Influence of different sources of microstructural heterogeneity on the degradation of asphalt mixtures

References

• Abbas, A., et al., 2007. Micromechanical modeling of the viscoelastic behavior of asphalt mixtures using the discrete-element method. International Journal of Geomechanics, 7 (2), 131–139.10.1061/(ASCE)1532-3641(2007)7:2(131)
   Google Scholar
• Adhikari, S. and You, Z., 2010. 3D discrete element models of the hollow cylindrical asphalt concrete specimens subject to the internal pressure. International Journal of Pavement Engineering, 11 (5), 429–439.10.1080/10298436.2010.489114
   Web of Science ®Google Scholar
• Allison, J., 2011. Integrated computational materials engineering: a perspective on progress and future steps. The Journal of The Minerals, Metals & Materials Society, 63 (4), 15–18.
   Google Scholar
• Al-Rousan, T., et al., 2005. New methodology for shape classification of aggregates. Transportation Research Record: Journal of the Transportation Research Board, 1913, 11–23.10.3141/1913-02
   Google Scholar
• Aragão, F.T.S., et al., 2015. A novel methodology to generate and analyze virtual microstructures of asphalt concrete mixtures. In: T.R. Board, ed. TRB 94th Annual Meeting. Washington, DC. Available from: http://trid.trb.org/view.aspx?id=1337772.
   Google Scholar
• Arambula, E., Caro, S. and Masad, E., 2010. Experimental measurement and numerical simulation of water vapor diffusion through asphalt pavement materials. Journal of Materials in Civil Engineering, 22 (6), 588–598.10.1061/(ASCE)MT.1943-5533.0000059
   Web of Science ®Google Scholar
• Arambula, E., Masad, E. and Martin, A., 2007. Influence of air void distribution on the moisture susceptibility of asphalt mixes. Journal of Materials in Civil Engineering, 19, 655–664.10.1061/(ASCE)0899-1561(2007)19:8(655)
   Web of Science ®Google Scholar
• Ban, H., Kim, Y.-R. and Rhee, S.-K., 2013. Computational microstructure modeling to estimate progressive moisture damage behavior of asphaltic paving mixtures. International Journal for Numerical and Analytical Methods in Geomechanics, 37, 2005–2020.10.1002/nag.v37.13
   Web of Science ®Google Scholar
• Caro, S., et al., 2008a. Probabilistic analysis of fracture in asphalt mixtures caused by moisture damage. Transportation Research Record: Journal of the Transportation Research Board, 2057, 28–36.10.3141/2057-04
   Web of Science ®Google Scholar
• Caro, S., et al., 2008b. Moisture susceptibility of asphalt mixtures, Part 1: mechanisms. International Journal of Pavement Engineering, 9 (2), 81–98.10.1080/10298430701792128
   Google Scholar
• Caro, S., et al., 2010. Probabilistic modeling of the effect of air voids on the mechanical performance of asphalt mixtures subjected to moisture diffusion. Journal of the Association of Asphalt Paving Technologists (AAPT), 79, 221–252.
   Google Scholar
• Caro, S., et al., 2011. Stochastic micromechanical model of the deterioration of asphalt mixtures subject to moisture diffusion processes. International Journal for Numerical and Analytical Methods in Geomechanics, 35, 1079–1097.10.1002/nag.v35.10
   Web of Science ®Google Scholar
• Castillo, D. and Caro, S., 2014. Probabilistic modeling of air void variability of asphalt mixtures in flexible pavements. Construction and Building Materials, 61, 138–146.10.1016/j.conbuildmat.2014.02.075
   Web of Science ®Google Scholar
• Castillo, D., et al., 2015. Studying the effect of microstructural properties on the mechanical degradation of asphalt mixtures. Construction and Building Materials, 93, 70–83.10.1016/j.conbuildmat.2015.05.108
   Web of Science ®Google Scholar
• Castillo, D., et al., 2016. Modelling moisture-mechanical damage in asphalt mixtures using random microstructures and a continuum damage formulation. Road Materials and Pavement Design, Accepted for publication. doi:10.1080/14680629.2016.1138880.
   Google Scholar
• Chen, J., Wang, H. and Li, L., 2015. Virtual testing of asphalt mixture with two-dimensional and three-dimensional random aggregate structures. International Journal of Pavement Engineering. doi:10.1080/10298436.2015.1066005.
   Google Scholar
• Coleri, E., et al., 2012. Development of a micromechanical finite element model from computed tomography images for shear modulus simulation of asphalt mixtures. Construction and Building Materials, 30, 783–793.10.1016/j.conbuildmat.2011.12.071
   Web of Science ®Google Scholar
• Dai, Q., 2011. Two- and three-dimensional micromechanical viscoelastic finite element modeling of stone-based materials with X-ray computed tomography images. Construction and Building Materials, 25 (2), 1102–1114.10.1016/j.conbuildmat.2010.06.066
   Web of Science ®Google Scholar
• Dai, Q. and You, Z., 2008. Micromechanical finite element framework for predicting viscoelastic properties of asphalt mixtures. Materials and Structures, 41, 1025–1037.10.1617/s11527-007-9303-4
   Web of Science ®Google Scholar
• Darabi, M., Abu Al-Rub, R. and Little, D., 2012. A continuum damage mechanics framework for modeling micro-damage healing. International Journal of Solids and Structures, 49, 492–513.10.1016/j.ijsolstr.2011.10.017
   Web of Science ®Google Scholar
• Darabi, M., et al., 2011. A thermo-viscoelastic–viscoplastic–viscodamage constitutive model for asphaltic materials. International Journal of Solids and Structures, 48, 191–207.10.1016/j.ijsolstr.2010.09.019
   Web of Science ®Google Scholar
• Darabi, M., et al., 2013. Constitutive modeling of fatigue damage response of asphalt concrete materials with consideration of micro-damage healing. International Journal of Solids and Structures, 50 (19), 2901–2913.10.1016/j.ijsolstr.2013.05.007
   Web of Science ®Google Scholar
• El-Kadi, A.I. and Williams, S.A., 2000. Generating two-dimensional fields of autocorrelated, normally distributed parameters by the matrix decomposition technique. Ground Water, 38 (4), 530–532.10.1111/gwat.2000.38.issue-4
   Web of Science ®Google Scholar
• Grenfell, J., Apeagyei, A. and Airey, G., 2015. Moisture damage assessment using surface energy, bitumen stripping and the SATS moisture conditioning procedure. International Journal of Pavement Engineering, 16 (5), 411–431.10.1080/10298436.2015.1007235
   Web of Science ®Google Scholar
• Kassem, E., et al., 2008. Evaluation of full-depth asphalt pavement construction using X-Ray computed tomography and ground penetrating radar. Journal of Performance of Constructed Facilities, 22 (6), 408–416.10.1061/(ASCE)0887-3828(2008)22:6(408)
   Web of Science ®Google Scholar
• Kassem, E., et al., 2009. Measurements of the moisture diffusion coefficient of asphalt mixtures and its relationship to mixture composition. International Journal of Pavement Engineering, 10 (6), 389–399.10.1080/10298430802524792
   Web of Science ®Google Scholar
• Kringos, N., Scarpas, A. and Debondt, A., 2008. Determination of moisture susceptibility of mastic-stone bond strength and comparison to thermodynamical properties. Journal of the Association of Asphalt Paving Technologists (AAPT), 77, 475–478.
   Google Scholar
• Lea, J.D. and Harvey, J.T., 2014. Using spatial statistics to characterise pavement properties. International Journal of Pavement Engineering. 16 (3), 239–255. doi:10.1080/10298436.2014.942856.
   Web of Science ®Google Scholar
• Lea, J.D. and Harvey, J.T., 2015. A spatial analysis of pavement variability. International Journal of Pavement Engineering, 16 (3), 256–267.10.1080/10298436.2014.942857
   Web of Science ®Google Scholar
• Lua, Y.J. and Sues, R.H., 1996. Probabilistic finite-element analysis of airfield pavements. Transportation Research Record: Journal of the Transportation Research Board, 1540, 29–38.10.3141/1540-05
   Google Scholar
• Masad, E., Castelblanco, A., and Birgisson, B., 2006. Effects of air void size distribution, pore pressure, and bond energy on moisture damage. Journal of Testing and Evaluation, 34 (1), 1–9.
   Web of Science ®Google Scholar
• Masad, E., et al., 2001. Correlation of fine aggregate imaging shape indices with asphalt mixture performance. Transportation Research Record: Journal of the Transportation Research Board, 1757, 148–156.10.3141/1757-17
   Web of Science ®Google Scholar
• Mehrez, L., et al., 2015. Stochastic identification of linear-viscoelastic models of aged and unaged asphalt mixtures. Journal of Materials in Civil Engineering, 27 (4), 04014149.10.1061/(ASCE)MT.1943-5533.0001103
   Google Scholar
• Rahmani, E., et al., 2015. Constitutive modeling of coupled chemo-viscoelastic response of asphalt concrete. Submitted and under evaluation.
   Google Scholar
• Schapery, R.A., 1969. Further development of a thermodynamic constitutive theory: stress formulation West Lafayette IN: Purdue University, Purdue Research Foundation.
   Google Scholar
• Shakiba, M., et al., 2013. Continuum coupled moisture-mechanical damage model for asphalt concrete. Transportation Research Record: Journal of the Transportation Research Board, 2372 (1), 72–82.10.3141/2372-09
   Web of Science ®Google Scholar
• Shakiba, M., et al., 2014. Microstructural modeling of asphalt concrete using a coupled moisture-mechanical constitutive relationship. International Journal of Solids and Structures, 51 (25–26), 4260–4279.10.1016/j.ijsolstr.2014.08.012
   Web of Science ®Google Scholar
• Shakiba, M., et al., 2015. Three-dimensional microstructural modelling of coupled moisture–mechanical response of asphalt concrete. International Journal of Pavement Engineering, 16 (5), 445–466.10.1080/10298436.2015.1007239
   Web of Science ®Google Scholar
• Stuedlein, A.W., et al., 2012. Geotechnical characterization and random field modeling of desiccated clay. Journal of Geotechnical and Geoenvironmental Engineering, 138 (11), 1301–1313.10.1061/(ASCE)GT.1943-5606.0000723
   Web of Science ®Google Scholar
• Tashman, L., et al., 2001. Internal structure analysis of asphalt mixes to improve the simulation of superpave gyratory compaction to field conditions. Asphalt paving technology, 70, 605–645.
   Google Scholar
• Terrel, R.L. and Al-Swailmi, S., 1993. The role of pessimum voids concept in understanding moisture damage to asphalt concrete mixtures. Transportation Research Record: Journal of the Transportation Research Board, 1386, 31–37.
   Google Scholar
• Tong, Y., Luo, R., and Lytton, R.L., 2015. Moisture and aging damage evaluation of asphalt mixtures using the repeated direct tensional test method. International Journal of Pavement Engineering, 16 (5), 397–410.10.1080/10298436.2015.1007234
   Web of Science ®Google Scholar
• Vanmarcke, E., 1983. Random fields: analysis and synthesis. Cambridge, MA: MIT Press.
   Google Scholar
• Vasconcelos, K.L., et al., 2011. Experimental measurement of water diffusion through fine aggregate mixtures. Journal of Materials in Civil Engineering, 23 (4), 445–452.10.1061/(ASCE)MT.1943-5533.0000190
   Web of Science ®Google Scholar
• Wang, Z.M., Kwan, A.K.H., and Chan, H.C., 1999. Mesoscopic study of concrete I: generation of random aggregate structure and finite element mesh. Computers and Structures, 70, 533–544.10.1016/S0045-7949(98)00177-1
   Web of Science ®Google Scholar
• Wang, Y., et al., 2007. Noninvasive measurement of three-dimensional permanent strains in asphalt concrete with X-ray tomography imaging. Transportation Research Record: Journal of the Transportation Research Board, 2005, 95–103.10.3141/2005-11
   Web of Science ®Google Scholar
• You, Z., Adhikari, S., and Kutay, E., 2009. Dynamic modulus simulation of the asphalt concrete using the X-ray computed tomography images. Materials and Structures, 42, 617–630.10.1617/s11527-008-9408-4
   Web of Science ®Google Scholar
• You, T., et al., 2012. Three-dimensional microstructural modeling of asphalt concrete using a unified viscoelastic–viscoplastic–viscodamage model. Construction and Building Materials, 28, 531–548.10.1016/j.conbuildmat.2011.08.061
   Web of Science ®Google Scholar
• Zelelew, H. and Papagiannakis, A.T., 2011. A volumetrics thresholding algorithm for processing asphalt concrete X-ray CT images. International Journal of Pavement Engineering, 12 (6), 543–551.10.1080/10298436.2011.561345
   Web of Science ®Google Scholar