Using the mechanistic-empirical pavement design guide for material selection

Authors

  • Armando Orobio University of Valle
  • John P. Zaniewski West Virginia University Morgantown

DOI:

https://doi.org/10.17533/udea.redin.13122

Keywords:

pavement design, sensitivity analysis, MEPDG, M-E PDG, pavement materials

Abstract

The general design approach in the Mechanistic-Empirical pavement Design Guide (MEPDG) is to compare the performance of several trail structures over the design period against previously defined performance criteria to choice the best alternative after life cycle and constructability analyses. The material properties are selected from laboratory testing, correlation or typical values depending on the hierarchical levels deÆ ned by the designers. Layers in a flexible pavement structure are built with different materials and different asphalt mix types. The MEPDG predicted performance of pavement structures varies with variations of the material properties and material properties combination in the different layers. The effect on pavement performance from variations of material properties in the different layers of a pavement structure is analyzed in this study using MEPDG. The study showed that results from sensitivity studies of MEPDG to material properties can be used in selection of pavement materials for better performance.

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Author Biographies

Armando Orobio, University of Valle

School of Civil Engineering and Geomatics.

John P. Zaniewski, West Virginia University Morgantown

Department of Civil and Environmental Engineering.

References

ARA, Inc. ERES Consultants Division. Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures. Final Report, NCHRP Project 1-37A. Transportation Research Board of the National Academies, Washington, DC. 2004. Available in www.trb.org/mepdg/guide.htm.

A. Orobio. Sensitivity Analysis of Flexible Pavement Performance Parameters in the Mechanistic Empirical Design Guide. Dissertation. West Virginia University. Morgantown. USA. 2010. pp.194.

A. Orobio, J. Zaniewski. “Sampling-Based Sensitivity Analysis of the Mechanistic-Empirical Pavement Design Guide Applied to Material Inputs”. Journal of the Transportation Research Board, No 2226. 2011. pp. 85-93. DOI: https://doi.org/10.3141/2226-09

K. Hall, S. Beam. “Estimating the sensitivity of design input variables for rigid pavement analysis with a mechanistic - Empirical design guide”. Journal of the Transportation Research Board. Vol. 1919. 2005. pp. 65-73. DOI: https://doi.org/10.1177/0361198105191900108

S. Haider, R. Harichandran. “Effect of Axle Load Spectrum Characteristics on Flexible Pavement Performance”. Journal of the Transportation Research Board, No 2095. 2009. pp. 101-114. DOI: https://doi.org/10.3141/2095-11

J. Li, L. Pierce, M. Hallenbeck, J. Uhlmeyer. “Sensitivity of Axle Load Spectra in the Mechanistic Empirical Pavement Design Guide for Washington State”. Journal of the Transportation Research Board, No 2093. 2009. pp. 50-56. DOI: https://doi.org/10.3141/2093-06

A. Papagiannakis, M. Bracher, J. Li, N. Jackson. “Sensitivity of NCHRP 1-37A Pavement Design to Traffc Input”. Journal of the Transportation Research Board, No 1945. 2006. pp. 49-55. DOI: https://doi.org/10.1177/0361198106194500107

D. Timm, J. Bower, R. Turochy. “Effect of Load Spectra on Mechanistic-Empirical Flexible Pavement Design”. Journal of the Transportation Research Board, No 1947. 2006; pp. 146-154. DOI: https://doi.org/10.1177/0361198106194700114

A. Guclu, H. Ceylan, K. Gopalakrishnan, S. Kim. “Sensitivity Analysis of Rigid Pavement Systems Using the Mechanistic-Empirical Design Guide Software”. ASCE Journal of Transportation Engineering. Vol 135. 2009. pp. 555-562. DOI: https://doi.org/10.1061/(ASCE)TE.1943-5436.0000036

Ws. Haider, B. Neeraj, C. Karim. Simplified approach for quantifying effect of significant input variables and designing rigid pavements using M-E PDG. CDROM. Transportation Research Board of the National Academies. Washington, DC. 2009. pp. 25.

V. Kannekanti, J. Harvey. Sensitivity analysis of 2002 design guide distress prediction models for jointed plain concrete pavement. Journal of the Transportation Research Board, No 1947. 2006. pp. 91-100. DOI: https://doi.org/10.1177/0361198106194700109

S. Kim, H. Ceylan, K. Gopalakrishna. “Effect of M-E design guide inputs on flexible pavement performance predictions”. Road Materials and Pavement Design. Vol 8. 2007. pp. 375-397. DOI: https://doi.org/10.1080/14680629.2007.9690080

R. Graves, K. Mahboub. “Pilot study in sampling based sensitivity analysis of NCHRP design guide for flexible pavements”. Journal of the Transportation Research Board, No 1947. 2006. pp. 123-135.

H. Ceylan, B. Coree, K. Gopalakrishnan. Strategic Plan for Implementing Mechanistic-Empirical Pavement Design Guide in Iowa. In Proc. of the TRB 85th Annual Meeting. 22-26 Enero de 2006. Washington DC, USA. pp. 1-23.

Y. Kim, N. Muthadi. Implementation Plan for the New Mechanistic-Empirical Pavement Design Guide. NCDOT Final Report. Raleigh: North Carolina State University. Raleigh (USA). 2006. pp. 623.

S. Haider, N. Buch, K. Chatii. Simplified approach for quantifying effect of significant input variables and designing rigid pavements using M-E PDG. Presented at 88th Annual Meeting Transportation Research Board. Washington, DC. 2009. pp. 25.

J. Sacks, W. Welch, T. Mitchell, H. Wynn. “Design and Analysis of Computer Experiments”. Statistical Science. Vol. 4. 1989. pp. 409-423. DOI: https://doi.org/10.1214/ss/1177012413

R. Graves, K. Mahboub. “Pilot study in Sampling Based sensitivity analysis of NCHRP design guide for flexible pavements”. Journal of the Transportation Research Board. No. 1947. 2006. pp. 123-135. DOI: https://doi.org/10.1177/0361198106194700112

Published

2012-10-03

How to Cite

Orobio, A., & Zaniewski, J. P. (2012). Using the mechanistic-empirical pavement design guide for material selection. Revista Facultad De Ingeniería Universidad De Antioquia, (64), 138–149. https://doi.org/10.17533/udea.redin.13122