Comparative modelling of indirect tensile strength of asphalt mixtures with and without considering air void characteristics

References

• Abbas, A., et al., 2005. Modelling asphalt mastic stiffness using discrete element analysis and micromechanics-based models. International Journal of Pavement Engineering, 6 (2), 137–146. doi: https://doi.org/10.1080/10298430500159040
   Google Scholar
• ACD Systems International Inc, 2007. ACDSee 8.0. Victoria, British Columbia, Canada.
   Google Scholar
• Arambula, E., Masad, E., and Martin, A.E., 2007. Influence of air void distribution on the moisture susceptibility of asphalt mixes. Journal of Materials in Civil Engineering, 19 (8), 655–664. doi: https://doi.org/10.1061/(ASCE)0899-1561(2007)19:8(655)
   Web of Science ®Google Scholar
• Buttlar, W. and You, Z., 2001. Discrete element modeling of asphalt concrete: microfabric approach. Transportation Research Record: Journal of the Transportation Research Board, 1757, 111–118. doi: https://doi.org/10.3141/1757-13
   Web of Science ®Google Scholar
• Chen, J.S., Huang, B.S., and Shu, X., 2013. Air-void distribution analysis of asphalt mixture using discrete element method. Journal of Materials in Civil Engineering, 25 (10), 1375–1385. doi: https://doi.org/10.1061/(ASCE)MT.1943-5533.0000661
   Web of Science ®Google Scholar
• Dai, Q., Sadd, M.H., and You, Z., 2006. A micromechanical finite element model for linear and damage-coupled viscoelastic behaviour of asphalt mixture. International Journal for Numerical and Analytical Methods in Geomechanics, 30, 1135–1158. doi: https://doi.org/10.1002/nag.520
   Web of Science ®Google Scholar
• Elliot, R.P., et al., 1992. Effect of aggregate gradation variation on asphalt concrete mix properties. Transportation Research Record: Journal of the Transportation Research Board, 1317 (1), 52–60.
   Google Scholar
• Hu, J., et al., 2015. Influence of aggregate particles on mastic and air-voids in asphalt concrete. Construction and Building Materials, 93, 1–9. doi: https://doi.org/10.1016/j.conbuildmat.2015.05.031
   Web of Science ®Google Scholar
• Itasca Consulting Group, 2004. Particle flow code in three-dimensions (PFC3D) manual version 3.1. Minneapolis, MN.
   Google Scholar
• Kim, H. and Buttlar, W.G., 2009. Discrete fracture modeling of asphalt concrete. International Journal of Solids and Structures, 46 (13), 2593–2604. doi: https://doi.org/10.1016/j.ijsolstr.2009.02.006
   Web of Science ®Google Scholar
• Kim, H., Wagoner, M.P., and Buttlar, W.G., 2008. Simulation of fracture behavior in asphalt concrete using a heterogeneous cohesive zone discrete element model. Journal of Materials in Civil Engineering, 20 (8), 552–563. doi: https://doi.org/10.1061/(ASCE)0899-1561(2008)20:8(552)
   Web of Science ®Google Scholar
• Kose, S., 2002. Development of a virtual test procedure for asphalt concrete. PhD dissertation. University of Wisconsin-Madison.
   Google Scholar
• Kose, S., et al., 2000. Distribution of strains within hot-mix asphalt binders: applying imaging and finite-element techniques. Transportation Research Record: Journal of the Transportation Research Board, 1728, 21–27. doi: https://doi.org/10.3141/1728-04
   Google Scholar
• Ma, T., et al., 2016a. Effect of air voids on the high-temperature creep behavior of asphalt mixture based on three-dimensional discrete element modeling. Materials and Design, 89, 304–313. doi: https://doi.org/10.1016/j.matdes.2015.10.005
   Web of Science ®Google Scholar
• Ma, T., et al., 2016b. Influences by air voids on fatigue life of asphalt mixture based on discrete element method. Construction and Building Materials, 126, 785–799. doi: https://doi.org/10.1016/j.conbuildmat.2016.09.045
   Web of Science ®Google Scholar
• Masad, E., et al., 1999. Internal structure characterization of asphalt concrete using image analysis. Journal of Computing in Civil Engineering, 13 (2), 88–95. doi: https://doi.org/10.1061/(ASCE)0887-3801(1999)13:2(88)
   Web of Science ®Google Scholar
• Masad, E., et al., 2002. Characterization of air void distribution in asphalt mixes using X-ray computed tomography. Journal of Materials in Civil Engineering, 14 (2), 122–129. doi: https://doi.org/10.1061/(ASCE)0899-1561(2002)14:2(122)
   Web of Science ®Google Scholar
• Monismith, C.L., 1992. Analytically based asphalt pavement design and rehabilitation. Transportation Research Record 1354, Transportation Research Board, Washington, DC, 5–26.
   Google Scholar
• Nguyen, T.T., et al., 2019. A micromechanical investigation for the effects of pore size and its distribution on geopolymer foam concrete under uniaxial compression. Engineering Fracture Mechanics, 209, 228–244. doi: https://doi.org/10.1016/j.engfracmech.2019.01.033
   Web of Science ®Google Scholar
• Obaidat, M.T., et al., 1998. An innovative digital image analysis approach to quantify the percentage of voids in mineral aggregates of bituminous mixtures. Canadian Journal of Civil Engineering, 25 (6), 1041–1049. doi: https://doi.org/10.1139/l98-034
   Web of Science ®Google Scholar
• Papagiannakis, A.T., Abbas, A., and Masad, E., 2002. Micromechanical analysis of viscoelastic properties of asphalt concretes. Transportation Research Record: Journal of the Transportation Research Board, 1789, 113–120. doi: https://doi.org/10.3141/1789-12
   Google Scholar
• Peng, Y. and Bao, J.X., 2018. Micromechanical analysis of asphalt-mixture shear strength using the three-dimensional discrete element method. Journal of Materials in Civil Engineering, 30 (11), 04018302. doi: https://doi.org/10.1061/(ASCE)MT.1943-5533.0002508
   Web of Science ®Google Scholar
• Peng, Y., Harvey, J., and Sun, L.J., 2017. Three-dimensional discrete-element modeling of aggregate homogeneity influence on indirect tensile strength of asphalt mixtures. Journal of Materials in Civil Engineering, 29 (11), 04017211. doi: https://doi.org/10.1061/(ASCE)MT.1943-5533.0002034
   Web of Science ®Google Scholar
• Peng, Y. and Sun, L.J., 2009. Effects of air void content on asphalt mixture performance. Journal of Wuhan University of Technology (Transportation Science and Engineering), 33 (5), 826–829.
   Google Scholar
• Peng, Y., et al., 2019a. Numerical simulation of influence factors of splitting strength of asphalt mixtures. Journal of Jilin University (Engineering and Technology), 49 (5), 1521–1530.
   Google Scholar
• Peng, Y., Wan, L., and Sun, L.J., 2019b. Three-dimensional discrete element modelling of influence factors of indirect tensile strength of asphalt mixtures. International Journal of Pavement Engineering, 20 (6), 724–733. doi: https://doi.org/10.1080/10298436.2017.1334459
   Web of Science ®Google Scholar
• Rao, C.B., 2001. Development of 3-D image analysis techniques to determine shape and size properties of coarse aggregate. PhD dissertation. University of Illinois at Urbana-Champaign.
   Google Scholar
• Ren, J.L. and Sun, L., 2017. Characterizing air void effect on fracture of asphalt concrete at low-temperature using discrete element method. Engineering Fracture Mechanics, 170, 23–43. doi: https://doi.org/10.1016/j.engfracmech.2016.11.030
   Web of Science ®Google Scholar
• Roberts, F.L., et al., 1996. Hot mix asphalt materials, mixture design and construction. Lanham: NAPA Education Foundation, Md.
   Google Scholar
• Rotherburg, L., et al., 1992. Micromechanical modeling of asphalt concrete in connection with pavement rutting problems. In: 7th international conference on asphalt pavements, Nottingham, UK, ARRB Group Limited, Vermont South, Victoria, Australia.
   Google Scholar
• Sefidmazgi, N.R., Tashman, L., and Bahia, H., 2012. Internal structure characterization of asphalt mixtures for rutting performance using imaging analysis. Road Materials and Pavement Design, 13 (S1), 21–37. doi: https://doi.org/10.1080/14680629.2012.657045
   Web of Science ®Google Scholar
• Soares, J.B., de Freitas, F.A.C., and Allen, D.H., 2003. Considering material heterogeneity in crack modeling of asphaltic mixtures. Transportation Research Record: Journal of the Transportation Research Board, 1832, 113–120. doi: https://doi.org/10.3141/1832-14
   Google Scholar
• Tashman, L., et al., 2002. X-ray tomography to characterize air void distribution in superpave gyratory compacted specimens. International Journal of Pavement Engineering, 3 (1), 19–28. doi: https://doi.org/10.1080/10298430290029902a
   Google Scholar
• Tashman, L., Wang, L.B., and Thyagarajan, S., 2007. Microstructure characterization for modeling HMA behaviour using image technology. Road Materials and Pavement Design, 8 (2), 207–238. doi: https://doi.org/10.1080/14680629.2007.9690073
   Web of Science ®Google Scholar
• Wang, L.B., Frost, J.D., and Shashidhar, N., 2001. Microstructure study of WesTrack mixes from X-ray tomography images. In Transportation Research Record: Journal of the Transportation Research Board, No. 1767, Transportation Research Board of the National Academies, Washington, DC, 85–94.
   Google Scholar
• You, Z., Liu, Y., and Dai, Q., 2011. Three-dimensional microstructural-based discrete element viscoelastic modeling of creep compliance tests for asphalt mixtures. Journal of Materials in Civil Engineering, 23 (1), 79–87. doi: https://doi.org/10.1061/(ASCE)MT.1943-5533.0000038
   Web of Science ®Google Scholar
• Yue, Z.Q., Bekking, W., and Morin, I., 1995. Application of digital image processing to quantitative study of asphalt concrete microstructure. Transportation Research Record: Journal of the Transportation Research Board, 1492 (1), 53–60.
   Google Scholar
• Zhang, J.X., Zhang, J.H., and Wang, D.Z., 2005. Frost resistance of the low quality coarse-aggregate. Concrete, (8), 11–15.
   Google Scholar