Estimation of aggregate gradation from partial gradation information obtained by multiple imaging equipment

References

• Adhikari, S., You, Z., & Peterson, K. (2013). Multi-phase characterization of asphalt concrete using X-ray microfluorescence. International Journal of Pavement Research and Technology, 6(2), 117–122.
   Google Scholar
• Al-Thyabat, S., & Miles, N. J. (2006). An improved estimation of size distribution from particle profile measurements. Powder Technology, 166(3), 152–160.
   Web of Science ®Google Scholar
• ASTM D6926. (2010). Standard practice for preparation of bituminous specimens using Marshall apparatus. West Conshohocken, PA: ASTM.
   Google Scholar
• Chermant, J. L., Chermant, L., Coster, M., Dequidet, A. S., & Redon C. (2001). Some fields of applications of automatic image analysis in civil engineering. Cement and Concrete Composites, 23(2–3), 157–169.
   Web of Science ®Google Scholar
• Coenen, A. R., Kutay, M. E., Sefidmazgi, N. R., & Bahia, H. U. (2012). Aggregate structure characterization of asphalt mixtures using two-dimensional image analysis. Road Materials and Pavement Design, 13(3), 433–454.
   Web of Science ®Google Scholar
• Fernlund, J. M. R. (2005). Image analysis method for determining 3-D size distribution of coarse aggregates. Bulletin of Engineering Geology and Environment, 64(2), 159–166.
   Web of Science ®Google Scholar
• Fernlund, J. M. R., Robert, W. Z., & Kragic, D. (2007). Influence of volume/mass on grain-size curves and conversion of image-analysis size to sieve size. Engineering Geology, 90(3–4), 124–137.
   Web of Science ®Google Scholar
• Gopalkrishnan, K., Ceylan, H., & Inanc, F. (2007). Using X-ray computed tomography to study paving materials. Proceedings of the Institution of Civil Engineers—Construction Materials, 160(1), 15–23.
   Google Scholar
• Guo, Q., Bian, Y., Li, L., Jiao, Y., Tao, J., & Xiang, C. (2015). Stereological estimation of aggregate gradation using digital image of asphalt mixture. Construction and Building Materials, 94, 458–466.
   Web of Science ®Google Scholar
• Hassan, N. A., Airey, G. D., Khan, R., & Collop, A. C. (2011). Nondestructive characterization of the effect of asphalt mixture compaction on aggregate orientation an segregation using X-ray computed tomography. International Journal of Pavement Research and Technology, 5(2), 84–92.
   Google Scholar
• Igathinathane, C., Pordesimo, L. O., Columbus, E. P., Batchelo, W. D., & Methuku, S. R. (2008). Shape identification and particle size distribution from basic shape parameters using ImageJ. Computers and Electronics in Agriculture, 63, 168–182.
   Web of Science ®Google Scholar
• Kuity, A. (2017). Studies on effect of distribution of aggregates on the mechanical response of asphalt mix (PhD thesis, submitted). Department of Civil Engineering, IIT Kanpur.
   Google Scholar
• Kuity, A., & Das, A. (2015). Homogeneity of filler distribution within asphalt mix- a microscopic study. Construction and Building Materials, 95, 497–505.
   Web of Science ®Google Scholar
• Kuity, A., & Das, A. (2016). Study on aggregate size distribution in asphalt mix using images obtained by different imaging techniques. Transportation Research Procedia, 17, 340–348.
   Google Scholar
• Kumara, G. H. A. J. J., Hayano, K., & Ogiwara, K. (2012). Image analysis techniques on evaluation of particle size distribution of gravel. International Journal of Geo-mate, 3(1), 290–297.
   Google Scholar
• Kwan, A. K. H., Mora, C. F., & Chan, H. C. (1999). Particle shape analysis of coarse aggregate using digital image processing. Cement and Concrete Research, 29, 1403–1410.
   Web of Science ®Google Scholar
• Latham, J. P., Munjiza, A., Garcia, X., Xiang, J., & Guises, R. (2008). Three-dimensional particle shape acquisition and use of shape library for DEM and FEM/DEM simulation. Minerals Engineering, 21(11), 797–805.
   Web of Science ®Google Scholar
• Lee, J. R. J., Smith, M. L., & Smith, L. N. (2007). A new approach to the three-dimensional quantification of angularity using image analysis of the size and form of coarse aggregates. Engineering Geology, 91, 254–264.
   Web of Science ®Google Scholar
• Marinono, N., Pavese, A., Foi, M., & Trombino, L. (2005). Characterization of mortar morphology in thin sections by digital image processing. Cement and Concrete Research, 35, 1613–1619.
   Web of Science ®Google Scholar
• Masad, E., Muhunthan, B., Shashidhar, N., & Harman, T. (1999). Internal structure characterization of asphalt concrete using image analysis. Journal of Computing in Civil Engineering, 13(2), 88–95.
   Web of Science ®Google Scholar
• MATLAB and Image Processing Toolbox Release. (2010). The MathWorks Inc. Natick, MA: Author.
   Google Scholar
• Mora, C. F., Kwan, A. K. H., & Chan, H. C. (1998). Particle size distribution analysis of coarse aggregate using digital image processing. Cement and Concrete Research, 28(2), 921–932.
   Google Scholar
• MORT&H (Ministry of Road Transport and Highway). (2013). Specifications for Road and Bridge works. Indian Road Congress. 5th Revision. New Delhi, India: Author.
   Google Scholar
• Pirard, E., Vergara, N., & Chapeau, V. (2004). Direct estimation of sieve size distributions from 2-D image analysis of sand particles. Paper presented at Proceeding of International Congress for Particle Technology, Nuremberg, Germany. Retrieved from https://orbi.ulg.ac.be/bitstream/2268/12635/1/PARTEC2004%20P516.pdf
   Google Scholar
• Underwood, E. E. (1970). Quantitative stereology. Reading, MA: Addison-Wesley Publishing Company.
   Google Scholar
• Underwood, B. S., & Kim, Y.R. (2013). Microstructural investigation of asphalt concrete for performing multiscale experimental studies. International Journal of Pavement Engineering, 14(5), 498–516.
   Web of Science ®Google Scholar
• Wang, L. B., Frost, J. D., & Lai, J. S. (2004). Three dimensional digital representation of granular material microstructure from X-ray tomography imaging. Journal of Computing in Civil Engineering, 18(1), 28–35.
   Web of Science ®Google Scholar
• Wang, L., Jin-Young, P., & Fu, Y. (2007). Representation of real particles for DEM simulation using X-ray tomography. Construction and Building Materials, 21(2), 338–346.
   Web of Science ®Google Scholar
• Wang, Y., Wang, L., Harman, T., & Li, Q. (2007). Non-invasive measurement of three dimensional permanent strains in asphalt concrete with X-ray tomography imaging. Transportation Research Record 2005 (pp. 95–103). Washington, DC.
   Google Scholar
• Wu, W., Wang, D., & Zhang, X. (2011). Estimating the gradation of asphalt mixtures using X-ray computerized tomography and stereology method. Road Materials and Pavement Design, 12(3), 699–710.
   Web of Science ®Google Scholar
• Wu, W., Wang, D., Zhang, X., & Li, Z. (2010). Analyzing the gradation of asphalt mixtures based on industrial computerized tomography. International Journal of Pavement Research and Technology, 3(1), 51–55.
   Google Scholar
• Yue, Z. Q., Bekking, W., & Morin, I. (1995). Application of digital image processing to quantitatively study of asphalt concrete microstructure. Transportation Research Record, 1492: 53–60.
   Google Scholar
• Yue, Z. Q., & Morin, I. (1996). Digital image processing for aggregate orientation in asphalt concrete mixtures. Canadian Journal of Civil Engineering, 23(2), 480–489.
   Web of Science ®Google Scholar
• Zelelew, H. M., Almuntashri, A., Agaian, S., & Papagiannakis, A. T. (2013). An image proved image processing technique for asphalt concrete X-ray CT images. Road Materials and Pavement Design, 14(2), 341–359.
   Web of Science ®Google Scholar
• Zelelew, H. M., Papagiannakis, A. T., & Masad, E. (2008). Application of digital image processing techniques for asphalt concrete mixture images. Paper presented at 12th International Conference of International Association for Computer Methods and Advances in Geo-Mechanics (pp. 119–124), Goa, India.
   Google Scholar