Technical Papers
Mar 4, 2014

Comparing Flexible Pavement Performance Using Emerging Analysis Tools

Publication: Journal of Transportation Engineering
Volume 140, Issue 5

Abstract

In recent years, a variety of tools have been developed to assist in the analysis of flexible pavement service life in the United States. Although the output from many of the approaches is similar, each tool varies in the amount of testing effort, materials, and equipment necessary to arrive at the resulting predictions. Building upon the findings from research conducted in the National Cooperative Highway Research Program (NCHRP) Project 9-22B, this study focused on comparing flexible pavement performance predictions using three emerging analysis tools. One of the pavement analysis software packages, which considered the standard of, predicts performance in terms of incremental distresses and damage accumulation during a pavement’s service life. The other two programs are performance-related specification (PRS) tools that predict pavement performance in terms of service life factors. Three different asphalt mixtures were evaluated including a conventional mixture and two unconventional mixtures modified with emerging material technologies. The conventional mixture was used in a full-depth reconstruction project that featured low-level truck traffic. The two unconventional mixtures were placed as overlays on two structures featuring heavy truck traffic and the same substructure. Results from all three programs indicated that rutting predictions were similar among different analysis tools. However, the fatigue cracking predictions showed the greatest differences due to how the different analysis tools model climatic conditions. A comparison of the different analysis tools also suggested that for the mixes evaluated, one of them could be used effectively with Level 2 hot mix asphalt (HMA) inputs, in lieu of requiring the more time-intensive Level 1 HMA inputs, to predict the service life of flexible pavements. By performing a parametric analysis, it was established that this tool was sensitive to traffic variations and changes in structural support in combination with higher traffic. Certain modifications to the volumetric properties of the HMA layers produced significantly different performance predictions using this particular tool. The results of this study showed that the three analysis tools are comparable and produce equivalent performance predictions. Thus, the decision of which analysis tool to use should be based on a transportation agency’s assessment of its testing capabilities, budget level, and project complexity. In addition, the approach developed in this study can be enhanced in the future to form the basis of a decision-making procedure to help direct the amount of effort and funding necessary in the pavement and mixture design phase.

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Acknowledgments

An initial portion of the research presented herein was performed under NCHRP Project 9–22B, sponsored by the Cooperative Research Program of the National Academies, by the Dept. of Civil and Environmental Engineering at Villanova University, and by the Rutgers University Advanced Pavement Laboratory. The Maine and Delaware DOTs actively participated in this project by generously supplying project data, materials, and coordination with paving contractors.

References

AASHTO. (2008). Mechanistic-empirical pavement design guide, Interim edition: A manual of practice, Washington, DC.
Applied Research Associates (ARA). (2004). NCHRP project 1-37A: Guide for mechanistic-empirical design of new and rehabilitated pavement structures, Transportation Research Board of the National Academies, Washington, DC.
Bonaquist, R. (2008). NCHRP Rep. 614: Refining the simple performance tester for use in routine practice, Transportation Research Board of the National Academies, Washington, DC, 153.
Ceylan, H., Schwartz, C., Kim, S., and Gopalakrishnan, K. (2009). “Accuracy of predictive models for dynamic modulus of hot-mix asphalt.” J. Mater. Civ. Eng., 286–293.
El-Badawy, S., Awed, A., and Bayomy, F. (2011). “Evaluation of the MEPDG dynamic modulus prediction models for asphalt concrete mixtures.” Proc., Transportation and Development Institute Congress, ASCE, Reston, VA, 576–585.
Jeong, M. G. (2010a). “AMPT QA program.” 〈http://onlinepubs.trb.org/onlinepubs/nchrp/docs/NCHRP09-22_AMPT_QA_Program.zip〉 (Jun. 12, 2012).
Jeong, M. G. (2010b). “Implementation of a simple performance test procedure in a hot mix asphalt quality.” Ph.D. dissertation, Arizona State Univ.
Jeong, M. G. (2010c). Manual of practice HMA quality assurance spreadsheet program using measured values of E* and d. 〈http://onlinepubs.trb.org/onlinepubs/nchrp/docs/NCHRP09-22_AMPT_QA_SoftwareManualOfPractice.pdf〉 (Jun. 12, 2012).
Moulthrop, J., and Witczak, M. (2011). NCHRP Rep. 704: A performance-related specification for hot-mixed asphalt, Transportation Research Board of the National Academies, Washington DC, 199.
Patni, A. (2009). Transportation research circular E-C137: Glossary of highway quality assurance terms, 4th update, Transportation Research Board of the National Academies, Washington, DC.
Quality-Related Specification Software (QRSS) [Computer software]. National Cooperative Highway Research Program (NCHRP), Washington, DC, 〈http://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=958〉 (Jun. 12, 2012).
Tarefder, R. A., and Sumee, N. (2011). “Evaluating sensitivity of pavement performance to mix design variable in MEPDG.” Road Mater. New Innov. Pavement Eng., 49–56.
Von Quintus, H. J., Mallela, J., Bonaquist, R., Schwartz, C. W., and Carvalho, R. L. (2011). NCHRP Rep. 719: Calibration of rutting models for structural and mix design, Transportation Research Board of the National Academies, Washington DC.
Witczak, M., Kaloush, K., Pellinen, T., El-Basyouny, M., and Von Quintus, H. (2002). NCHRP Rep. 465: Simple performance test for superpave mix design, Transportation Research Board of the National Academies, Washington, DC, 114.
Witczak, M. W., and Fonseca, O. A. (1996). “Revised predictive model for dynamic (complex) modulus of asphalt mixtures.”, Transportation Research Board, Washington, DC, 15–23.

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Published In

Go to Journal of Transportation Engineering
Journal of Transportation Engineering
Volume 140Issue 5May 2014

History

Received: Jan 22, 2013
Accepted: Jan 20, 2014
Published online: Mar 4, 2014
Published in print: May 1, 2014
Discussion open until: Aug 4, 2014

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Authors

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Leslie Myers McCarthy, Ph.D., P.E., M.ASCE [email protected]
Assistant Professor, Villanova Univ., 800 E. Lancaster Ave., Villanova, PA 19085 (corresponding author). E-mail: [email protected]
Maria Chiara Guercio [email protected]
Graduate Research Assistant, Villanova Univ., 800 Lancaster Ave., Villanova, PA 19085. E-mail: [email protected]
Thomas Bennert, Ph.D. [email protected]
Assistant Research Professor, Rutgers Univ., Center for Advanced Infrastructure and Transportation (CAIT), 100 Brett Rd., Piscataway Township, NJ 08854. E-mail: [email protected]
Van DeJarnette, A.M.ASCE [email protected]
Graduate Research Assistant, Villanova Univ., 800 Lancaster Ave., Villanova, PA 19085. E-mail: [email protected]

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