Technical Papers
Sep 23, 2017

Computational Analysis of Thermal Conductivity of Asphalt Mixture Using Virtually Generated Three-Dimensional Microstructure

Publication: Journal of Materials in Civil Engineering
Volume 29, Issue 12

Abstract

This study developed computational models for virtually generating three-dimensional (3D) random asphalt mixture microstructure (3D RAMM) using a Voronoi diagram, and analyzed the thermal conductivity of heterogeneous microstructure. The mixture was simulated as a three-phase composite material including fine aggregate matrix (FAM), coarse aggregate, and air void. The 3D RAMM was generated considering different morphological characteristics (size distribution, sphericity, orientation) of the dispersed phases (coarse aggregate and air void) using virtual sieve analysis and an innovative shrinking algorithm. Finite-element (FE) modeling of the steady heat transfer process was used to calculate the effective thermal conductivity of an asphalt mixture. The thermal simulation results were validated with experiment data reported in the literature. The results show that the heat flux in the asphalt mixture is not uniformly distributed. The sphericity and the orientation angle of the dispersed phase have a combined effect on the effective thermal conductivity of asphalt mixture. The developed computational model provides an effective way to analyze the microstructure effect on the bulk properties of composite materials.

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Acknowledgments

This work was financially supported by the China Natural Science Foundation (51278518), the China Civil Aviation Science and Technology Innovation Fund (MHRD20140215), and the Project of Six Talent Peaks in Jiangsu Province (1150140005).

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Go to Journal of Materials in Civil Engineering
Journal of Materials in Civil Engineering
Volume 29Issue 12December 2017

History

Received: Sep 15, 2016
Accepted: May 24, 2017
Published online: Sep 23, 2017
Published in print: Dec 1, 2017
Discussion open until: Feb 23, 2018

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Authors

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Associate Professor, Intelligent Transportation System Research Center of Southeast Univ., Nanjing 210096, China (corresponding author). E-mail: [email protected]
Hao Wang, M.ASCE [email protected]
Associate Professor, Dept. of Civil and Environmental Engineering, Rutgers, State Univ. of New Jersey, Piscataway, NJ 08854. E-mail: [email protected]
Zhongshan Ren [email protected]
Ph.D. Student, Intelligent Transportation System Research Center of Southeast Univ., Nanjing 210096, China. E-mail: [email protected]

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