Guide for the Local Calibration of the Mechanistic-empirical Pavement Design Guide PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Guide for the Local Calibration of the Mechanistic-empirical Pavement Design Guide PDF full book. Access full book title Guide for the Local Calibration of the Mechanistic-empirical Pavement Design Guide by . Download full books in PDF and EPUB format.
Author:
Publisher: AASHTO
ISBN: 1560514493
Category : Technology & Engineering
Languages : en
Pages : 202
Get Book Here
Book Description
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.
Author:
Publisher: AASHTO
ISBN: 1560514493
Category : Technology & Engineering
Languages : en
Pages : 202
Get Book Here
Book Description
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.
Author: Hongren Gong
Publisher:
ISBN:
Category : Pavements
Languages : en
Pages : 152
Get Book Here
Book Description
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.
Author: Shariq A. Momin
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
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.
Author: American Association of State Highway and Transportation Officials
Publisher: AASHTO
ISBN: 156051423X
Category : Pavements
Languages : en
Pages : 218
Get Book Here
Book Description
Author: Abu Ahmed Sufian
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
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.
Author: Matthew L. Steele
Publisher:
ISBN:
Category : Pavements
Languages : en
Pages : 248
Get Book Here
Book Description
Author: Syed Waqar Haider
Publisher:
ISBN:
Category : Asphalt emulsion mixtures
Languages : en
Pages :
Get Book Here
Book Description
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.
Author: Taylor J. Kasperick
Publisher:
ISBN: 9781303160103
Category : Pavements
Languages : en
Pages : 190
Get Book Here
Book Description
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.
Author: Xiaohui Sun (Writer on roads)
Publisher:
ISBN:
Category : Pavements
Languages : en
Pages : 212
Get Book Here
Book Description
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.
Author: Michael I. Darter
Publisher:
ISBN:
Category : Pavements
Languages : en
Pages : 218
Get Book Here
Book Description
"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.
