Development of Adjustment Factors for MEPDG Pavement Responses Utilizing Finite-Element Analysis
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 143, Issue 7
Abstract
The Mechanistic-empirical pavement design guide (MEPDG) provides theoretically superior methodology, as compared with its predecessor, for the design and analysis of pavement structures. The mechanistic part refers to simulating pavement–tire interaction to calculate critical responses within pavement. The empirical part means prediction of pavement distress propagation over time using transfer functions that link a critical pavement response to a particular pavement distress. The mechanistic part of MEPDG simulates tire–pavement interaction in three steps: subdivision of pavement layers; complex modulus calculation at the middepth of each sublayer, considering velocity and temperature; and running the multilayered elastic theory (MLET) software, JULEA. Although MEDPG has a grounded methodology for pavement analysis, it has a number of limitations and unrealistic simplifications that result in inaccurate response predictions. These limitations are primarily related to the pavement analysis approach used in the MEPDG framework, MLET. By contrast, finite-element (FE) analysis has proven to be a promising numerical approach for overcoming these limitations and simulating pavement more accurately and realistically. Although comparison of MLET with FE analysis has been studied, the difference between FE and MEPDG simulations has not been quantified. This study fills that gap by developing linear equations that connect pavement responses produced by these two approaches to pavement analysis. The equations are developed for ten different pavement responses, using a total of 336 cases simulated using FE and MEPDG analyses. The cases modeled in simulations were selected to capture extreme conditions, i.e., thick and thin pavement structures with strong and weak material properties. The equations developed can help pavement researchers understand quantitatively the effect of MEPDG limitations. In addition, the equations may be used as adjustment factors for MEPDG to compute pavement responses more realistically without using computationally expensive approaches, such as FE analysis.
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References
AASHTO. (2008). Mechanistic-empirical pavement design guide: A manual of practice, Washington, DC.
AASHTOWare Pavement [Computer software]. AASHTO, Washington, DC.
Al-Qadi, I. L., et al. (2008). “Accuracy of current complex modulus selection procedure from vehicular load pulse.” Transp. Res. Rec., 2087(1), 81–90.
Al-Qadi, I. L., Wang, H., Yoo, P., and Dessouky, S. (2008). “Dynamic analysis and in situ validation of perpetual pavement response to vehicular loading.” Transp. Res. Rec., 2087, 29–39.
Al-Qadi, I. L., Xie, W., and Elseifi, M. A. (2008). “Frequency determination from vehicular loading time pulse to predict appropriate complex modulus in MEPDG.” J. Assoc. Asphalt Paving Technol., 77, 739.
Al-Qadi, I. L., and Yoo, P. J. (2007). “Effect of surface tangential contact stresses on flexible pavement response.” J. Assoc. Asphalt Paving Technol., 76, 663–692.
Bayat, A., and Knight, M. (2012). “Field evaluation and analysis of flexible pavement structural responses under dynamic loads.” Road Mater. Pavement Des., 13(1), 26–37.
Elseifi, M. A., Al-Qadi, I. L., and Yoo, P. J. (2006). “Viscoelastic modeling and field validation of flexible pavements.” J. Eng. Mech., 172–178.
FHWA (Federal Highway Administration). (2017). LTTP InfoPave, Washington, DC.
Gungor, O. E., Al-Qadi, I., Gamez, A., and Hernandez, J. (2016). “Quantitative assessment of the effect of wide-base tires on pavement response by finite element analysis.” Transp. Res. Rec., 2590, 37–43.
Gungor, O. E., Al-Qadi, I. L., Gamez, A., and Hernandez, J. A. (2016). “In-situ validation of three-dimensional pavement finite element models.” Roles of accelerated pavement testing in pavement sustainability, Springer, Costa Rica, 145–159.
Hernandez, J. A., Al-Qadi, I., and De Beer, M. (2013). “Impact of tire loading and tire pressure on measured 3-D contact stresses.” Sustainable and efficient pavements, airfield and highway pavement, ASCE, Reston, VA, 551–560.
Hernandez, J. A., Gamez, A., and Al-Qadi, I. L. (2016). “Effect of wide-base tires on nationwide flexible pavement systems: Numerical modeling.” Transp. Res. Rec., 2590, 104–112.
Kim, M., Tutumluer, E., and Kwon, J. (2009). “Nonlinear pavement foundation modeling for three-dimensional finite-element analysis of flexible pavements.” Int. J. Geomech., 195–208.
Maina, J. W., Ozawa, Y., and Matsui, K. (2012). “Linear elastic analysis of pavement structure under non-circular loading.” Road Mater. Pavement Des., 13(3), 403–421.
MEPDG (Mechanistic-Empirical Pavement Design Guide) Interim Guide. (2008). Mechanistic-empirical pavement design guide: A manual of practice, AASHTO, Washington, DC.
Myers, L., Roque, R., Ruth, B., and Drakos, C. (1999). “Measurement of contact stresses for different truck tire types to evaluate their influence on near-surface cracking and rutting.” Transp. Res. Rec., 1655, 175–184.
NCHRP (National Cooperative Highway Research Program). (2004). “Guide for mechanistic-empirical design of new and rehabilitated pavement structures.”, Transportation Research Board, National Research Council, Washington, DC.
Romanoschi, S., and Metcalf, J. (2001). “Characterization of asphalt concrete layer interfaces.” Transp. Res. Rec., 1778, 132–139.
Siddharthan, R. V., Yao, J., and Sebaaly, P. E. (1998). “Pavement strain from moving dynamic 3D load distribution.” J. Transp. Eng., 557–566.
Simulia (2013). Abaqus 6.13 user’s manual, Dassault Systems, Providence, RI.
Tutumluer, E. (2008). “State of the art: Anisotropic characterization of unbound aggregate layers in flexible pavements.” Engineering Mechanics Conf., Minneapolis.
Wang, H., and Al-Qadi, I. L. (2011). “Impact quantification of wide-base tire loading on secondary road flexible pavements.” J. Transp. Eng., 630–639.
Xiao, Y., Tutumluer, E., and Siekmeier, J. (2011). “Mechanistic-empirical evaluation of aggregate base and granular subbase quality affecting flexible pavement performance in Minnesota.” Transp. Res. Rec., 2227, 97–106.
Yoo, P., and Al-Qadi, I. (2007). “Effect of transient dynamic loading on flexible pavements.” Transp. Res. Rec., 1990, 129–140.
Yoo, P. J., and Al-Qadi, I. L. (2008). “The truth and myth of fatigue cracking potential in hot-mix asphalt: Numerical analysis and validation.” J. Assoc. Asphalt Paving Technol., 77, 549.
Yoo, P. J., Al-Qadi, I. L., Elseifi, M. A., and Janajreh, I. (2006). “Flexible pavement responses to different loading amplitudes considering layer interface condition and lateral shear forces.” Int. J. Pavement Eng., 7(1), 73–86.
Ziyadi, M., and Al-Qadi, I. L. (2016). “Efficient surrogate method for predicting pavement response to various tire configurations.” Neural Comput. Appl., 1–13.
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©2017 American Society of Civil Engineers.
History
Received: May 2, 2016
Accepted: Nov 2, 2016
Published online: Feb 27, 2017
Published in print: Jul 1, 2017
Discussion open until: Jul 27, 2017
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