Influence of Aggregate Motion Related to Rutting Depth of Asphalt Mixture Based on Intelligent Aggregate and DEM
Publication: Journal of Materials in Civil Engineering
Volume 36, Issue 5
Abstract
With the use of intelligent aggregate (IA) and discrete element method (DEM), a method was proposed to predict the influence of aggregate motion on the rutting depth in asphalt mixtures. The IAs were embedded in the center and side position of the specimen in a wheel tracking test, and the characteristics of IA motion parameters were compared with those obtained from virtual tests. The suitable motion factors for prediction model of rutting depth were first selected based on the trend of curve changes from the comparing results. Evaluation of the correlation between motion factors (Z-axis displacement and X-axis rotation angle of different IAs) and rutting depth of asphalt mixture was used to build the correlation matrix. Based on the high correlation coefficients, the curves of Z-axis displacement for No. 1 and No. 2 IA and X-axis rotation angle for No. 1 IA were further selected as the predicted factors, the prediction models of rutting depth were established. The feasibility of prediction models was verified by returning the IA motion data in indoor test and virtual test separately to observe the fitting degree between the actual curve and the prediction curve. It showed that the deviation of the prediction curve with the displacement factors was less than 4%, which was suitable to use as the predicted factors. On the other hand, due to the large fluctuation range of the rotation angle, the prediction curve with the rotation angle factor was more appropriate as a confidence curve to validate the prediction curve.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This material is based in part upon work supported by the National Natural Science Foundation of China (52008154), Hebei Science and Technology Department (E2021202074), and Special Funds for Jointly Building Colleges and Universities in Tianjin (280000-299).
References
ASTM. 2010. Stand test method for softening point of bitumen (ring-and-ball apparatus). ASTM D36. West Conshohocken, PA: ASTM.
ASTM. 2020. Standard test method for penetration of bituminous materials. ASTM D5. West Conshohocken, PA: ASTM.
ASTM. 2021a. Standard test method for density of semi-solid bituminous materials (pycnometer method). ASTM D70. West Conshohocken, PA: ASTM.
ASTM. 2021b. Standard test method for evaluating rubber property-retraction at lower temperatures (TR Test). ASTM D13. West Conshohocken, PA: ASTM.
Dan, H. C., D. Yang, X. Liu, A. P. Peng, and Z. Zhang. 2020. “Experimental investigation on dynamic response of asphalt pavement using SmartRock sensor under vibrating compaction loading.” Constr. Build. Mater. 247 (Jun): 118592. https://doi.org/10.1016/j.conbuildmat.2020.118592.
Feng, H., M. Pettinari, B. Hofko, and H. Stang. 2015. “Study of the internal mechanical response of an asphalt mixture by 3-D discrete element modeling.” Constr. Build. Mater. 77 (Feb): 187–196. https://doi.org/10.1016/j.conbuildmat.2014.12.022.
Gao, J. F., H. N. Wang, Y. Bu, Z. P. You, M. R. M. 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.
Gong, F. Y., R. Deng, Q. H. Wang, J. W. Bai, and X. J. Cheng. 2023. “A review on the simulation of aggregate morphologies in mixture performances based on discrete element method.” Constr. Build. Mater. 385 (Jul): 131522. https://doi.org/10.1016/j.conbuildmat.2023.131522.
Gong, F. Y., Y. Liu, X. D. Zhou, and Z. P. You. 2018a. “Lab assessment and discrete element modeling of asphalt mixture during compaction with elongated and flat coarse aggregates.” Constr. Build. Mater. 182 (Sep): 573–579. https://doi.org/10.1016/j.conbuildmat.2018.06.059.
Gong, F. Y., X. D. Zhou, Z. P. You, Y. Liu, and S. Y. Chen. 2018b. “Using discrete element models to track movement of coarse aggregates during compaction of asphalt mixture.” Constr. Build. Mater. 189 (Nov): 338–351. https://doi.org/10.1016/j.conbuildmat.2018.08.133.
Hu, J., P. F. Liu, D. W. Wang, and M. Oeser. 2018. “Influence of aggregates’ spatial characteristics on air-voids in asphalt mixture.” Road Mater. Pavement Des. 19 (4): 837–855. https://doi.org/10.1080/14680629.2017.1279072.
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.
Jin, C., X. D. Wan, P. F. Liu, X. Yang, and M. Oeser. 2021a. “Stability prediction for asphalt mixture based on evolutional characterization of aggregate skeleton.” Comput.-Aided Civ. Infrastruct. Eng. 36 (11): 1453–1466. https://doi.org/10.1111/mice.12742.
Jin, C., W. X. Zhang, P. F. Liu, X. Yang, and M. Oeser. 2021b. “Morphological simplification of asphaltic mixture components for micromechanical simulation using finite element method.” Comput.-Aided Civ. Infrastruct. Eng. 36 (11): 1435–1452. https://doi.org/10.1111/mice.12696.
Li, C., J. C. Li, Y. Q. Zhao, and L. Wang. 2023. “Study on high temperature creep properties and constitutive structure relation of composite polyphosphate modified asphalt mixes.” [In Chinese.] J. Munic. Technol. 41 (3): 1–6. https://doi.org/10.19922/j.1009-7767.2023.03.001.
Li, J. G., A. M. Sha, W. Jiang, Z. Z. Liu, M. Jia, and Z. Q. Han. 2022a. “Study on dynamic responses of particle in aggregate mixture during the laboratory compaction utilizing smart aggregate.” Constr. Build. Mater. 344 (Aug): 128156. https://doi.org/10.1016/j.conbuildmat.2022.128156.
Li, W., D. Wang, B. Chen, K. Hua, Z. Huang, C. Xiong, and H. Yu. 2022b. “Preparation of artificial pavement coarse aggregate using 3D printing technology.” Materials 15 (4): 1575. https://doi.org/10.3390/ma15041575.
Li, Y. J., and Z. H. Yue. 2022. “Research on asphalt mortar migration law under driving load based on discrete element method.” [In Chinese.] J. Munic. Technol. 40 (1): 48–53. https://doi.org/10.19922/j.1009-7767.2022.01.048.
Liu, S. S., H. Huang, T. Qiu, and L. Gao. 2017. “Comparison of laboratory testing using smartrock and discrete element modeling of ballast particle movement.” J. Mater. Civ. Eng. 29 (3): D6016001. https://doi.org/10.1061/(ASCE)MT.1943-5533.0001540.
Peng, Y., H. Gao, X. Y. Lu, and L. J. Sun. 2020. “Micromechanical discrete element modeling of asphalt mixture shear fatigue performance.” J. Mater. Civ. Eng. 32 (7): 04020183. https://doi.org/10.1061/(ASCE)MT.1943-5533.0003246.
Saleh, M., and M. Ghorban Ebrahimi. 2017. “Finite element modeling of permanent deformation in the loaded wheel tracker test.” Transp. Res. Rec. 2641 (1): 94–102. https://doi.org/10.3141/2641-12.
Singh, A. K., and J. P. Sahoo. 2021. “Rutting prediction models for flexible pavement structures: A review of historical and recent developments.” J. Traffic Transp. Eng. 8 (3): 315–338. https://doi.org/10.1016/j.jtte.2021.04.003.
Tan, Y. Q., Z. D. Liang, N. H. Xu, and C. Xing. 2022. “Research on rutting deformation monitoring method based on intelligent aggregate.” IEEE Trans. Intell. Transp. Syst. 23 (11): 22116–22126. https://doi.org/10.1109/TITS.2022.3175060.
Tong, J. S., T. Ma, K. R. Shen, H. Y. Zhang, and S. P. Wu. 2022. “A criterion of asphalt pavement rutting based on the thermal-visco-elastic-plastic model.” Int. J. Pavement Eng. 23 (4): 1134–1144. https://doi.org/10.1080/10298436.2020.1792470.
Van Staden, R. C., and S. Fragomeni. 2020. “Moisture damage in asphalt pavements at aggregate-asphalt interface finite element study.” In Proc., 25th Australasian Conf. on Mechanics of Structures and Materials 2020, 605–613. Singapore: Springer. https://doi.org/10.1007/978-981-13-7603-0_59.
Wang, H., Q. S. Zhang, and J. Q. Tan. 2009. “Investigation of layer contributions to asphalt pavement rutting.” J. Mater. Civ. Eng. 21 (4): 181–185. https://doi.org/10.1061/(ASCE)0899-1561(2009)21:4(181).
Wang, H., Z. H. Zhou, W. L. Huang, and X. Y. Dong. 2021. “Investigation of asphalt mixture permanent deformation based on three-dimensional discrete element method.” Constr. Build. Mater. 272 (Feb): 121808. https://doi.org/10.1016/j.conbuildmat.2020.121808.
Wang, X., S. H. Shen, H. Huang, and L. C. Almeida. 2018. “Characterization of particle movement in Superpave gyratory compactor at meso-scale using SmartRock sensors.” Constr. Build. Mater. 175 (Jun): 206–214. https://doi.org/10.1016/j.conbuildmat.2018.04.146.
Wang, X., S. H. Shen, H. Huang, and Z. D. Zhang. 2019. “Towards smart compaction: Particle movement characteristics from laboratory to the field.” Constr. Build. Mater. 218 (Sep): 323–332. https://doi.org/10.1016/j.conbuildmat.2019.05.122.
Xue, B., J. Xu, J. Z. Pei, J. P. Zhang, and R. Li. 2021. “Investigation on the micromechanical response of asphalt mixture during permanent deformation based on 3D virtual wheel tracking test.” Constr. Build. Mater. 267 (Jan): 121031. https://doi.org/10.1016/j.conbuildmat.2020.121031.
Yao, H., M. Xu, J. F. Liu, Y. Liu, J. Ji, and Z. P. You. 2022. “Literature review on the discrete element method in asphalt mixtures.” Front. Mater. 9 (Apr): 879245. https://doi.org/10.3389/fmats.2022.879245.
Zhang, C., and H. Wang. 2021. “A new method for compaction quality evaluation of asphalt mixtures with the intelligent aggregate (IA).” Materials 14 (9): 2422. https://doi.org/10.3390/ma14092422.
Zhang, C., and Z. W. Zhang. 2021. “Study on migratory behavior of aggregate in asphalt mixture based on the intelligent acquisition system of aggregate attitude data.” Sustainability 13 (6): 3053. https://doi.org/10.3390/su13063053.
Zhang, D. Y., L. H. Gu, and J. Q. Zhu. 2019a. “Effects of aggregate mesostructure on permanent deformation of asphalt mixture using three-dimensional discrete element modeling.” Materials 12 (21): 3601. https://doi.org/10.3390/ma12213601.
Zhang, J. P., X. Q. Li, W. S. Ma, and J. Z. Pei. 2019b. “Characterizing heterogeneity of asphalt mixture based on aggregate particles movements.” Iran. J. Sci. Technol. Trans. Civ. Eng. 43 (1): 81–91. https://doi.org/10.1007/s40996-018-0125-0.
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Published In
Journal of Materials in Civil Engineering
Volume 36 • Issue 5 • May 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Jun 24, 2023
Accepted: Oct 13, 2023
Published online: Feb 20, 2024
Published in print: May 1, 2024
Discussion open until: Jul 20, 2024
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