number of agencies that have reported entirely adopting this design system is small. Among the many causes of this phenomenon, the poor predictive accuracy of the performance prediction models is considered the most crucial one. To improve the accuracy of performance predicted by the MEPDG, a preliminary calibration was first conducted for these models with data from the pavement management system (PMS) of Tennessee, and then employed various machine learning algorithms for further improvements. Also, an approach for estimating the modulus of existing asphalt pavement was proposed to enhance the reliability of rehabilitation analysis with the MEPDG. The transfer functions for alligator cracking and longitudinal cracking were validated and calibrated with data collected from the PMS of the state of Tennessee. The results of calibration efforts showed that after calibration, both the bias and variance of the prediction were significantly reduced. It was noted that although local calibration helped improve the accuracy of the transfer functions, the extent of improvement is limited. An observation of the performance models revealed that they were either inadequately formulated or too inflexible to capture sufficient information from the inputs. To further improve the predictive performance of the transfer functions in the MEPDG, several machine learning algorithms were employed including the gradient boosted model (GBM) for fatigue cracking, deep neural networks for rutting, and random forest for IRI. Using the determination of coefficient (R2) and root mean squared error (RMSE) as the measure of model performance, compared with the global transfer functions, the models developed achieved significantly better predictive performance. The results from the regularized regression model indicated that, compared with the model using deflection basins parameters (DBPs), the one without DBPs could still generate modulus prediction of reasonable accuracy. Rehabilitation analyses in the MEPDG with the estimated modulus also contributed to the improved accuracy in pavement performance prediction.
Download or read book Mechanistic empirical Pavement Design Guide Calibration for Pavement Rehabilitation written by R. Christopher Williams and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Calibration of the Mechanistic empirical Pavement Design Guide for Local Paved Roads in Wyoming written by Taylor J. Kasperick and published by . This book was released on 2013 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Mechanistic-Empirical Pavement Design Guide (MEPDG) was released in 2004 under NCHRP Project 1-37A. Since that time, considerable efforts to calibrate the program and its performance prediction models for local conditions have taken place in multiple states attempting to implement the program. Currently, Wyoming DOT is in the process of implementing the DARWIN-ME (the MEPDG in its most current form) on the interstate and the state highway systems. In order to compliment that effort, this study attempted to develop a set of calibration coefficients and localized traffic inputs that can be used on local paved roads. Wyoming is an energy rich state and has seen an increase in the amount of heavy truck traffic that its roadways encounter, thus requiring locally calibrated inputs for the DARWIN-ME. Predicted distresses using the DARWIN-ME were largely different from measured distresses on local paved roadways included in this study, particularly IRI, rutting, alligator cracking, transverse cracking, and longitudinal cracking. These distresses were measured on the local paved roads using Pathway Services Inc. and the surface imaging that it provided. Inputs for trial runs using the DARWIN-ME were determined through work with local county road maintenance superintendents, WYDOT, and previous research regarding climatic data in Wyoming. Localized traffic inputs were developed using Weigh-In Motion (WIM) data collected on non-interstate roadways across Wyoming. Once a significant error and bias were found between predicted and measured distresses, calibration coefficients for IRI, alligator cracking, rutting, and longitudinal cracking were altered to reduce bias and sum of squared errors. The final calibration coefficients settled on in this study reduced the sum of squared errors and bias significantly. A sensitivity analysis was also performed during this study to determine the effect of layer thicknesses on the prediction capabilities of the DARWIN-ME. The process followed in this study can be utilized by other local governments around the country to help them implement the DARWIN-ME.
Download or read book Calibrating Mechanistic Empirical Design Guide Permanent Deformation Models Based on Accelerated Pavement Testing written by Feng Hong and published by . This book was released on 2009 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the challenges to the implementation of the mechanistic-empirical pavement design guide (MEPDG) comes from calibrating the transfer functions. This paper focuses on calibration of one of the major distress models in flexible pavement: permanent deformation or rutting. Two key aspects are critical to a successful rutting model calibration: data and method. Regarding the data, existing in-field information only provides total rut depth, which could not meet the requirement of permanent deformation in each structural layer by the MEPDG. Concerning the method, existing work either fails to address calibration factors from a holistic perspective by only focusing on individual sections separately or ignores variability inherent in those factors. In this study, layer-wise permanent deformation from instrumented pavement under accelerated pavement testing serves to accommodate the models calibration. A systematic calibration procedure is established, which globally optimizes all available information across all test sections. Through simulation and numerical optimization, optimal calibration shift factors for three typical flexible pavement materials, asphalt mixture, unbound granular base, and finegrain soil are obtained as 0.60, 0.49, and 0.84, respectively. This implies that the uncalibrated MEPDG is biased toward overprediction of rut depth. It is further suggested that a more rational result for each calibrated factor is to introduce an appropriate distribution to characterize its uncaptured variability. In addition, a case study involving using calibrated MEPDG to predict pavement performance or life indicates that (1) model calibration has a significant impact on the prediction and (2) the "fourth power law" is supported by the MEPDG.
Download or read book Development of a Master Plan for Calibration and Implementation of the Mechanistic Empirical Pavement Design Guide written by Kevin Dale Hall and published by . This book was released on 2015 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Implementation of the Mechanistic empirical Pavement Design Guide in Utah written by Michael I. Darter and published by . This book was released on 2009 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Highway agencies across the nation are moving towards implementation of the new AASHTO Mechanistic- Empirical Pavement Design Guide (MEPDG) for pavement design. The objective of this project was to implement the MEPDG into the daily operations of the Utah Department of Transportation (UDOT). The implementation of the MEPDG as a UDOT standard required modifications in some UDOT pavement design protocols (i.e., lab testing procedures, equipment, and protocols, traffic data reporting, software issues, design output interpretation, and others). A key requirement is validation of the MEPDG's nationally calibrated pavement distress and smoothness prediction models when applied under Utah conditions and performing local calibration if needed. This was accomplished using data from Long Term Pavement Performance (LTPP) projects located in Utah and UDOT pavement management system (PMS) pavement sections. The nationally calibrated MEPDG models were evaluated. With the exception of the new hot-mix asphalt (HMA) pavement total rutting model, all other models were found to be reasonable. The rutting model was locally calibrated to increase goodness of fit and remove significant bias. Due to the nature of the data used in model validation, it is recommended that further MEPDG model validation be accomplished in the future using a database that contains HMA pavement and jointed plain concrete pavement (JPCP) exhibiting moderate to severe deterioration. This report represents Phase II of the UDOT MEPDG implementation study and builds on the Phase I study report completed in 2005 for UDOT. The Draft User's Guide for UDOT Mechanistic-Empirical Pavement Design (UDOT Research Report No. UT-09.11a, dated October 2009) incorporates the findings of this report as inputs and pavement design guidelines for Utah for use by UDOT's pavement design engineers during trial implementation of the MEPDG"--Technical report documentation p.
Download or read book Calibration of the Flexible Pavement Distress Prediction Models in the Mechanistic Empirical Pavement Design Guide MEPDG for North Carolina written by Fadi Munir Jadoun and published by . This book was released on 2011 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Sensor Installation for the Local Calibration of the Mechanistic Empirical Pavement Design Guide in New Hampshire written by Matthew L. Steele and published by . This book was released on 2010 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Implementation of the AASHTO Mechanistic Empirical Design Guide AASHTOWare Pavement ME Design for Pavement Rehabilitation written by Shuvo Islam and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The AASHTOWare Pavement ME Design (PMED) is a novel design method for new and rehabilitated pavement designs based on mechanistic-empirical design principles. The design process includes several empirical models calibrated with pavement performance data from pavement sections throughout the United States. Improved accuracy of the design process requires that the models be calibrated to local conditions. Therefore, the objective of this study was to implement the AASHTOWare PMED software for rehabilitated pavement design by performing local calibration for state-managed roads in Kansas, New Jersey, and Maine. Transfer functions for translating mechanistic pavement responses into visible distresses embedded in the AASHTOWare PMED software were locally calibrated to eliminate bias and reduce the standard error for rehabilitated pavements in Kansas and New York. Calibration was performed using version 2.5 and then verified with version 2.6.2.2, which was released in September 2022. Rehabilitated pavement sections included asphalt concrete (AC) over AC in Kansas and the New England region and jointed plain concrete pavement (JPCP) sections in Kansas. Because the PMED software requires periodic recalibration of the prediction models to account for improvements in the models, changes in agency design and construction strategies, and updates in performance data, this study also developed an automated technique for calibrating the AASHTOWare PMED software performance models. This automated methodology incorporated robust sampling techniques to verify calibrated PMED models. In addition, statistical equivalence testing was incorporated to ensure PMED-predicted performance results tended to agree with the in-situ data. A comparison of results for the AASHTOWare PMED versions 2.5 and 2.6.2.2 showed that most predicted distress values in Kansas remained the same, except for the predicted AC total fatigue cracking, specifically asphalt bottom-up fatigue cracking. For both distress types, slightly higher values were obtained with version 2.6.2.2. Results of three candidate crack tests showed that IDEAL-CT test results can be used as cracking-resistance criterion for mixtures in Kansas. The rehabilitation models were also successfully calibrated for the New England region.
Download or read book Calibration and Validation of the Enhanced Integrated Climatic Model for Pavement Design written by C. E. Zapata and published by Transportation Research Board. This book was released on 2008 with total page 73 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This report summarizes the results of research to evaluate, calibrate, and validate the Enhanced Integrated Climatic Model (EICM) incorporated in the original Version 0.7 (July 2004 release) of the Mechanistic-Empirical Pavement Design Guide (MEPDG) software with measured materials data from the Long-Term Pavement Performance Seasonal Monitoring Program (LTPP SMP) pavement sections. The report further describes subsequent changes made to the EICM to improve its prediction of moisture equilibrium for granular bases. The report will be of particular interest to pavement design engineers in state highway agencies and industry ..."--Foreword.
Download or read book Guide for the Local Calibration of the Mechanistic empirical Pavement Desing Guide written by and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
