Technical Notes
Aug 21, 2018

Evaluation of Susceptibility of High-Temperature Performance of Asphalt Mixture to Morphological Feature of Aggregates by Fractal Theory

Publication: Journal of Materials in Civil Engineering
Volume 30, Issue 11

Abstract

Morphological characteristics of aggregates have been regarded as a significant factor related to the high-temperature performance of asphalt mixtures. Fractal theory was used to calculate the fractal dimension to evaluate the morphological characteristics of aggregates. Dynamic creep test was selected to estimate the high-temperature performance of asphalt mixtures in terms of gradation types, nominal maximum aggregates sizes (NMAS), asphalt binders, and gyration levels. For each of these factors, correlation analysis between high-temperature indicators and fractal dimension was conducted. The results indicate that the flow number (FN) Index, that is, the ratio of maximum microstrain to flow number, is well-correlated with the fractal dimensions of asphalt mixtures in terms of gradation types and NMAS. Strain rate was a more comprehensive indicator linked with the morphologies of aggregates. According to fractal analysis, the specimen of AC-13 revealed optimal high-temperature resistance in terms of morphology. The AC-13 mixture with 75 gyrations had the largest value of fractal dimension and exhibited the best high-temperature performance. In addition, fractal dimensions measured by box-counting and sandbox methods were well-correlated with indicators of high-temperature ability; box-counting presented advantages for computing the fractal dimension of asphalt mixture.

Get full access to this article

View all available purchase options and get full access to this article.

References

AASHTO. 2009. Standard method of test for determining the dynamic modulus and flow number for hot mix asphalt (HMA) using the asphalt mixture performance tester (AMPT). AASHTO TP79. Washington, DC: AASHTO.
Castillo, D., S. Caro, M. Darabi, and E. Masad. 2017. “Influence of aggregate morphology on the mechanical performance of asphalt mixtures.” Road Mater. Pavement Des. 19 (4): 1–20. https://doi.org/10.1080/14680629.2017.1283357.
Chen, J., H. Li, L. Wang, J. Wu, and X. Huang. 2015. “Micromechanical characteristics of aggregate particles in asphalt mixtures.” Constr. Build. Mater. 91: 80–85. https://doi.org/10.1016/j.conbuildmat.2015.05.076.
Coenen, A. R., M. E. Kutay, N. R. Sefidmazgi, and H. U. Bahia. 2012. “Aggregate structure characterisation of asphalt mixtures using two-dimensional image analysis.” Road Mater. Pavement Des. 13 (3): 433–454. https://doi.org/10.1080/14680629.2012.711923.
Gama, D. A., J. M. Rosa, T. J. A. de Melo, and J. K. G. Rodrigues. 2016. “Rheological studies of asphalt modified with elastomeric polymer.” Constr. Build. Mater. 106: 290–295. https://doi.org/10.1016/j.conbuildmat.2015.12.142.
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 (1–2): 665–676. https://doi.org/10.1617/s11527-015-0528-3.
Hou, Y., Y. Huang, F. Sun, and M. Guo. 2016. “Fractal analysis on asphalt mixture using a two-dimensional imaging technique.” Adv. Mater. Sci. Eng. 2016 (2): 1–7. https://doi.org/10.1155/2016/8931295.
Jiang, J., F. Ni, L. Gao, and L. Yao. 2017a. “Effect of the contact structure characteristics on rutting performance in asphalt mixtures using 2D imaging analysis.” Constr. Build. Mater. 136: 426–435. https://doi.org/10.1016/j.conbuildmat.2016.12.210.
Jiang, J., F. Ni, L. Yao, and X. Cui. 2017b. “Evaluating the mastic distribution of asphalt mixtures based on a new thickness threshold using 2D image planers.” Road Mater. Pavement Des. 19 (6): 1–14. https://doi.org/10.1080/14680629.2017.1323001.
Lee, C., and T. A. Kramer. 2004. “Prediction of three-dimensional fractal dimensions using the two-dimensional properties of fractal aggregates.” Adv. Colloid Interface Sci. 112 (1–3): 49–57. https://doi.org/10.1016/j.cis.2004.07.001.
Li, J., Q. Du, and C. Sun. 2009. “An improved box-counting method for image fractal dimension estimation.” Pattern Recognit. 42 (11): 2460–2469. https://doi.org/10.1016/j.patcog.2009.03.001.
Liu, J., R. Jiang, J. Sun, P. Shi, and Y. Yang. 2017a. “Concrete damage evolution and three-dimensional reconstruction by integrating CT test and fractal theory.” J. Mater. Civ. Eng. 29 (9): 04017122. https://doi.org/10.1061/(ASCE)MT.1943-5533.0001932.
Liu, P., J. Hu, D. Wang, M. Oeser, S. Alber, W. Ressel, and G. Canon Falla. 2017b. “Modelling and evaluation of aggregate morphology on asphalt compression behavior.” Constr. Build. Mater. 133: 196–208. https://doi.org/10.1016/j.conbuildmat.2016.12.041.
Liu, T., X.-N. Zhang, Z. Li, and Z.-Q. Chen. 2014. “Research on the homogeneity of asphalt pavement quality using X-ray computed tomography (CT) and fractal theory.” Constr. Build. Mater. 68: 587–598. https://doi.org/10.1016/j.conbuildmat.2014.06.046.
Lopes, R., and N. Betrouni. 2009. “Fractal and multifractal analysis: A review.” Med. Image Anal. 13 (4): 634–649. https://doi.org/10.1016/j.media.2009.05.003.
Ma, T., D. Zhang, Y. Zhang, and J. Hong. 2016a. “Micromechanical response of aggregate skeleton within asphalt mixture based on virtual simulation of wheel tracking test.” Constr. Build. Mater. 111: 153–163. https://doi.org/10.1016/j.conbuildmat.2016.02.104.
Ma, X., Q. Li, Y.-C. Cui, and A.-Q. Ni. 2016b. “Performance of porous asphalt mixture with various additives.” Int. J. Pavement Eng. 19 (4): 1–7. https://doi.org/10.1080/10298436.2016.1175560.
Nejad, F. M., H. Sorkhabi, and M. M. Karimi. 2016. “Experimental investigation of rest time effect on permanent deformation of asphalt concrete.” J. Mater. Civ. Eng. 28 (5): 06015016. https://doi.org/10.1061/(ASCE)MT.1943-5533.0001498.
Souza, L. T., Y. R. Kim, F. V. Souza, and L. S. Castro. 2012. “Experimental testing and finite-element modeling to evaluate the effects of aggregate angularity on bituminous mixture performance.” J. Mater. Civ. Eng. 24 (3): 249–258. https://doi.org/10.1061/(ASCE)MT.1943-5533.0000386.
Tan, Y., L. Zhang, and H. Chu. 2015. “New index used to evaluate the high-temperature and low-temperature performance of asphalt.” J. Mater. Civ. Eng. 27 (8): C4014007. https://doi.org/10.1061/(ASCE)MT.1943-5533.0001201.
Wang, H., Y. Bu, Y. Wang, X. Yang, and Z. You. 2016. “The effect of morphological characteristic of coarse aggregates measured with fractal dimension on asphalt mixture’s high-temperature performance.” Adv. Mater. Sci. Eng. 2016 (1787): 1–9. https://doi.org/10.1155/2016/6264317.
Zhang, J., A. E. Alvarez, S. I. Lee, A. Torres, and L. F. Walubita. 2013. “Comparison of flow number, dynamic modulus, and repeated load tests for evaluation of HMA permanent deformation.” Constr. Build. Mater. 44: 391–398. https://doi.org/10.1016/j.conbuildmat.2013.03.013.

Information & Authors

Information

Published In

Go to Journal of Materials in Civil Engineering
Journal of Materials in Civil Engineering
Volume 30Issue 11November 2018

History

Received: Dec 23, 2017
Accepted: May 14, 2018
Published online: Aug 21, 2018
Published in print: Nov 1, 2018
Discussion open until: Jan 21, 2019

Permissions

Request permissions for this article.

Authors

Affiliations

Ph.D. Student, School of Transportation, Southeast Univ., Nanjing, Jiangsu 210096, P.R. China. Email: [email protected]
Qiao Dong, Ph.D. [email protected]
Professor, School of Transportation, Southeast Univ., Nanjing, Jiangsu 210096, P.R. China. Email: [email protected]
Fujian Ni, Ph.D. [email protected]
Professor, School of Transportation, Southeast Univ., Nanjing, Jiangsu 210096, P.R. China (corresponding author). Email: [email protected]
Jiwang Jiang [email protected]
Ph.D. Student, School of Transportation, Southeast Univ., Nanjing, Jiangsu 210096, P.R. China. Email: [email protected]
Master Student, School of Transportation, Southeast Univ., Nanjing, Jiangsu 210096, P.R. China. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share