CUI Zhe, ZHANG Sheng-rui. Computational method of 3D aggregate angularity based on CT images[J]. Journal of Traffic and Transportation Engineering, 2017, 17(5): 39-49.
Citation: CUI Zhe, ZHANG Sheng-rui. Computational method of 3D aggregate angularity based on CT images[J]. Journal of Traffic and Transportation Engineering, 2017, 17(5): 39-49.

Computational method of 3D aggregate angularity based on CT images

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  • Author Bio:

    CUI Zhe(1978-), male, senior engineer, doctoral student, 723648316@qq.com

    ZHANG Sheng-rui(1961-), male, professor, PhD, 723648316@qq.com

  • Received Date: 2017-06-08
  • Publish Date: 2017-10-25
  • To improve the evaluation accuracy of aggregate angularity, a computational method of3 D aggregate angularity was put forward.Based on CT technology and 3 D reconstruction technology, image intensification and sharpen filter were used to clearly display the aggregates in aggregate CT images, and the gray thresholds of enhanced CT images were calculated and divided.MIMICS was used to reconstruct the 3 D models of aggregates in Marshal specimens.The roughness degree and sphericity degree of aggregate were put forward and taken as evaluation indexes to evaluate aggregate angularity based on the 3 D model.The influence factorsof 3 D model reconstruction were analyzed.Computational result shows the gray values of aggregate, asphalt and pore in AC-16 Marshall specimens are 101.32-170.14, 4.32-101.32, and0-4.32, respectively, so, image intensification and sharpen filter can clearly display aggregates in CT images and improve the 3 Dreconstruction accuracy of aggregate.The computational standard deviation of sphericity degrees is 0.000 7 when the CT images are dealt with by 2 pixels×2 pixels and 3 pixels×3 pixels sharpen filters, and the standard deviation of sphericity degrees is 0.042 3 when the CT images are dealt with by 5 pixels×5 pixels, 6 pixels×6 pixels and 7 pixels×7 pixels sharpen filters.Therefore, 2 pixels×2 pixels or 3 pixels×3 pixels sharpen filter should be adopted to dealt with the CT images in order to ensure the low fluctuation of computed sphericity degree.When sampling point densities are 50 and 70 per cubic millimeter, the standard deviation of roughness degrees is 0.001 6, but when sampling point densities are 5, 15 and 25 per cubic millimeter, the standard deviation of roughness degrees is 0.034 9, so, the density range of sampling points in CT images should be 50-70 per cubic millimeter to ensure that the 3 D models can reflect the real shapes of aggregates precisely.The standard deviations of 2 D sphericity degrees and roughness degrees based on 5 CT cross sections are 0.012 1-0.048 2, which reflects the larger variability and deviation.However, the roughness degrees of aggregates 1-5 calculated by the method based on the 3 D models are 0.991 2, 1.032 1, 0.974 2, 1.075 1, 1.043 2, respectively, and the corresponding average 2 Droughness degrees of aggregates 1-5 are 0.994 1, 1.023 9, 0.988 3, 1.097 5 and 1.060 8, respectively, which shows the 3 Dand 2 Droughness degrees are basically same.Obviously, the computational method based on the 3 D model used to calculate the roughness degree and sphericity degree fully considers the 3 D angularity of aggregate, the calculation result is not affected by the selected CT cross sections, and there are no calculation variability and deviation.

     

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