عنوان مقاله [English]
Mechanistic–Empirical Pavement Design Guide (MEPDG) uses dynamic modulus for flexible pavement design and rehabilitation. This parameter could be defined as the viscoelastic property of asphalt materials. Mechanistic–Empirical Pavement Design Guide (MEPDG) uses results of both Falling Weight Deflectometer (FWD) and laboratory dynamic modulus predictive models for determination of dynamic modulus of in-service asphalt layers. In this research, ten asphalt pavement sites were selected in Khuzestan and Kerman provinces in Iran. Field and laboratory testing were performed and dynamic modulus of in-service asphalt layers was determined. Hirsch predictive model for dynamic modulus of asphalt mixes was calibrated and new model was developed for predicting in-situ dynamic modulus of asphalt layers. Performance evaluation and validation of this new model showed very good correlation between predicted and measured values with high prediction accuracy and low prediction bias.
Keywords: Dynamic Modulus of Asphalt Layers, FWD, Dynamic Modulus Predictive Models, Hirsch Model, Mechanistic–Empirical Pavement Design Guide (MEPDG).
AASHTO. 2012. “Standard method of test for determining the rheological properties of asphalt binder using a dynamic shear rheometer (DSR)”. AASHTO Designation: T 315-12.
AASHTO. 2014. “Standard method of test for quantitative extraction of asphalt binder from hot-mix asphalt (HMA)”. AASHTO Designation: T 164-14.
ARA. 2004. “Guide for mechanistic-empirical design of new and rehabilitated pavement structures”. NCHRP 1-37A, National Cooperative Highway Research Program, Transportation Research Board, National Research Council, Washington, D.C.
ASTM. 2011. “Standard test methods for quantitative extraction of bitumen from bituminous paving mixtures (D2172/D2172M-11)”. West Conshohocken, PA. http://dx.doi.org/10.1520/D2172_D2172M-11.
ASTM. 2015. “Standard test method for determining the rheological properties of asphalt binder using a dynamic shear rheometer (D7175-15)”. West Conshohocken, PA. http://dx.doi.org/10.1520/D7175-15. 5.
Christensen, D. W., Pellinen, T. and Bonaquist, R. F. 2003. “Hirsch model for estimating the modulus of asphalt concrete”. J. Assoc. Asphalt Paving Technol., 72: 97-121.
Georgouli, K., Pomoni, M., Cliatt, B. and Loizos, A. 2015. “A simplified approach for the estimation of HMA dynamic modulus for in service pavements”. 6th International Conference on Bituminous Mixtures and Pavements, Thessaloniki, Greece, 10-12 June.
Gopalakrishnan, K., Ceylan, H., Kim, S. and Kaya, O. 2014. “Development of asphalt dynamic modulus master curve using falling weight deflectometer measurements”. TR-659, Institute for Transportation, Iowa State University.
Gopalakrishnan, K., Kim, S., Ceylan, H. and Kaya, O. 2015. “Use of neural networks enhanced differential evolution for backcalculating asphalt concrete viscoelastic properties from falling weight deflectometer time series data”. 6th International Conference on Bituminous Mixtures and Pavements, Thessaloniki, Greece, 10-12 June.
Kavussi, A., Solatifar, N. and Abbasghorbani, M. (2016). “Mechanistic-empirical analysis of asphalt dynamic modulus for rehabilitation projects in Iran”. J. Rehabil. Civ. Eng., 4(1): 18-29. https://doi.org/10.22075/jrce.2016.488.
Kutay, E., Chatti, K. and Lei, L. 2011. “Backcalculation of dynamic modulus master curve from falling weight deflectometer surface deflections”. Transport. Res. Record: J. Transport. Res. Board, 2227: 87-96. https://doi.org/10.3141/2227-10.
Loulizi, A., Flintsch, G. W. and McGhee, K. 2007. “Determination of the in-place hot-mix asphalt layer modulus for rehabilitation projects by a mechanistic-empirical procedure”. Transport. Res. Record: J. Transport. Res. Board, 2037: 53-62. https://doi.org/10.3141/2037-05.
Lytton, R. L., Germann, F. P., Chou, Y. J. and Stoffels, S. M. 1990. “Determining asphaltic concrete pavement structural properties by nondestructive testing”. National Cooperative Highway Research Program (NCHRP), Report 327, Transportation Research Board, Washington, D.C.
Seo, J., Kim, Y., Cho, J. and Jeong, S. 2013. “Estimation of in situ dynamic modulus by using MEPDG dynamic modulus and FWD data at different temperatures”. Int. J. Pavement Eng., 14(4): 343-353. https://doi.org/10.1080/10298436.2012.664274.
Solatifar, N. 2018. “Analysis of conventional dynamic modulus predictive models of asphalt mixtures”. Amirkabir J. Civ. Eng., In press. http://dx.doi.org/10.22060/ceej.2018.15006.5811.
Solatifar, N., Abbasghorbani, M., Kavussi, A. and Sivilevičius, H. 2018. “Prediction of depth temperature of asphalt layers in hot climate areas”. J. Civ. Eng. Manage., 24(7): 516-525. https://doi.org/10.3846 /jcem.2018.6162.
Solatifar, N., Kavussi, A., Abbasghorbani, M. and Katicha, S. W. 2019. “Development of dynamic modulus master curves of in-service asphalt layers using MEPDG models”. Road Mater. Pavement Design, 20(1): 225-243. https://doi.org/10.1080/14680629.2017.1380688.
Solatifar, N., Kavussi, A., Abbasghorbani, M. and Sivilevičius, H. 2017. “Application of FWD data in developing dynamic modulus master curves of in-service asphalt layers”. J. Civ. Eng. Manage., 23(5): 661-671. https://doi.org/10.3846/13923730.2017.1292948.
Ullidtz, P. 2000. “Will nonlinear backcalculation help?”. In: Tayabji, S. D. and Lukanen, E. O. (Eds.), Nondestructive Testing of Pavements and Backcalculation of Moduli, Third Volume, ASTM STP 1375, American Society for Testing and Materials, West Conshohocken, PA. http://dx.doi.org /10.1520/STP14757S.
Varma, S. and Kutay, M. E. 2016. “Backcalculation of viscoelastic and nonlinear flexible pavement layer properties from falling weight deflections”. Int. J. Pavement Eng., 17(5): 388-402. https://doi.org /10.1080 /10298436.2014.993196.
Varma, S., Kutay, M. E. and Levenberg, E. 2013. “Viscoelastic Genetic Algorithm for inverse analysis of asphalt layer properties from falling weight deflections”. Transport. Res. Record: J. Transport. Res. Board, 2369: 38-46. https://doi.org/10.3141/2369-05.