Recalibration and Development of Prediction Models For Dynamic Modulus Of Bituminous Mixtures

[1] D. Han, M. Yuan, and H. Hu, “Establishing prediction master curve of dynamic modulus of asphalt mixture considering randomness of aggregate morphology”, Construction and Building Materials, vol. 294, p. 123575, 2021, doi:10.1016/j.conbuildmat.2021.123575. Search in Google Scholar

[2] A. Jamshidi, G. White, and M. Hosseinpour, “Revisiting the correlation between the dynamic modulus and the flexural modulus of hot mixture asphalt”, Construction and Building Materials, vol. 296, p. 123697, 2021, doi:10.1016/j.conbuildmat.2021.123697. Search in Google Scholar

[3] AASHTO, “Standard Method of Test for Determining Dynamic Modulus of Hot-Mix Asphalt Concrete Mix”, TP 62-07, American Association of State Highway and Transportation Officials, 2006. Search in Google Scholar

[4] Y. H. Huang, “Pavement Analysis and Design”, vol. 2, pp. 401-409, Upper Saddle River, NJ: Pearson Prentice Hall, 2004. Search in Google Scholar

[5] A. Behnood, “A review of the warm mix asphalt (WMA) technologies: Effects on thermo-mechanical and rheological properties”, Journal of Cleaner Production, vol. 259, p. 120817, 2020, doi:10.1016/j.jclepro.2020.120817. Search in Google Scholar

[6] A. Behnood, “Application of rejuvenators to improve the rheological and mechanical properties of asphalt binders and mixtures: A review”, Journal of Cleaner Production, vol. 231, pp. 171-182, 2019, doi:10.1016/j.jclepro.2019.05.209 Search in Google Scholar

[7] A. Behnood and M. M. Gharehveran, “Morphology, rheology, and physical properties of polymer-modified asphalt binders”, European Polymer Journal, vol. 112, pp. 766-791, 2019, doi:10.1016/j.eurpolymj.2018.10.049. Search in Google Scholar

[8] G. W. Flintsch, A. Loulizi, S. D. Diefenderfer, K. A. Galal, and B. K. Diefenderfer, “Asphalt materials characterization in support of implementation of the proposed mechanistic-empirical pavement design guide”, Virginia Center for Transportation Innovation and Research, 2007. Search in Google Scholar

[9] M. Junaid, M. Z. A. Shah, G. Yaseen, H. H. Awan, D. Khan, and M. Jawad, “Investigating the effect of gradation, temperature and loading duration on the resilient modulus of asphalt concrete,” Civil Engineering Journal, vol. 8, no. 02, 2022, doi:10.28991/CEJ-2022-08-02-07. Search in Google Scholar

[10] G. Suleiman, H. H. Aodah, S. Hanandeh, M. Ergun, R. Abu Salim, and D. Qtiashat, “Investigating the dynamic creep of polymer modified hot mix asphalt,” Civil and Environmental Engineering, vol. 20, no. 1, pp. 387–396, 2024, doi:10.2478/cee-2024-0030. Search in Google Scholar

[11] D. Han, M. Yuan, and H. Hu, “Establishing prediction master curve of dynamic modulus of asphalt mixture considering randomness of aggregate morphology”, Construction and Building Materials, vol. 294, p. 123575, 2021, doi:10.1016/j.conbuildmat.2021.123575. Search in Google Scholar

[12] J. Ahmad, M. R. Hainin, E. Shaffie, K. A. Masri, and M. A. Shaffi, “Effect of temperature on phase angle and dynamic modulus of asphalt mixtures using SPT”, Materials Science Forum, vol. 1007, pp. 99-104, Trans Tech Publications Ltd, September 2020. Search in Google Scholar

[13] Junaid, M., Jiang, C., Eltwati, A., Khan, D., Alamri, M., & Eisa, M. S. (2024). Statistical analysis of low-density and high-density polyethylene modified asphalt mixes using the response surface method. Case Studies in Construction Materials, 21, e03697. doi:10.1016/j.cscm.2024.e03697. Search in Google Scholar

[14] Junaid, M., Jiang, C., Gazder, U., Hafeez, I., & Khan, D. (2024). Evaluation of asphalt mixtures modified with low-density polyethylene and high-density polyethylene using experimental results and machine learning models. Scientific Reports, 14(1), 24601. doi:10.1038/s41598-024-74657-1 Search in Google Scholar

[15] Y. Zhang, L. Sun, and H. Cheng, “Effects of nominal maximum aggregate size and compaction effort on the mechanical properties of hot-mix asphalt (HMA)”, Construction and Building Materials, vol. 324, p. 126715, 2022, doi:10.1016/j.conbuildmat.2022.126715. Search in Google Scholar

[16] H. Chen, R. G. Saba, G. Liu, D. M. Barbieri, X. Zhang, and I. Hoff, “Influence of material factors on the determination of dynamic moduli and associated prediction models for different types of asphalt mixtures”, Construction and Building Materials, vol. 365, p. 130134, 2023, doi:10.1016/j.conbuildmat.2022.130134. Search in Google Scholar

[17] M. Zhang, H. Zhao, L. Fan, and J. Yi, “Dynamic modulus prediction model and analysis of factors influencing asphalt mixtures using gray relational analysis methods”, Journal of Materials Research and Technology, vol. 19, pp. 1312-1321, 2022, doi:10.1016/j.jmrt.2022.05.120. Search in Google Scholar

[18] M. R. Islam, S. A. Kalevela, and G. Mendel, “How the mix factors affect the dynamic modulus of hot-mix asphalt”, Journal of Composites Science, vol. 3, no. 3, p. 72, 2019, doi:10.3390/jcs3030072. Search in Google Scholar

[19] A. I. Kareem, T. T. Khaled, A. Aljubory, R. Kh. S. Al-Hamd, and D. Isaac, “Investigating the influence of mineral fillers at Australian asphalt mixtures,” Civil and Environmental Engineering, vol. 20, no. 1, pp. 109–123, 2024, doi:10.2478/cee-2024-0010. Search in Google Scholar

[20] A. Behnood and E. M. Golafshani, “Predicting the dynamic modulus of asphalt mixture using machine learning techniques: An application of multi biogeography-based programming”, Construction and Building Materials, vol. 266, p. 120983, 2021, doi:10.1016/j.conbuildmat.2020.120983. Search in Google Scholar

[21] D. Daneshvar and A. Behnood, “Estimation of the dynamic modulus of asphalt concretes using random forests algorithm”, International Journal of Pavement Engineering, vol. 23, no. 2, pp. 250-260, 2022, doi:10.1080/10298436.2020.1741587. Search in Google Scholar

[22] G. Mazurek, P. Buczyński, and M. Iwański, “Stiffness modulus prediction against basic physical and mechanical characteristics of recycled base course with foamed bitumen and emulsified bitumen”, Archives of Civil Engineering, vol. 69, no. 3, 2023, doi: 10.24425/ace.2023.146069. Search in Google Scholar

[23] X. Ai, J. Cao, D. Feng, L. Gao, W. Hu, and J. Yi, “Performance evaluation of recycled asphalt mixtures with various percentages of RAP from the rotary decomposition process”, Construction and Building Materials, vol. 321, p. 126406, 2022, doi:10.1016/j.conbuildmat.2022.126406. Search in Google Scholar

[24] Y. H. Pi, G. C. Li, Z. Li, and Y. Li, “Static and dynamic moduli of a cold recycled emulsified asphalt mixture”, Strength of Materials, vol. 52, pp. 646-654, 2020. Search in Google Scholar

[25] D. Witczak Andrei, M. W. Witczak, and M. W. Mirza, “Development of a revised predictive model for the dynamic (complex) modulus of asphalt mixtures”, NCHRP Report 1-37A, University of Maryland, College Park, MD, USA, 1999. Search in Google Scholar

[26] J. Bari and M. W. Witczak, “Development of a new revised version of the witczak E* predictive model for hot mix asphalt mixtures”, Journal of the Association of Asphalt Paving Technologies, vol. 75, pp. 381-423, 2006. Search in Google Scholar

[27] AASHTO, “Mechanistic-empirical pavement design guide: A manual of practice”, American Association of State and Highway Transportation Officials, Washington DC, USA, 2015. Search in Google Scholar

[28] AASHTO, “Pavement design, construction, and management”, American Association of State and Highway Transportation Officials, Washington DC, USA, 2015. Search in Google Scholar

[29] C. W. Schwartz, “Evaluation of the Witczak dynamic modulus prediction model”, Proceedings of the 84th Annual Meeting of the Transportation Research Board, Washington, DC, vol. 1, no. 9, 2005. Search in Google Scholar

[30] H. Ceylan, C. W. Schwartz, S. Kim, and K. Gopalakrishnan, “Accuracy of predictive models for dynamic modulus of hot-mix asphalt”, Journal of Materials in Civil Engineering, vol. 21, no. 6, pp. 286-293, 2009, doi:10.1061/(ASCE)0899-1561(2009)21:6(286). Search in Google Scholar

[31] ASTM, “Standard Test Method for Marshall Stability and Flow of Asphalt Mixtures”, D 6927. Search in Google Scholar

[32] L. Tashman and M. A. Elangovan, “Dynamic modulus test-laboratory investigation and future implementation in the State of Washington”, WA-RD 704.1, 2008. Search in Google Scholar

[33] J. Mandula and T. Olexa, “Study of the visco-elastic parameters of asphalt concrete”, Procedia Engineering, vol. 190, pp. 207-214, 2017, doi:10.1016/j.proeng.2017.05.328. Search in Google Scholar

[34] AASHTO, “Standard Method of Test for Determining the Dynamic Modulus and Flow Number for Hot Mix Asphalt (HMA) Using the Asphalt Mix Performance Tester (AMPT)”, T. TP-79, American Association of State Highway & Transportation Officials, Washington DC, 2010. Search in Google Scholar

[35] R. F. Bonaquist, “Ruggedness testing of the dynamic modulus and flow number tests with the simple performance tester”, Washington, DC: The National Academies Press, 2008. Search in Google Scholar

[36] M. W. Witczak, D. Andrei, and W. N. Houston, “Guide for mechanistic-empirical design of new and rehabilitated pavement structures”, Transportation Research Board of the National Research Council, 2004, pp. 1-91. Search in Google Scholar

[37] AASHTO, “Standard Method of Test for Determining Dynamic Modulus of Hot-Mix Asphalt Concrete Mix”, TP 62-07, American Association of State Highway and Transportation Officials, 2006. Search in Google Scholar

[38] H. Azari, G. Al-Khateeb, A. Shenoy, and N. Gibson, “Comparison of Measured STP E* of ALF Mixtures with Predicted E* Using NCHRP 1-37 A and Witczak’s new equations”, CD-ROM, Presented at 86th Annual Transportation Research Board Meeting, Transportation Research Board, Washington, DC, 2007. Search in Google Scholar

[39] X. Shu and B. Huang, “Micromechanics-based dynamic modulus prediction of polymeric asphalt concrete mixtures”, Composites Part B: Engineering, vol. 39, no. 4, pp. 704-713, 2008, doi:10.1016/j.compositesb.2007.05.003. Search in Google Scholar

[40] R. P. Leandro, K. L. Vasconcelos, and L. L. B. Bernucci, “Evaluation of the laboratory compaction method on the air voids and the mechanical behavior of hot mix asphalt”, Construction and Building Materials, vol. 156, pp. 424-434, 2017, doi:10.1016/j.conbuildmat.2017.08.178. Search in Google Scholar

[41] N. Koyuncu and C. Kadilar, “Ratio and product estimators in stratified random sampling”, Journal of Statistical Planning and Inference, vol. 139, no. 8, pp. 2552-2558, 2009, doi:10.1016/j.jspi.2008.11.009. Search in Google Scholar

[42] J. Barugahare, A. N. Amirkhanian, F. Xiao, and S. N. Amirkhanian, “ANN-based dynamic modulus models of asphalt mixtures with similar input variables as Hirsch and Witczak models”, International Journal of Pavement Engineering, vol. 23, no. 5, pp. 1328-1338, 2022, doi:10.1080/10298436.2020.1799209. Search in Google Scholar

[43] A. M. Awed, A. N. Awaad, M. R. Kaloop, J. W. Hu, S. M. El-Badawy, and R. T. Abd El-Hakim, “Boosting Hot Mix Asphalt Dynamic Modulus Prediction Using Statistical and Machine Learning Regression Modeling Techniques”, Sustainability, vol. 15, no. 19, p. 14464, 2023, doi:10.3390/su151914464. Search in Google Scholar

[44] P. K. Ozili, “The acceptable R-square in empirical modelling for social science research”, Social research methodology and publishing results: A guide to non-native english speakers, pp. 134-143, IGI Global, 2023, doi: 10.4018/978-1-6684-6859-3.ch009. Search in Google Scholar

[45] A. N. Spiess and N. Neumeyer, “An evaluation of R2 as an inadequate measure for nonlinear models in pharmacological and biochemical research: a Monte Carlo approach”, BMC pharmacology, vol. 10, no. 1, pp. 1-11, 2010. Search in Google Scholar

[46] H. Wang, I. L. Al-Qadi, A. F. Faheem, H. U. Bahia, S. H. Yang, and G. H. Reinke, “Effect of mineral filler characteristics on asphalt mastic and mixture rutting potential”, Transportation Research Record, vol. 2208, no. 1, pp. 33-39, 2011, doi:10.3141/2208-05. Search in Google Scholar

[47] E. W. Tarbay, A. M. Azam, and S. M. El-Badawy, “Waste materials and by-products as mineral fillers in asphalt mixtures”, Innovative Infrastructure Solutions, vol. 4, no. 1, p. 5, 2019. Search in Google Scholar