|
|
|
| Quantitative Characterization of 3D Road Aggregate Morphology |
| LI Luo-ke1, LIU Hai-ming1, ZHANG Zhen-guo2, CAO Peng3, YAN Yuan4 |
1. Faculty of Architecture and Civil Engineering, Kunming University of Science and Technology, Kunming Yunnan 650500, China;
2. The 41st Institute of the Fourth Academy of CASC, National Key Laboratory of Combustion, low and Thermo-structure, Xi'an Shaanxi 710072, China;
3. College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China;
4. Highway Science and Technology Research Institute of Yunnan Province, Kunming Yunnan 650000, China |
|
|
|
|
Abstract This study quantitatively analyzed the shape, angularity, and roughness of road aggregate particles. A contactless three-dimensional (3D) scanning technique was used to capture the 3D coordinate data of point clouds on an aggregate surface. The data were then used to reconstruct 3D elevation digital models of aggregate particles. Six independent feature parameters were subsequently used as an evaluation index to quantitatively describe the multilevel features of the 3D morphology of road aggregates. The methods for calculating and analyzing the feature parameters on the basis of the cloud data of the aggregate scanning point were also presented. The 3D morphologies of four types of road aggregates were studied. On the basis of the results, an aggregate polishing testing system was developed, and the practicability of the 3D roughness coefficient index was demonstrated accordingly. Results show that (1) the sphericity index can describe the compactness of aggregate shape, (2) the shape factor index can describe the needle-flake properties of aggregates, (3) the ellipsoid index can evaluate the sharp edges and corners of aggregates, (4) the maximum surface curvature can be used to identify the local angular features of particles, (5) the two-dimensional roughness index can be used to analyze the anisotropic characteristics of the surface profiles of aggregates, and (6) the 3D roughness index is suitable for evaluating the roughness of aggregate surface texture at the mesoscopic level. Under the experimental conditions of this study, the shape and angular features of aggregate particles matched the requirements of road performance. This result benefitted the formation of an aggregate skeleton structure in asphalt concrete with S>0.76, SF of 0.80-1.20, and E of 0.79-0.88. The aggregate texture was uneven, and the physical adsorption between the asphalt and the aggregates on the contact surface was relatively high when JRC3D ≥ 11.0.
|
|
Received: 15 October 2020
|
| Fund:Supported by the National Natural Science Fund (No.51708267); the National Key Research and Development Plan of the 13th Five-Year Plan (No.2017YFC0804601) |
|
Corresponding Authors:
LI Luo-ke
E-mail: Locke@kust.edu.cn
|
|
|
|
[1] WANG Wen-zhen, SHEN Ai-qin, GUO Yin-chuan, et al. Shape Feature Parameters and Distribution Rule of Coarse Aggregate Based on Image Analysis[J]. Journal of Highway and Transportation Research and Development, 2019, 37(1):25-31. (in Chinese)
[2] YOU Zhi-cheng, WANG Liang-qing, YANG Yan-xia, et al. Anisotropic Research on Shear Strength Parameters of Discontinuity Based on Three-Dimensional Laser Scanning Technology[J]. Chinese Journal of Rock Mechanics and Engineering, 2014, 33(S1):3003-3008. (in Chinese)
[3] FENG Qi-bo, XIE Fang, ZHANG Bin. Optical Measurement Technology and Application[M]. Beijing:Tsinghua University Press, 2008. (in Chinese)
[4] LARKIN K G. Efficien Tnonlinear Algorithm for Envelope Detection in White Lighti Nterferometry[J]. Journal of the Optical Society of America A, 1996, 13(4):832-843.
[5] HIRABAYASHI A, OGAWA H KITAGAWA K. Fast Surface Profiler by White-Light Interferometry by Use of A New Algorithm Based on Sampling Theory[J]. Applied Optics, 2002, 41(23):4876-4883.
[6] TANG Zhi-rong, LIU Ming-zhe, JIANG Yue, et al. Point Cloud Registration Algorithm Based on Canonical Correlation Analysis[J]. Chinese Journal of Lasers, 2019, 46(4):173-181. (in Chinese)
[7] CUI Xin, YAN Xiu-tian, LI Shi-peng. Feature Preserving Scattered Point Cloud Denoising[J]. Opticsand Precision Engineering 2017, 25(12):3169-3178. (in Chinese)
[8] DING Han, ZHU Li-min, XIONG Zhen-hua. Survey on Coordinate Measurement, Geometric Modeling and RP or NC Code Generation from Measured Data Points[J]. Chinese Journal of Mechanical Engineering, 2003, 039(11):28-37. (in Chinese)
[9] 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. (in Chinese)
[10] WANG Wei, DUAN Hu-rong, ZHANG De-cheng, et al. A Method for Solving the Volume and Surface Area of Irregular Body after Three-dimensional Laser Scanning[J]. Geomatics & Spatial Information Technology, 2019, 42(8):172-175. (in Chinese)
[11] JIN Can, WANG Pei-song, YANG Xu, et al. Analysis on Gradation Parameters of Asphalt Mixture Based on 3D Virtual Measurement[J]. Journal of Highway and Transportation Research and Development, 2019, 36(8):1-8. (in Chinese)
[12] GENG Chao. Quantitative Evaluation of Morphological Feature of Aggregate Based on Image Processing[J]. Journal of Highway and Transportation Research and Development, 2018, 35(12):42-47. (in Chinese)
[13] FU Ru, HU Xin-li, ZHOU Bo, et al. A Quantitative Characterization Method of 3D Morphology of Sand Particles[J]. Rock and Soil Mechanics, 2018, 39(2):483-490. (in Chinese)
[14] BARTON N, CHOUBEY V. The Shear Strength of Rock Joints in Theory and Practice[J]. Rock Mechanics, 1977, 10(12):1-54.
[15] TSE R, CRUDEN D M. Estimating Joint Roughness Coefficients[J]. International Journal of Rock Mechanics and Mining Sciences and Geomechanics Abstracts, 1979, 16(5):303-307.
[16] CHEN Shi-jiang, ZHU Wan-cheng, WANG Chuang-ye, et al. Review of Research Progresses of the Quantifying Joint Roughness Coefficients[J]. Chinese Journal of Theoretical and Applied Mechanics, 2017, 49(2):239-256. (in Chinese)
[17] BELEM T, HOMAND-ETIENNE F, SOULEY M. Quantitative Parameters for Rock Joint Surface Roughness[J]. Rock Mechanics and Rock Engineering, 2000, 33(4):217-242.
[18] POWERS M C. A New Roundness Scale for Sedimentary Particles[J].Journal of Sedimentary Research,1953,23(2):117-119.
[19] LI Yan, JIN Zhen-kui, JIN Ting, et al. Geological Significance of Magmatic Gravel Roundness[J]. Acta Sedimentologica Sinica, 2014, 32(2):189-197. (in Chinese)
[20] DONG Wen-jiao. Resaerch on the Effect of Aggregate Morphology on Affnity Between Bitumen and Aggregate[D].Yangzhou:Yangzhou University, 2013. (in Chinese) |
|
|
|
2021, Vol. 15 
