A comprehensive particle packing-based design of bituminous mixtures and its mechanical characterisation

References

• AASHTO:T19M, 2015. Standard method of test for bulk density (“unit weight”) and voids in aggregate. Washington, DC: American Association of State Highway and Transportation Officials.
   Google Scholar
• AASHTO:T378, 2017. Standard method of test for determining the dynamic modulus and flow number for asphalt mixtures using the asphalt mixture performance tester (AMPT). Washington, DC: American Association of State Highway and Transportation Officials.
   Google Scholar
• Apeagyei, A.K., 2011. Rutting as a function of dynamic modulus and gradation. Journal of Materials in Civil Engineering, 23 (9), 1302–1310. https://doi.org/10.1061/(ASCE)MT.1943-5533.0000309.
   Web of Science ®Google Scholar
• ASTM:D6925, 2015. Standard test method for preparation and determination of the relative density of asphalt mix specimens by means of the superpave gyratory compactor. West Conshohocken, PA, USA.
   Google Scholar
• Blazejowski, K., 2016. Stone matrix asphalt. Boca Raton: CRC Press, FL. https://doi.org/10.1201/b10285.
   Google Scholar
• Booij, H.C., and Thoone, G., 1982. Generalization of Kramers–Kronig transforms and some approximations of relations between viscoelastic quantities. Rheologica Acta, 21, 15–24. https://doi.org/10.1007/bf01520701.
   Web of Science ®Google Scholar
• Cooper, S.B., et al., 2014. Balanced asphalt mixture design through specification modification: Louisiana's experience. Transportation Research Record, 2447 (1), 92–100. https://doi.org/10.3141/2447-10.
   Web of Science ®Google Scholar
• Coree, B.J., and Hislop, W.P., 1999. Difficult nature of minimum voids in the mineral aggregate: historical perspective. Transportation Research Record, 1681, 148–156. https://doi.org/10.3141/1681-18.
   Google Scholar
• de Larrard, F., 1999. Concrete mixture proportioning: a scientific approach. London, New York: E & FN Spon.
   Google Scholar
• de Larrard, F., and Sedran, T., 1994. Optimization of ultra-high-performance concrete by the use of a packing model. Cement and Concrete Research, 24 (6), 997–1009. https://doi.org/10.1016/0008-8846(94)90022-1.
   Web of Science ®Google Scholar
• Deepa, S., Saravanan, U., and Murali Krishnan, J., 2019. On measurement of dynamic modulus for bituminous mixtures. International Journal of Pavement Engineering, 20 (9), 1073–1089. https://doi.org/10.1080/10298436.2017.1380809.
   Web of Science ®Google Scholar
• Fuller, W.B., and Thompson, S.E., 1907. The laws of proportioning concrete. Transactions of the American Society of Civil Engineers, 57 (2), 67–143.
   Google Scholar
• IS73, 2018. Indian standard paving bitumen – specification, fourth revision. New Delhi, India: Bureau of Indian Standards.
   Google Scholar
• Janmejaya, B., Abhijith, B.S., and Krishnan, J.M., 2021. Influence of confinement pressure and rest periods on measurement of dynamic modulus of bituminous mixtures. Journal of Materials in Civil Engineering, 33 (9), Article ID 04021253. https://doi.org/10.1061/(asce)mt.1943-5533.0003854.
   Web of Science ®Google Scholar
• Kumar, S.V., and Santhanam, M., 2003. Particle packing theories and their application in concrete mixture proportioning: a review. Indian Concrete Journal, 77 (9), 1324–1331.
   Google Scholar
• Lees, G., 1970. The rational design of aggregate gradings for dense asphaltic compositions. Proceedings of Association of Asphalt Paving Technologists, 39, 60–97.
   Google Scholar
• Lira, B., Jelagin, D., and Birgisson, B., 2013. Gradation-based framework for asphalt mixture. Materials and Structures, 46 (8), 1401–1414.
   Web of Science ®Google Scholar
• Liu, H., Luo, R., and Lv, H., 2018. Establishing continuous relaxation spectrum based on complex modulus tests to construct relaxation modulus master curves in compliance with linear viscoelastic theory. Construction and Building Materials, 165, 372–384.
   Web of Science ®Google Scholar
• Mandelbrot, B.B., 1983. The fractal geometry of nature. New York: Freeman and Company.
   Google Scholar
• MATLAB, 2021. MATLAB version 9.11.0.1751886 (R2021b). Natick, MA: The Mathworks, Inc.
   Google Scholar
• MoRTH, 2013. Specification for road and bridge works, fifth revision. New Delhi, India: Ministry of Road Transport and Highways, Indian Roads Congress.
   Google Scholar
• MS-2, 2014. Asphalt mix design methods. Manual Series No.02. USA: Asphalt Institute.
   Google Scholar
• National Academics of Sciences, Engineering, and Medicine, 2011. A manual for design of hot-mix asphalt with commentary. Washington, DC: The National Academic Press. https://doi.org/10.17226/14524.
   Google Scholar
• NCAT, 2017. Moving towards balanced mix design for asphalt mixtures. Available from: http://www.eng.auburn.edu/research/centers/ncat/newsroom/2017-spring/balanced-mix.html [Accessed 1 November 2021].
   Google Scholar
• Olard, F., and Perraton, D., 2010. On the optimization of the aggregate packing characteristics for the design of high-performance asphalt concretes. Road Materials and Pavement Design, 11 (Suppl. 1), 145–169.
   Google Scholar
• Orbey, N., and Dealy, J.M., 1991. Determination of the relaxation spectrum from oscillatory shear data. Journal of Rheology, 35 (6), 1035–1049. https://doi.org/10.1122/1.550164.
   Web of Science ®Google Scholar
• Pasetto, M., and Baldo, N., 2014. Influence of the aggregate skeleton design method on the permanent deformation resistance of stone mastic asphalt. Materials Research Innovations, 18 (Suppl. 3), S3-96–S3-101.
   Google Scholar
• Powers, T.C., 1968. The properties of fresh concrete. New York: John Wiley and Sons.
   Google Scholar
• Roquier, G., 2016. The 4-parameter compressible packing model (CPM) including a new theory about wall effect and loosening effect for spheres. Powder Technology, 302, 247–253. https://doi.org/10.1016/j.powtec.2016.08.031.
   Web of Science ®Google Scholar
• Roquier, G., 2019. A theoretical packing density model (TPDM) for ordered and disordered packings. Powder Technology, 344, 343–362. https://doi.org/10.1016/j.powtec.2018.12.033.
   Web of Science ®Google Scholar
• Roy, N., Veeraragavan, A., and Krishnan, J.M., 2016. Influence of confinement pressure and air voids on the repeated creep and recovery of asphalt concrete mixtures. International Journal of Pavement Engineering, 17 (2), 133–147. https://doi.org/10.1080/10298436.2014.925622.
   Web of Science ®Google Scholar
• Shanbhag, S., 2019. pyReSpect: a computer program to extract discrete and continuous spectra from stress relaxation experiments. Macromolecular Theory and Simulations, 28 (3), 1900005. https://doi.org/10.1002/mats.201900005.
   Web of Science ®Google Scholar
• Stadler, F.J., 2013. On the usefulness of rheological spectra–a critical discussion. Rheologica Acta, 52 (1), 85–89. https://doi.org/10.1007/s00397-012-0664-4.
   Web of Science ®Google Scholar
• Stadler, F.J., and Mahmoudi, T., 2011. Understanding the effect of short-chain branches by analyzing viscosity functions of linear and short-chain branched polyethylenes. Korea–Australia Rheology Journal, 23 (4), 185–193. https://doi.org/10.1007/s13367-011-0023-5.
   Web of Science ®Google Scholar
• Stovall, T., de Larrard, F., and Buil, M., 1986. Linear packing density model of grain mixtures. Powder Technology, 48 (1), 1–12. https://doi.org/10.1016/0032-5910(86)80058-4.
   Web of Science ®Google Scholar
• Takeh, A., and Shanbhag, S., 2013. A computer program to extract the continuous and discrete relaxation spectra from dynamic viscoelastic measurements. Applied Rheology, 23 (2), Article ID 24628. https://doi.org/10.3933/applrheol-23-24628.
   Web of Science ®Google Scholar
• Vavrik, W., et al., 2002. Method summarized for gradation selection in hot-mix asphalt design. Transportation Research Circular E-C044. Washington, DC: TRB, National Research Council.
   Google Scholar
• West, R., et al., 2018. Development of a framework for balanced mix design. NCHRP Project Report. Auburn: National Center for Asphalt Technology at Auburn University.
   Google Scholar
• Wong, V., and Kwan, A.K.H., 2014. A 3-parameter model for packing density prediction of ternary mixes of spherical particles. Powder Technology, 268, 357–367. https://doi.org/10.1016/j.powtec.2014.08.036.
   Web of Science ®Google Scholar
• Yuan, G., et al., 2020. Optimization design and verification of large stone porous asphalt mixes gradation using compressible packing model. Construction and Building Materials, 230, Article ID 116903. https://doi.org/10.1016/j.conbuildmat.2019.116903.
   Web of Science ®Google Scholar