Technical Papers
Jun 5, 2013

Permanent Deformation Predictive Equations Applicable to Mechanistic-Empirical Flexible Pavement Design

Publication: Journal of Transportation Engineering
Volume 139, Issue 12

Abstract

Flexible pavement design is increasingly utilizing mechanistic-empirical (M-E) based design methods. To date, research has resulted in the development of two primary prediction models for permanent deformation on the basis of two different mechanistic-behavioral theories. An axially based model assumes that deformation is the result of axial compression, whereas a shear-based model assumes shear stresses within the asphalt layer are the primary cause of deformation. Permanent deformation is likely described by a model that incorporates both theories; however, little research exists in this area. The objective of this paper is to investigate numerous permanent deformation predictive models under the hypothesis that a model that combines both mechanistic theories reduces model form error. Improvement in the accuracy of performance predictions will allow designers to investigate novel mix designs, perform accurate reliability analyses, perform precise design optimization, and provide cost-effective designs for both initial construction and maintenance plans. Validation and comparison of numerous models through classical and Bayesian statistical methods will be achieved utilizing empirical data from the National Cooperative Highway Research Program’s (NCHRP) WesTrack project.

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References

Ali, H. A., and Tayabji, S. D. (1998). “Evaluation of mechanistic-empirical performance prediction models for flexible pavements.”, Transportation Research Board, Washington, DC, 169–180.
ARA, ERES Consultants Division. (2004). NCHRP guide for mechanistic-empirical design, National Cooperative Highway Research Program Transportation Research Board National Research Council, Champaign, IL.
ARA, ERES Consultants Division. (2011). “Calibration of rutting models for HMA structural and mix design.”, Champaign, IL.
Azari, H., Mohseni, A., and Gibson, N. (2008). “Verification of rutting predictions from mechanistic-empirical pavement design guide by use of accelerated loading facility data.”, Transportation Research Board, Washington, DC, 157–167.
Clemen, R. T. (1989). “Combining forecasts: A review and annotated bibliography.” Int. J. Forecasting, 5(4), 559–583.
Devore, J. L. (2000). Probability and statistics for engineering and the sciences, Duxbury Thompson Learning, Pacific Grove, CA.
El-Basyouny, M. M., Witczak, M. W., and El-Badawy, S. (2005). “Verification for the calibrated permanent deformation models for the 2002 design guide (with discussion).” J. Assoc. Asphalt Paving Technol., 74(2005), 601–652.
Epps, J. A., et al. (2002). “Recommended performance-related specification for hot-mix asphalt construction: Results of the WesTrack Project.”, Transportation Research Board, Washington, DC, 283–286.
Federal Highway Administration (FHWA). (2009). “Table FA-6A.” Highway Statistics 2009, 〈http://www.fhwa.dot.gov/policyinformation/statistics/2009/fa6a.cfm#foot3〉 (Mar. 17, 2011).
Federal Highway Administration (FHWA). (2012). “Pavement Testing Facility.” 〈http://www.fhwa.dot.gov/pavement/utwweb/facilit.cfm〉 (Feb. 21, 2012).
Forrester, A. I. J., Sobester, A., and Keane, A. (2008). Engineering design via surrogate modelling: A practical guide, Wiley, U.K.
Hoegh, K., Khazanovich, L., and Jense, M. (2010). “Local calibration of mechanistic-empirical pavement design guide rutting model.”, Transportation Research Board, Washington, DC, 130–141.
Jeffreys, H. (1961). Theory of probability, Clarendon Press, Oxford, U.K.
Kaloush, K. E., and Witczak, M. W. (2000). “Development of permanent to elastic strain ratio model for asphalt mixtures.” Inter-Team Rep. for the Development of the 2002 Guide for the Design of New and Rehabilitated Structure, NCHRP, 1–37.
Khattak, M. J., and Baladi, G. Y. (2001). “Fatigue and permanent deformation models for polymer-modified asphalt mixtures.”, Transportation Research Board, Washington, DC, 135–145.
Leahy, R. B. (1989). Permanent deformation characteristics of asphalt concrete, Maryland Univ., College Park, MD.
MATLAB [Computer software]. The MathWorks, Natick, MA.
Minnesota Dept. of Transportation (MnDOT). (2012). “Mn/ROAD Project.” Minnesota Road Research Project, 〈http://www.mrr.dot.state.mn.us/research/MnROAD_Project/mnroadproject.asp〉 (Feb. 21, 2012).
Monismith, C. L., et al. (1994). Permanent deformation response of asphalt aggregate mixes, Transportation Research Board, Washington, DC.
Monismith, C. L., Deacon, J. A., and Harvey, J. T. (2000). “WesTrack: Performance models for permanent deformation and fatigue.” Rep. to Nichols Consulting Engineers, Chtd., Pavement Research Center, Institute of Transportation Studies, Univ. of California, Berkeley, Berkeley, CA.
Muthadi, N. R., and Kim, Y. R. (2008). “Local calibration of mechanistic-empirical pavement design guide for flexible pavement design.”, Transportation Research Board, Washington, DC, 131–141.
Park, I., Amarchinta, H. K., and Grandhi, R. V. (2010). “A Bayesian approach for quantification of model uncertainty.” Reliab. Eng. Syst. Saf., 95(7), 777–785.
Retherford, J. Q., and McDonald, M. (2011). “Estimation and validation of Gaussian process surrogate models for MEPDG-based sensitivity analysis and design optimization.”, Vanderbilt Univ., Nashville, TN.
Timm, D. H., Newcomb, D. E., and Galambos, T. V. (2000). “Incorporation of reliabiliy into mechanistic-empirical pavement design.”, Transportation Research Board, Washington, DC, 73–80.
Washington State Dept. of Transportation (WSDOT). (2011). “9.7 Pavement Evaluation—Flexible Pavement Distress.” 〈http://training.ce.washington.edu/WSDOT/Modules/09_pavement_evaluation/09-7_body.htm#rutting〉 (Mar. 17, 2011).
Witczak, M., Schwartz, C., and von Quintus, H. (2001). “NCHRP Project 9-19: Superpave support and performance models management.” Interim Rep., Federal Highway Administration and the National Cooperative Highway Research Program, Washington, DC.
Zhang, R., and Mahadevan, S. (2000). “Model uncertainty and Bayesian updating in reliability-based inspection.” Struct. Saf., 22(2), 145–160.

Information & Authors

Information

Published In

Go to Journal of Transportation Engineering
Journal of Transportation Engineering
Volume 139Issue 12December 2013
Pages: 1156 - 1163

History

Received: Feb 21, 2012
Accepted: Jun 3, 2013
Published online: Jun 5, 2013
Discussion open until: Nov 5, 2013
Published in print: Dec 1, 2013

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Authors

Affiliations

Jennifer Q. Retherford [email protected]
P.E.
S.M.ASCE
Graduate Student, Dept. of Civil and Environmental Engineering, Vanderbilt Univ., VU Station B 351831, Nashville, TN 37235 (corresponding author). E-mail: [email protected]
Mark McDonald [email protected]
M.ASCE
Assistant Professor, Dept. of Civil Engineering, Lipscomb Univ., One University Park Dr., Nashville, TN 37204. E-mail: [email protected]

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