Mesogenetic Evaluation and Design of Coarse Aggregate Contact within Asphalt Mixture
Publication: Journal of Materials in Civil Engineering
Volume 34, Issue 8
Abstract
To establish a new gene database and asphalt mixture evaluation method, coarse aggregate contact characteristics from the meso perspective serve as a reference for the improvement of fine design and asphalt mixture performance. In this study, a rapid analysis and evaluation software for coarse aggregate contact software was developed. An optimization calculation method for voids in coarse aggregate of asphalt mixture was proposed based on digital image processing techniques. In addition, the meso characteristic gene of coarse aggregate contact for eight different asphalt mixtures was investigated, and the relationship between coarse aggregate contact mesogenetic parameters and the corresponding macrorutting resistance was established. The results indicate that number of contact points is not appropriate as the mesoparameter for evaluating the skeleton of the asphalt mixture; average coordination number, skeleton ratio, and “free” coarse aggregate content can be used to evaluate the mesostructure of the asphalt mixture. Skeleton ratio is the most sensitive mesogenetic parameter affecting rut depth, which can be used as the main control parameter for fine design of asphalt mixture. The limit standards of the skeleton ratio and “free” coarse aggregate content values are 41.32% and 82.89%, respectively, and the range of average coordination numbers is 0.5–1.72. However, the mesodesign parameters cannot reach the standard theoretical value due to the inhomogeneous granular material characteristics of the asphalt mixture. In the asphalt mixture design process, average coordination number is , skeleton ratio is , and “free” coarse aggregate content is ; these values can be used as the mesoparameter standard for the fine design of skeleton asphalt mixtures.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
This work was supported by Foshan Land Sea Smart Civil Engineering Material Technology R&D Centre, Special Funded Project of Guangdong Enterprise Science and Technology Special Commissioner in 2020 (Grant No. GDKTP2020036600), Science and Technology Innovation Platform of Foshan City, Guangdong Province, China (Grant No. 2016AG100341), and Natural Science Foundation of Guangdong Province (Sequence No. 2214050007315). The authors thank the editor and anonymous reviewers for their constructive comments and valuable suggestions to improve the quality of the article.
References
Anton, D. P., and P. B. William. 2019. “A review of X-ray computed tomography of concrete and asphalt construction materials.” Constr. Build. Mater. 199 (Feb): 637–651. https://doi.org/10.1016/j.conbuildmat.2018.12.049.
Cai, X., L. Chen, R. D. Zhang, K. Wu, and X. Ye. 2020. “Estimation of shear modulus of asphalt mixture based on the shear strength of the aggregate interface.” Constr. Build. Mater. 248 (Jul): 118695. https://doi.org/10.1016/j.conbuildmat.2020.118695.
Cao, W. D., S. T. Liu, Z. C. Xue, L. C. Chen, and Z. D. Zhang. 2021. “Laboratory method to characterize coarse aggregate segregation for HMA.” J. Mater. Civ. Eng. 33 (1): 04020412. https://doi.org/10.1061/(ASCE)MT.1943-5533.0003522.
Chao, X., Y. Q. Tan, K. Zhang, L. Y. Shan, and H. N. Xu. 2020. “Review on the genome system of asphalt mixture and its relationship with performance.” [In Chinese.] China J. Highway Transp. 33 (10): 76–90. https://doi.org/10.19721/j.cnki.1001-7372.2020.10.003.
Coenen, A. R., M. E. Kutay, N. R. Sefidmazgi, and H. U. Bahia. 2012. “Aggregate structure characterization of asphalt mixtures using 2-Dimensional image analysis.” Road Mater. Pavement Des. 13 (3): 433–454. https://doi.org/10.1080/14680629.2012.711923.
Ding, X. H., T. Ma, and W. Gao. 2017. “Morphological characterization and mechanical analysis for coarse aggregate skeleton of asphalt mixture based on discrete-element modeling.” Constr. Build. Mater. 154 (Nov): 1048–1061. https://doi.org/10.1016/j.conbuildmat.2017.08.008.
Dong, Z. J., Z. Y. Liu, C. Yang, and X. B. Gong. 2020. “Viscosity characterization of confined bitumen considering microaggregate-bitumen interactions.” Comput.-Aided Civ. Infrastruct. Eng. 35 (11): 1261–1275. https://doi.org/10.1111/mice.12562.
Elseifi, M. A., I. L. Al-Qadi, S. H. Yang, and S. H. Carpenter. 2008. “Validity of asphalt binder film thickness concept in hot-mix asphalt.” Transp. Res. Rec. 2057 (1): 37–45. https://doi.org/10.3141/2057-05.
Gao, J. F., H. N. Wang, Y. Bu, Z. P. You, M. R. Mohd Hasan, and M. Irfan. 2018. “Effects of coarse aggregate angularity on the microstructure of asphalt mixture.” Constr. Build. Mater. 183 (Sep): 472–484. https://doi.org/10.1016/j.conbuildmat.2018.06.170.
Gao, X. W., Z. P. Fan, J. P. Zhang, and S. W. Liu. 2017. “Micromechanical model for asphalt mixture coupling inter-particle effect and imperfect interface.” Constr. Build. Mater. 148 (Sep): 696–703. https://doi.org/10.1016/j.conbuildmat.2017.05.015.
Georgiou, P., L. Sideris, and A. Loizos. 2015. “Evaluation of the effects of gyratory and field compaction on asphalt mix internal structure.” Mater. Struct. 49 (1): 665–676. https://doi.org/10.1617/s11527-015-0528-3.
Jiang, J. W., F. J. Ni, Q. Dong, L. Y. Yao, and X. Ma. 2019. “Investigation of the internal structure change of two-layer asphalt mixtures during the wheel tracking test based on 2D image analysis.” Constr. Build. Mater. 209 (Jun): 66–76. https://doi.org/10.1016/j.conbuildmat.2019.02.156.
Jiang, J. W., F. J. Ni, and L. Gao. 2017. “Effect of the contact structure characteristics on rutting performance in asphalt mixtures using 2D imaging analysis.” Constr. Build. Mater. 136 (Apr): 426–435. https://doi.org/10.1016/j.conbuildmat.2016.12.210.
Jiang, J. W., Z. Zhang, Q. Dong, and F. J. Ni. 2018. “Characterization and identification of asphalt mixtures based on convolutional neural network methods using X-ray scanning images.” Constr. Build. Mater. 174 (Jun): 72–80. https://doi.org/10.1016/j.conbuildmat.2018.04.083.
Khalilitehrani, M., S. Sasic, and A. Rasmuson. 2018. “Characterization of force networks in a dense high-shear system.” Particuology 38 (Jun): 215–221. https://doi.org/10.1016/j.partic.2017.11.001.
Kim, H., C. T. Haas, A. F. Rauch, and C. Browne. 2003. “3D image segmentation of aggregates from laser profiling.” Comput.-Aided Civ. Infrastruct. Eng. 18 (4): 254–263. https://doi.org/10.1111/1467-8667.00315.
Kutay, M. E., E. Arambula, N. Gibson, and J. Youtcheff. 2010. “Three-dimensional image processing methods to identify and characterise aggregates in compacted asphalt mixtures.” Int. J. Pavement Eng. 11 (6): 511–528. https://doi.org/10.1080/10298431003749725.
Leon, L. P., and D. Gay. 2019. “Gene expression programming for evaluation of aggregate angularity effects on permanent deformation of asphalt mixtures.” Constr. Build. Mater. 211 (Jun): 470–478. https://doi.org/10.1016/j.conbuildmat.2019.03.225.
Li, J. G., P. L. Li, J. F. Su, Y. Xue, and W. Y. Rao. 2019. “Effect of aggregate contact characteristics on densification properties of asphalt mixture.” Constr. Build. Mater. 204 (Apr): 691–702. https://doi.org/10.1016/j.conbuildmat.2019.01.023.
Li, T. S., P. F. Liu, C. Du, M. Schnittcher, J. Hu, D. W. Wang, and M. Oeser. 2020. “Microstructural analysis of the effects of compaction on fatigue properties of asphalt mixtures.” Int. J. Pavement Eng. 23 (1): 9–20. https://doi.org/10.1080/10298436.2020.1728532.
Liu, W. D., and Y. Gao. 2016. “Discrete element modeling of migration and evolution rules of coarse aggregates in the static compaction process.” [In Chinese.] J. Southeast Univ. 32 (1): 85–92. https://doi.org/10.3969/j.issn.1003-7985.2016.01.015.
Ma, T., D. Y. Zhang, Y. Zhang, S. Q. Wang, and X. M. Huang. 2018. “Simulation of wheel tracking test for asphalt mixture using discrete element modeling.” Road Mater. Pavement Des. 19 (2): 367–384. https://doi.org/10.1080/14680629.2016.1261725.
Masad, E., and J. W. Button. 2020. “Unified imaging approach for measuring aggregate angularity and texture.” Comput.-Aided Civ. Infrastruct. Eng. 15 (4): 273–280. https://doi.org/10.1111/0885-9507.00191.
Masad, E., B. Muhunthan, N. Shashidhar, and T. Harman. 1999. “Internal structure characterization of asphalt concrete using image analysis.” J. Comput. Civ. Eng. 13 (2): 88–95. https://doi.org/10.1061/(ASCE)0887-3801(1999)13:2(88).
MGI Strategic Plan. 2014. “National science and technology council.” Accessed December 1, 2014. https://www.nist.gov/system/files/documents/2018/06/26/mgi_strategic_plan_-_dec_2014.pdf.
Ministry of Transport. 2011. Standard test methods of bitumen and bituminous mixtures for highway engineering. Beijing: Ministry of Transport.
Polaczyk, P., X. Shu, H. R. Gong, and B. S. Huang. 2019. “Influence of aggregates angularity on the locking point of asphalt mixtures.” Road Mater. Pavement Des. 20 (1): 183–195. https://doi.org/10.1080/14680629.2019.1588151.
Pouranian, M. R., and J. E. Haddock. 2018. “Determination of voids in the mineral aggregate and aggregate skeleton characteristics of asphalt mixtures using a linear-mixture packing model.” Constr. Build. Mater. 188 (Nov): 292–304. https://doi.org/10.1016/j.conbuildmat.2018.08.101.
Shahrour, I., and W. G. Zhang. 2021. “Use of the soft computing techniques for tunneling optimization of tunnel boring machines.” Undergr. Space 6 (3): 233–239. https://doi.org/10.1016/j.undsp.2019.12.001.
Shi, L. W., D. Y. Wang, C. N. Jin, B. Li, and H. H. Liang. 2020a. “Measurement of coarse aggregates movement characteristics within asphalt mixture using digital image processing methods.” Measurement 163 (Oct): 107948. https://doi.org/10.1016/j.measurement.2020.107948.
Shi, L. W., D. Y. Wang, P. H. Lin, X. L. Sun, and X. Qin. 2021. “Meso-structural evaluation of asphalt mixture based on pore cellular structure model.” Int. J. Pavement Eng. 2021 (Jan): 1–14. https://doi.org/10.1080/102984362020.1869236.
Shi, L. W., D. Y. Wang, X. Xiao, and X. Qin. 2020b. “Meso-structural characteristics of asphalt mixture main skeleton based on meso-scale analysis.” Constr. Build. Mater. 232 (Jan): 117263. https://doi.org/10.1016/j.conbuildmat.2019.117263.
Sobol, I. M. 2001. “Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates.” Math. Comput. Simul. 55 (1): 271–280. https://doi.org/10.1016/S0378-4754(00)00270-6.
Vadooda, M., M. S. Joharia, and A. R. Rahaei. 2014. “Introducing a simple method to determine aggregate gradation of hot mix asphalt using image processing.” Int. J. Pavement Eng. 15 (2): 142–150. https://doi.org/10.1080/10298436.2013.786076.
Wang, D. M., and Y. H. Zhou. 2010. “Statistics of contact force network in dense granular matter.” Particuology 8 (2): 133–140. https://doi.org/10.1016/j.partic.2009.09.007.
Wollny, I., F. Hartung, M. Kaliske, P. Liu, M. Ouser, D. Wang, G. C. Falla, S. Leischner, and F. Wellner. 2020. “Coupling of microstructural and macrostructural computational approaches for asphalt pavements under rolling tire load.” Comput.-Aided Civ. Infrastruct. Eng. 35 (11): 1178. https://doi.org/10.1111/mice.12535.
Xing, C., H. N. Xu, Y. Q. Tan, X. Y. Liu, C. H. Zhou, and T. Scarpas. 2019. “Gradation measurement of asphalt mixture by X-ray CT images and digital image processing methods.” Measurement 132 (Jan): 377–386. https://doi.org/10.1016/j.measurement.2018.09.066.
Yao, H., Q. L. Dia, Z. P. You, J. X. Zhang, S. T. Lv, and X. H. Xiao. 2018. “Evaluation of contact angle between asphalt binders and aggregates using molecular dynamics (MD) method.” Constr. Build. Mater. 212 (Jul): 727–736. https://doi.org/10.1016/j.conbuildmat.2019.03.283.
Yuan, G. A., X. J. Li, P. W. Hao, D. W. Li, J. L. Pan, and A. G. Li. 2020. “Application of flat-joint contact model for uniaxial compression simulation of large stone porous asphalt mixes.” Constr. Build. Mater. 238 (Mar): 117695. https://doi.org/10.1016/j.conbuildmat.2019.117695.
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Journal of Materials in Civil Engineering
Volume 34 • Issue 8 • August 2022
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© 2022 American Society of Civil Engineers.
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Received: Aug 3, 2021
Accepted: Dec 27, 2021
Published online: May 26, 2022
Published in print: Aug 1, 2022
Discussion open until: Oct 26, 2022
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