Research on Characteristics of Macrotexture for Colored Anti-Skid Coating on Pavement Based on Fractal Theory

Abstract

A type of colored anti-skid coating was prepared to improve the anti-skid performance of pavement, as described in this paper, and the composition of the colored anti-skid coating was determined by laboratory tests. The image-processing techniques in MATLAB and fractal theory were used to analyze the macrotexture characteristics of colored anti-skid coating surfaces. Four different particle sizes were used for specimen preparation, with diameters of 1 mm, 2 mm, 3 mm, and 4 mm. The three-dimensional (3D) macrotexture structure model was constructed based on shape from shading (SFS) theory. The anti-skid performance of the coating assessed by the British pendulum number (BPN) correlates with the fractal dimension. The result shows that when the particle size is the same, the more the spraying amount of anti-skid particles, the larger the fractal dimension. There are different optimal spraying amounts (OSA) for the maximum fractal dimension at each particle size. Meanwhile, when the particle size increases from 1 mm to 4 mm at the OSA, the fractal dimension decreases from 2.719 to 2.492 and the BPN gradually increases from 75 to 86, and the colored anti-skid coating shows good anti-skid performance improvement. In addition, the fractal dimension has a negative correlation with the BPN, and the correlation coefficient R² between the fractal and the BPN is 0.95074, which indicates that the fractal dimension can reflect the complexity of the macrotexture and characterize the anti-skid performance of the coating under certain conditions. This research helps to provide an effective method to evaluate the macrotexture characteristics of colored anti-skid coating.

Keywords

infrastructure materials asphalt mixture evaluation and performance skid and friction resistance pavements pavement condition evaluation three-dimensional 3D pavement structural testing and evaluation layers structures testing and evaluation of transportation structures pavement texture

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References

Wang

Xiao

Guo

Preparation and Evaluation of Durability of Color Antiskid Pavement Particles Subjected to Different Treatments. Journal of Materials in Civil Engineering, Vol. 32, No. 1, 2020, p. 04019336.

Zhong

Mechanical Properties Test of Nano Modified Coating Material for Color Antiskid Pavement. In IOP Conference Series: Earth and Environmental Science, Vol. 186, No. 2, IOP Publishing, September, 2018, p. 012060.

Chen

H. Q.

HAO

P. W.

Performance Evaluation on Thin-Layer Antiskid Pavement Material. Journal of PLA University of Science and Technology (Natural Science Edition), Vol. 10, No. 6, 2009, pp. 565–569.

Sakai

S. I.

Sado

Hori

Dynamic Driving/Braking Force Distribution in Electric Vehicles With Independently Driven Four Wheels. Electrical Engineering in Japan, Vol. 138, No. 1, 2002, pp. 79–89.

Edmondson

Woodward

Lim

Kane

Martin

Shyha

Improved Non-Contact 3D Field and Processing Techniques to Achieve Macrotexture Characterisation of Pavements. Construction and Building Materials, Vol. 227, 2019, p. 116693.

Ejsmont

J. A.

Ronowski

Świeczko-Żurek

Sommer

Road Texture Influence on Tyre Rolling Resistance. Road Materials and Pavement Design, Vol. 18, No. 1, 2017, pp. 181–198.

Miao

Song

Gong

Fractal and Multifractal Characteristics of 3D Asphalt Pavement Macrotexture. Journal of Materials in Civil Engineering, Vol. 26, No. 8, 2014, p. 04014033.

Zhang

Liu

Chen

Research on Skid Resistance of Asphalt Pavement Based on Three-Dimensional Laser-Scanning Technology and Pressure-Sensitive Film. Construction and Building Materials, Vol. 69, 2014, pp. 49–59.

Amarasiri

Gunaratne

Sarkar

Use of Digital Image Modeling for Evaluation of Concrete Pavement Macrotexture and Wear. Journal of Transportation Engineering, Vol. 138, No. 5, 2012, pp. 589–602.

10.

Y. Q.

Luo

L. B.

Zhu

Z. F.

Nie

Zhang

Y. G.

Zeng

L. H.

Zhang

C. Y.

Wang

Jiang

High-Speed Ultraviolet-Visible-Near Infrared Photodiodes Based on p-ZnS Nanoribbon–n-Silicon Heterojunction. CrystEngComm, Vol. 15, No. 8, 2013, pp. 1635–1642.

11.

Y. L.

Chen

H. Q.

Hao

Z. H.

Pavement Antiskid Treatment of Chongqing Tongyu Tunnel. Technocogy of Highway and Transport, Vol. 3, 2005, pp. 52–54.

12.

Thanakumar

Murugappriya

Suresh

G. R.

High Density Impulse Noise Removal Using BDND Filtering Algorithm. In 2014 International Conference on Communication and Signal Processing, Melmaruvathur, India, IEEE, New York, April, 2014, pp. 1958–1962.

13.

Frankot

R. T.

Chellappa

A Method for Enforcing Integrability in Shape From Shading Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 10, No. 4, 1988, pp. 439–451.

14.

Cryer

J. E.

Tsai

P. S.

Shah

Integration of Shape From Shading and Stereo. Pattern Recognition, Vol. 28, No. 7, 1995, pp. 1033–1043.

15.

Liu

Wang

Chen

A Spherical Conformal Contact Model Considering Frictional and Microscopic Factors Based on Fractal Theory. Chaos, Solitons & Fractals, Vol. 111, 2018, pp. 96–107.

16.

Qing-Quan

Analysis of Tribological Property of Pavement Stone. China Journal of Highway and Transport, Vol. 3, 2004, pp. 19–22.

17.

Kokkalis

A. G.

Tsohos

G. H.

Panagouli

O. K.

Consideration of Fractals Potential in Pavement Skid Resistance Evaluation. Journal of Transportation Engineering, Vol. 128, No. 6, 2002, pp. 591–595.

18.

Wang

Chen

S. Y.

Evaluation of Durability Against Sliding on the Asphalt Mix Fractal Theory. Science Technology and Engineering, Vol. 31, 2014, pp. 302–307.

19.

Luo

Jin

Wei

Cai

An Analysis of Fractal Dimension and Tortuosity Based on 2D Numerical Reconstruction Model of Reservoir Rocks. Interpretation, Vol. 7, No. 4, 2019, pp. SJ1–SJ6.

20.

Koepfler

Lopez

Morel

J. M.

A Multiscale Algorithm for Image Segmentation by Variational Method. SIAM Journal on Numerical Analysis, Vol. 31, No. 1, 1994, pp. 282–299.

21.

Sarkar

Chaudhuri

B. B.

An Efficient Differential Box-Counting Approach to Compute Fractal Dimension of Image. IEEE Transactions on Systems, Man, and Cybernetics, Vol. 24, No. 1, 1994, pp. 115–120.

22.

Yang

Y. C.

Peng

R. D.

Zhou

H. W.

Computation of Fractal Dimension for Digital Image in a 3D Space. Journal of China University of Mining & Technology, Vol. 2, 2009, pp. 251–258.

23.

Wang

J. J.

X. P.

Roughness and Fractal Dimension of Polished Granite Surface and Their Relationship. Acta Metrologica Sinica, Vol. 2, 2007.

24.

Ergun

Iyinam

A. F.

Prediction of Road Surface Friction Coefficient Using Only Macro- and Microtexture Measurements. Journal of Transportation Engineering, Vol. 131, No. 4, 2005, pp. 311–319.