Random Modeling of Three-Dimensional Heterogeneous Microstructure of Asphalt Concrete for Mechanical Analysis
Publication: Journal of Engineering Mechanics
Volume 144, Issue 9
Abstract
This paper develops an algorithm for generating the three-dimensional (3D) heterogeneous microstructure of asphalt concrete based on random modeling. The asphalt concrete was modeled as heterogeneous material with fine aggregate matrix (FAM), coarse aggregates, and air voids. We generated 3D aggregate shapes with three two-dimensional (2D) projections randomly selected from the aggregate image database. We generated the 3D models of asphalt concrete by randomly placing 3D aggregates and air voids into the virtual specimen with compact packing. We predicted the dynamic modulus of asphalt concrete specimens with different microstructures through finite element (FE) analysis and validated with experimental data. The relative differences between the average dynamic modulus and the experimental data ranged from 0.32 to 6.01% for different frequencies, which indicates that the 3D heterogeneous microstructure model is acceptably accurate. The volume of aggregate in each sieve is the major factor controlling bulk material properties like dynamic modulus. We also generated 2D heterogeneous models of asphalt concrete by cutting the 3D model from different cross sections. The variation of dynamic modulus with the 2D models was much greater than the variation with the 3D models. The ratio of coarse aggregate content in the 2D and 3D models can range from 0.86 to 1.35. Although, in general, the predicted dynamic modulus increases as coarse aggregate content increases in 2D models, we observed variations due to differences in microstructure.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The authors would like to acknowledge the financial support provided by China Postdoctoral Science Foundation.
References
Applied Research Associates. 2004. Guide for mechanistic-empirical design of new and rehabilitated pavement structures. Washington, DC: Applied Research Associates.
Aragao, F. T. S., D. A. Hartmann, A. R. G. Pazos, and Y. R. Kim. 2017. “Virtual fabrication and computational simulation of asphalt concrete microstructure.” Int. J. Pavement Eng. 18 (9): 859–870.
Aragao, F. T. S., Y. Kim, J. Lee, and D. H. Allen. 2011. “Micromechanical model for heterogeneous asphalt concrete mixtures subjected to fracture failure.” J. Mater. Civ. Eng. 23 (1): 30–38.
Birgisson, B., and R. Roque. 2005. “Evaluation of the gradation effect on the dynamic modulus.” Transp. Res. Rec. 1929 (1): 193–199. https://doi.org/10.1177/0361198105192900123.
Cao, P., F. Jin, D. Feng, C. Zhou, and W. Hu. 2016. “Prediction on dynamic modulus of asphalt concrete with random aggregate modeling methods and virtual physics engine.” Constr. Build. Mater. 125: 987–997. https://doi.org/10.1016/j.conbuildmat.2016.08.121.
Caro, S. 2009. “A coupled micromechanical model of moisture-induced damage in asphalt mixtures: Formulation and applications.” Ph.D. dissertation, Zachry Department of Civil Engineering, Texas A&M Univ.
Caro, S., E. Masad, A. Bhasin, and D. Little. 2010. “Micromechanical modeling of the influence of material properties on moisture-induced damage in asphalt mixtures.” Constr. Build. Mater. 24 (7): 1184–1192. https://doi.org/10.1016/j.conbuildmat.2009.12.022.
Caro, S., E. Masad, M. Sanchez-Silva, and D. Little. 2011. “Stochastic micromechanical model of the deterioration of asphalt mixtures subject to moisture diffusion processes.” Int. J. Numer. Anal. Methods Geomech. 35 (10): 1079–1097. https://doi.org/10.1002/nag.943.
Castillo, D., S. Caro, M. Darabi, and E. Masad. 2015. “Studying the effect of microstructural properties on the mechanical degradation of asphalt mixtures.” Constr. Build. Mater. 93: 70–83. https://doi.org/10.1016/j.conbuildmat.2015.05.108.
Chen, J., H. Wang, and L. Li. 2015a. “Determination of effective thermal conductivity of asphalt concrete with random aggregate microstructure.” J. Mater. Civ. Eng. 27 (12): 04015045. https://doi.org/10.1061/(ASCE)MT.1943-5533.0001313.
Chen, J., H. Wang, and L. Li. 2017. “Virtual testing of asphalt mixture with two-dimensional and three-dimensional random aggregate structures.” Int. J. Pavement Eng. 18 (9): 824–836. https://doi.org/10.1080/10298436.2015.1066005.
Chen, J., M. Zhang, H. Wang, and L. Li. 2015b. “Evaluation of thermal conductivity of asphalt concrete with heterogeneous microstructure.” Appl. Therm. Eng. 84 (6): 368–374. https://doi.org/10.1016/j.applthermaleng.2015.03.070.
Dai, Q. 2011. “Two- and three-dimensional micromechanical viscoelastic finite element modeling of stone-based materials with X-ray computed tomography images.” Constr. Build. Mater. 25 (2): 1102–1114. https://doi.org/10.1016/j.conbuildmat.2010.06.066.
Dai, Q., and Z. You. 2008. “Micromechanical finite element framework for predicting viscoelastic properties of asphalt mixtures.” Mater. Struct. 41 (6): 1025–1037. https://doi.org/10.1617/s11527-007-9303-4.
Elseifi, M. A., L. N. Mohammad, E. Kassem, H. Ying, and E. Masad. 2011. “Quantification of damage in the dynamic complex modulus and flow number tests using X-ray computed tomography.” J. Mater. Civ. Eng. 30 (2): 1687–1696. https://doi.org/10.1061/(ASCE)MT.1943-5533.0000346.
Hunter, A. E., G. D. Airey, and A. C. Collop. 2004. “Aggregate orientation and segregation in laboratory-compacted asphalt samples.” Transp. Res. Rec. 1891: 8–15. https://doi.org/10.3141/1891-02.
Jin, C., Z. You, W. Zhang, and K. Liu. 2016. “Microstructural modeling method for asphalt specimens supporting 3D adaptive and automatic mesh generation.” J. Mater. Civ. Eng. 30 (2): 04015013. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000478.
Kim, Y. R., F. A. C. Freitas, J. S. Jung, and Y. Sim. 2015. “Characterization of bitumen fracture using tensile tests incorporated with viscoelastic cohesive zone model.” Constr. Build. Mater. 88: 1–9. https://doi.org/10.1016/j.conbuildmat.2015.04.002.
Kutay, E., H. I. Ozturk, A. R. Abbas, and C. C. Hu. 2011. “Comparison of 2D and 3D image-based aggregate morphological indices.” Int. J. Pavement Eng. 12 (4): 421–431. https://doi.org/10.1080/10298436.2011.575137.
Kutay, M. E., A. H. Aydilek, and E. Masad. 2007. “Estimating directional permeability of hot-mix asphalt by numerical simulation of microscale water flow.” Transp. Res. Rec. 2001: 29–36. https://doi.org/10.3141/2001-04.
Liu, Y., and Z. You. 2009. “Visualization and simulation of asphalt concrete with randomly generated three-dimensional models.” J. Comput. Civ. Eng. 23 (6): 340–347. https://doi.org/10.1061/(ASCE)0887-3801(2009)23:6(340).
Ma, T., H. Wang, D. Zhang, and Y. Zhang. 2017. “Heterogeneity effect on creep behavior of asphalt mixture based on three-dimensional discrete element modeling.” Mech. Mater. 104: 49–59. https://doi.org/10.1016/j.mechmat.2016.10.003.
Masad, E., V. K. Jandhyala, N. Dasgupta, N. Somadevan, and N. Shashidhar. 2002. “Characterization of air void distribution in asphalt mixes using X-ray computed tomography.” J. Mater. Civ. Eng. 14 (2): 122–129. https://doi.org/10.1061/(ASCE)0899-1561(2002)14:2(122).
Masad, E., D. Olcott, T. White, and L. Tashman. 2001. “Correlation of fine aggregate imaging shape indices with asphalt mixture performance.” Transp. Res. Rec. 1757: 148–156. https://doi.org/10.3141/1757-17.
National Research Council. 2002. Simple performance test for Superpave mix design. Washington, DC: National Research Council.
Rami, K. Z., S. Amelian, Y. R. Kim, T. You, and D. N. Little. 2017. “Modeling the 3D fracture-associated behavior of viscoelastic asphalt mixtures using 2D microstructures.” Eng. Fract. Mech. 182: 86–99. https://doi.org/10.1016/j.engfracmech.2017.07.015.
Tehrani, F. F., J. Absi, F. Allou, and C. Petit. 2013. “Investigation into the impact of the use of 2D/3D digital models on the numerical calculation of the bituminous composites’ complex modulus.” Comput. Mater. Sci. 79: 377–389. https://doi.org/10.1016/j.commatsci.2013.05.054.
Wang, H., J. Wang, and J. Chen. 2014. “Micromechanical analysis of asphalt mixture fracture with adhesive and cohesive failure.” Eng. Fract. Mech. 132: 104–119. https://doi.org/10.1016/j.engfracmech.2014.10.029.
Wang, H., J. Wang, and J. Chen. 2017. “Fracture modeling of asphalt concrete with random aggregate microstructure.” Road. Mater. Pavement., in press. https://doi.org/10.1080/14680629.2017.1345778.
Wang, L. B., J. Y. Park, and Y. R. Fu. 2007. “Representation of real particles for DEM simulation using X-ray tomography.” Constr. Build. Mater. 21 (2): 338–346. https://doi.org/10.1016/j.conbuildmat.2005.08.013.
Ying, H., M. A. Elseifi, L. N. Mohammad, and M. M. Hassan. 2014. “Heterogeneous finite-element modeling of the dynamic complex modulus test of asphalt mixture using X-ray computed tomography.” J. Mater. Civ. Eng. 26 (9): 04014052. https://doi.org/10.1061/(ASCE)MT.1943-5533.0000949.
Zhang, L., H. Wang, and Z. Ren. 2017. “Computational analysis of thermal conductivity of asphalt mixture using virtually generated three-dimensional microstructure.” J. Mater. Civ. Eng. 29 (12): 04017234. https://doi.org/10.1061/(ASCE)MT.1943-5533.0002081.
Information & Authors
Information
Published In
Journal of Engineering Mechanics
Volume 144 • Issue 9 • September 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: Sep 15, 2017
Accepted: Mar 28, 2018
Published online: Jun 29, 2018
Published in print: Sep 1, 2018
Discussion open until: Nov 29, 2018
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.