J. Cent. South Univ. (2013) 20: 520–527

DOI: 10.1007/s11771-013-1514-y

Evaluation of surface textures and skid resistance of pervious concrete pavement

CHEN Yu(陈瑜)¹, WANG Ke-jin(王科进)², ZHOU Wen-fang(周文芳)¹

1. School of Traffic and Transportation Engineering, Changsha University of Science & Technology,Changsha 410004, China;

2. Department of Civil, Construction and Environmental Engineering, Iowa State University, Ames IA50010, USA

Central South University Press and Springer-Verlag Berlin Heidelberg 2013

Abstract: Surface textures had long been recognized as primary factors to provide the skid resistance on pavements; however, no measurement of skid resistance on pervious concrete pavement with various surface texture parameters had been made. Fractal geometry was introduced in the present work to accurately simulate transect contour curves of pervious concrete specimens through fractal interpolation. It is proved that its fractal dimension (D) can be adopted to measure the skid resistance on pervious concrete pavement, overcoming the shortcomings of both macrotexture depth (D_T) and British portable pendulum number (N_BP). Combined with Fujikawa-Koike tire/road contact model, the optimization method of all surface textures was recommended for designing and constructing excellently skid-resistant and noise-absorptive pervious concrete pavement. In addition, evaluating of the abrasion process and attenuation of the surface textures on concrete pavement slabs was also the focus of this work based on accelerated abrasion test. Results show that the surface textures on pervious concrete pavement slabs is extremely durable, compared to those on conventional grooved or exposed aggregate concrete pavement slabs.

Key words: pervious concrete; surface texture; skid resistance; fractal dimension; abrasion

1 Introduction

In recent years, rapid abrasion of the skid-resistant textures on conventional concrete pavements by moving tires, especially on such roads as long precipitous slope sections, parking lots, within tunnels, as well as poor skid resistance of wet asphalt pavement had been reported [1–3]. Compared to asphalt pavement, concrete pavement had been proved to cause higher traffic noise, which became a big headache and limited the utilization at urban areas [4–5]. Pervious concrete, as an alternative paving material, gained more and more applications for excellent water permeability, skid resistance and noise reduction [6–8].

Skid resistance was a primary factor of controlling vehicle direction and speed. Microtexture appeared to be the most crucial surface parameter in determining traffic accident rates, and macrotexture had a substantial influence, especially under high speed and/or wet pavement conditions. Skid resistance on pervious concrete pavement was undoubtedly related to how the stochastically convex and concave surface was shaped. However, very limited study had been reported on the measurement of skid resistance on pervious concrete pavement with various surface texture parameters. No direct connection between the surface textures and skid resistance had been achieved by far, not to mention the designing or constructing strongly skid-resistant pervious concrete pavement.

It had been recognized that fractal geometry provided researchers with a powerful descriptive tool in road pavements or relative subjects. It was reported to use fractal for the characterization of aggregate shape and for the determination of its surface area [9]. The singular fractal function with lattice beam network was found to represent the fracture behavior of concrete [10]. And the flexural fatigue performance and fractal mechanism of concrete with high proportions of ground granulated blast-furnace slag were also derived [11].

In the present work, a transect contour curve of pervious concrete specimen was considered as a fractal curve, with its fractal dimension (D) indicating macrotexture, microtexture and their distributions on the surface [12–14]. The relation between surface textures, expressed through D, and skid resistance on pervious concrete pavement was investigated in detail. Combined with Fujikawa-Koike tire/road contact mode [15–16], the optimization of surface textures was analyzed for the purpose of designing or constructing skid-resistant and noise-absorptive pervious concrete pavement.

In addition, based on accelerated abrasion test, the abrasion process and attenuation of surface textures on different concrete pavements were also the focuses in this work. The changes of surface textures and skid resistance on pervious concrete, grooved concrete and exposed aggregate concrete pavement slabs were measured and compared.

2 Optimization of surface texture parameters

2.1 Surface texture parameters

To analyze and model pavement surface, a description of the surface textures was first needed. Under the criterion of magnitude, the irregularities of pavement surface could be classified. Microtexture was measured at the microscale of harshness and was known to be a function of aggregate particles and binder material mineralogy for given conditions of weather effect, traffic action and so on. Macrotexture was a surface texture irregularity, which was mainly attributed to the size, shape, angularity, spacing and distribution of coarse aggregates. Generally, a pavement surface could be classified into four categories in respect to its micro/macrotexture: (A) smooth and polished surface, i.e. having neither macrotexture nor microtexture; (B) smooth and harsh surface, i.e. having microtexture but no macrotexture; (C) rough and polished surface, i.e. having macrotexture but no microtexture; (D) rough and harsh surface, i.e. having both macrotexture and microtexture.

According to the report from Greek Ministry of Public Works, the eigenvalues of surface texture parameters were designated as 0.02 mm (fine), 0.03 mm (middle) and 0.05 mm (coarse) for microtexture; 0.3 mm (smooth), 0.7 mm (middle) and 1.0 mm (rough) for macrotexture; 10 (rare), 7 (middle) and 4 (dense) for their distribution densities, defined as the wavelength. The surface texture parameters and their corresponding friction coefficients measured on pavement are given in Table 1. A formula was established to calculate the friction coefficient m on asphalt pavement with the microtexture depth, macrotexture depth and distribution density as independent variables:

(R²=0.96)          (1)

where h_s (mm) and h_b (mm) are the average depths of microtexture and macrotexture, respectively; w is the wavelength. In most cases, 4.25w ^0.1 is equal to 5.165.

From Table 1, it could be seen that the skid resistance on asphalt pavement was closely related to the surface textures on it. Equation (1) describes the relation between surface texture parameters and friction coefficient on asphalt pavement and there is no any other material parameter involved. The measured results are very close to the calculated results. Different from conventional grooved concrete pavement and similar to asphalt pavement, there are countless random ups and downs on pervious concrete pavement with different surface textures corresponding to various skid resistances. So it is reasonable for h_s, h_b and w to be defined as the surface texture parameters on pervious concrete pavement.

Table 1 Eigenvalues of surface texture parameters and friction coefficient

2.2 Description of pervious concrete surface by fractal interpolation

A fractal is an object or quantity that displays self-similarity on all scales. Due to almost continuous self-similarity from micro to macro scales, the surface textures of pervious concrete could be seen as a fractal, which is ascribed to the random formation of pore structures and exposed coarse aggregates. Moreover, the natural erosion of pervious concrete pavement by moving tires is a stochastical process, and the abraded surface is complied with the fractal basic principles in a statistical sense. Therefore, the random surface textures and furthermore the transect contour curves of pervious concrete pavement could be described and analyzed by fractal geometry.

Some curves, not smooth and non-derived, such as coastlines, ridgelines, transect contour curves of pervious concrete pavement, and irregular distributed experimental data, could not be simulated by traditional numerical interpolations, but could be well fitted by fractal interpolation. However, it is worth noting that linear fractal interpolation is acceptable to fit self-affine curves; but it brought great error for not strictly self-affine curves. So an actual transect contour curve is suggested to be divided into several sections for more accurate simulation, and box-counting method is used to calculate its fractal dimension.

Therefore, there are two cases to simulate the surface textures on pervious concrete pavement. One is to fit the actual transect contour curves of pervious concrete pavement. Using digital photos of the cross-sections of pervious concrete specimens, transect contour curves of concrete specimen are easily obtained theoretically by using the boundary detection function of image processing software, such as MATLAB. In fact, there inevitably exist large errors because the superimposed projection of other cross-sections on the prescribed one is not excluded. However, it is feasible to determine the exact locations of a number of points on the outline of cross-sections. Based on these fractal interpolation points, i.e. a series of coordinates (x_i, y_i, i=0, 1, ···, n), an actual transect contour curve of pervious concrete specimen is simulated by piecewise linear fractal interpolation. Figure 1 illustrates two examples of the actual transect contour curves of pervious concrete specimens with the fractal dimension of 1.301 and 1.287, respectively.

Fig. 1 Actual transect contour curves of pervious concrete:

The other one is to simulate the theoretical transect contour curves by setting different values of surface texture parameters in advance, including microtexture depth h_s, macrotexture depth h_b and texture density w. On the basis of the equally spaced distributions of fractal interpolation points, the theoretical transect contour curves are obtained through integrated linear fractal interpolation. An example for h_s of 0.02 mm, h_b of 0.3 mm and w of 10 is given in Fig. 2. The fractal dimension is equal to 1.043.

Fig. 2 A theoretical transect contour curve of pervious concrete

2.3 Fractal dimension and skid resistance

Macrotexture depth (D_T) and British portable pendulum number (N_BP) are commonly used to evaluate the skid resistance on concrete pavements. D_T is a measurement of the roughness of pavement surface under dry status; while N_BP provides a good approximation of the microtexture. D, the fractal dimension of a transect contour curve of pervious concrete pavement, indicates the irregularity of stochastically convex and concave surface. Higher D means a rougher and harsher pavement for more complex surface textures; otherwise, a pavement surface is smooth. In order to investigate the feasibility and significance of D as an index to measure the skid resistance on pervious concrete pavement, different raw materials and mix proportions are chosen to produce pervious concrete specimens with diverse surface textures. D, D_T and N_BP are measured and illustrated in Fig. 3.

It can be seen from Fig. 3(a), with the increase of D_T, N_BP increases; but test data seem quite scattered. Figure 3(b) indicates that when D_T is low (i.e. less than 0.9 mm), D obviously increases with the increase of D_T. For a pavement with higher D_T, there are more exposed coarse aggregates distributed on the surface, resulting in more complex fractal structures and more excellent skid resistance. In rainy days, the edges and angles of those exposed coarse aggregates not only puncture water film to provide dry connection between pavement and moving tires, but also eliminate the rivulets on it. For higher D_T, D reaches the ultimate value and then slows down or even declines. It can be ascribed that D means the complexity of transect contour curves, changing to various directions at different scales; while D_T refers to the integrated roughness of the macrotexture on pavement. When D_T is high (i.e. 1.2 mm), the macrotexture parts on transect contour curves become rougher but their densities decrease at the same time; the microtexture tends to be smooth, lowering their complexity and hierarchy. It should be pointed out that D_T may differ even at the same N_BP, which explains that N_BP, a measurement of the fundamental skid resistance on pavements, indicates the microtexture more than the macrotexture. In Fig. 3(c), D increases with the increase of N_BP, which implies that D reflects the surface microtexture on pervious concrete pavement.

Therefore, all indexes, D, D_T and N_BP, describe the surface textures on pervious concrete pavement. D_T merely shows the overall roughness, while N_BP reflects the macrotexture but focuses more on the microtexture. However, because of no correspondence with the surface texture parameters, it is not practical for N_BP to be introduced to optimize the designing of surface textures on pervious concrete pavement. It is proved that D, fully indicating the macrotexture, microtexture and their distributions, can be adopted to measure the skid resistance on pervious concrete pavement, overcoming the shortcomings of both D_T and N_BP.

Fig. 3 Relations among D_T, N_BP, and D on pervious concrete:

2.4 Optimization of surface textures on pervious concrete pavement

Typical values of h_s, h_b and w are input and converted to theoretical transect contour curves of pervious concrete pavement. Results are represented in Figs. 4–6.

Figure 4 illustrates the improving of D with the change of h_s on the basis of h_b of 0.7 mm and w of 7, or h_b of 1.0 mm and w of 4, individually. With the increase of h_s, D increases dramatically at the beginning but slows down thereafter. When gradually approaching macro scales, the microtexture disappears on transect contour curves, reducing their complexity and hierarchy. Besides, D is also affected by h_b and ω. At the same value of h_s, D increases for higher h_b and/or lower w. It seems that D increases with the improvement of h_b in Fig. 5, explaining that h_b alone plays remarked effect on D. But for various h_s and w, there is much difference in the corresponding calculated D at the same h_b, implying the limitation of h_b or D_T as a single index to evaluate the skid resistance on pavement. A negative linear relation between D and w is found in Fig. 6. In general, lower w means denser distributed microtexture and macrotexture, leading to higher D.

Fig. 4 Relationships between D and h_s

Fig. 5 Relationships between D and h_b

Fig. 6 Relationships between D and w

FUJIKAWA et al [15–16] investigated the effect of surface texture features on noise reduction on pavement. Figure 7 depicts the road roughness parameters obtained from a road profile measured using a laser profile meter. The profile is separated by the H–H line representing a horizontal plane that divides the nominal contact area into two equal areas. Here, the parts above line H–H are treated as the asperities, indicating that the actual contact area between the tire tread and the pavement is less than 50% of the nominal contact area. Thus, the road roughness parameters illustrated in Fig. 7 are evaluated as follows: (1) Asperity height h_A: the height of the apex from line H–H; (2) Asperity height unevenness h_d: the asperity height difference between the two nearest asperities; (3) Asperity spacing x_A: the distance between adjacent asperities; (4) Asperity radius r_A: the radius of the arc that includes three points: A (apex of the asperity), B and C (the intersections between the profile and line H–H).

Fig. 7 Road roughness parameters obtained from road profile

Although some smaller asperities are frequently contained in the arcs, as shown in Fig. 7, they are neglected here. The conclusions drawn by Fujikawa et al [15–16] are listed below: (1) h_d and x_A are defined as the important parameters that govern tire vibration noise. Small h_d and x_A contribute to the abatement of tire vibration noise. (2) r_A is also found to be an essential parameter that affects tire vibration noise, although its effect is minor compared with that of h_d and x_A. Small r_A is better for noise abatement. (3) h_A, typically represented by mean roughness, is not an essential parameter.

Although the definitions of h_s, h_b, ω and h_A, h_d, x_A, r_A, are based on different models, there are some internal relations with each other. For pervious concrete, noise reduction is mainly attributed to the sound-absorptive and energy consumptive porous structure, and the stochastic uneven surface textures play a secondary role. Therefore, on the basis of skid resistance as the primary target and noise reduction as the secondary target for pervious concrete pavement, all surface texture parameters can be successfully optimized as a single index, D (seen from Table 2). It can be concluded that to optimize the surface texture parameters is in essence to seek the maximum value of D, which is recommended for designing and constructing skid-resistant and noise-absorptive pervious concrete pavement.

3 Abrasion and attenuation of surface textures

3.1 Materials and test

In China, concrete abrasion tests are referred to two standards: JTG E30—2005 (Test Methods of Cement and Concrete for Highway Engineering) or gb/t16925—1997 (Test Method for Abrasion Resistance of Concrete and its Products). unfortunately, none of these tests meet the requirements for the presented work due to no close link with the actual service circumstances on pavements, no reflection of the abrasion process changing with time, as well as no good relevance of two indexes, i.e. the abrasion speed and the corresponding attenuation degree of the surface textures on concrete pavements.

Figure 8 shows a schematic diagram of accelerated abrasion test. A concrete specimen (300 mm×300 mm×50 mm) was firmly placed on a sliding track, which was installed on a test table and driven back and forth at 50–100 cycles/min by power system, including an a rate of electromotor, a gearshift, an eccentric gear group with concave groove and a crank. Pressure was exerted on the axle of wear wheel to keep it freely rolling on the vertical plane to concrete surface. If there was enough friction between the wheel and concrete surface, the wheel rolled; while if not, it converted to slide. A hard emery wheel (width of 200 mm), exerting vertical pressure of (0.3±0.02) MPa, was served to replace the conventional rubber wheel. Mass loss percentage Dm, D_T and N_BP on concrete slab surface were measured. Modified D_T was calculated from sand area paved in fact and sand amount actually used, referred to JTJ059—95 (On-the-spot Test Methods for Highway Road Bases and Pavements). Two parameters, i.e. mass loss percentage within wheel track region Dm_i and abrasion speed index k_i, were defined, representing the abrasion degree and abrasion speed specifically.

Table 2 Optimization of surface texture parameters for pervious concrete pavement

Fig. 8 Schematic diagram of accelerated abrasion test for concrete pavement slabs

             (2)

                       (3)

where m₀ represents the original mass and m_i is the i-th measured mass of concrete specimen, and n refers to the abrasion frequency between two neighboring measures.

3.2 Abrasion process and attenuation of surface textures on grooved concrete slabs

C35 concrete slab specimens were prepared with 9.5–20 mm limestone as coarse aggregates. The specimen surfaces were handily pressed to form horizontal grooves (width of 4 mm, depth of 3 mm, and intervals of 20 mm) after being dragged rough by rag. Dm_i was measured on every 200 cycles of abrasion sustained. Test data, shown in Fig. 9, displayed that the abrasion process of grooved concrete pavement slabs can be divided into three phases. The grooved macrotexture is in direct contact with heavy wheel and rapidly worn away, leading to straightly increasing of Dm_i within less than 800 cycles. Poor abrasion resistance is undoubtedly attributed to the fact that only the weak convex parts of grooves bear the abrasion. During 1 000–1 600 cycles of abrasion, with the grooves ground away, both hardened mortar matrix and coarse aggregates exposed collectively undertake abrasion. So k_i is by far lower than that at the first phase. After 1 600 cycles of abrasion, an increasing k_i appears on account of the accumulated internal damages within concrete.

Fig. 9 Abrasion process on grooved concrete slabs

N_BP and D_T measured at the same occasions are shown in Fig. 10. Corresponding to the first phase with high k_i, both N_BP and D_T linearly decrease due to the weak convex hardened mortar. After about 1 000 cycles of abrasion, the attenuation of surface texture tends to stabilize and the final values of N_BP and D_T are dominated by the microtexture of hardened cement matrix and tiny veins of aggregates.

Fig. 10 Attenuation of surface textures on grooved concrete slabs

3.3 Attenuation of surface textures on exposed aggregate concrete pavement slabs

Recently, a new type of rigid pavement, exposed aggregate concrete pavement has been developed [17]. The 6–8 mm basalt crushed stones were embedded in concrete surface layer as exposed aggregate and 9.5–20 mm limestone was used as coarse aggregates for concrete matrix. N_BP and D_T were measured after being sustained every 200 cycles of abrasion.

Figure 11 provides the fitting curves of N_BP and D_T through regression analysis. Both of two curves fit the nonlinear exponent function y=Ae^Bx+C, accounting for rapid attenuation at early stages, gradually retarding later, and at last the tendency of stabilization. A+C, refers to the initial N_BP or D_T, indicating the original skid resistance of exposed aggregate veins and textures; while C means the final stable value after attenuating. A, the attenuation range, is on behalf of the difference of skid resistances between the surface texture of exposed aggregates and concrete matrix. Higher absolute B implies more rapid attenuation of the surface textures. In comparison, exposed aggregate concrete displays excellent abrasion resistance at early stages because of strong exposed basalt stones to resist the abrasion. With exposed aggregates entirely worn away, the matrix is exposed, and the attenuation curve will be almost the same as that of grooved concrete at later stages.

Fig. 11 Attenuation of surface textures on exposed aggregate concrete slabs

3.4 Abrasion process and attenuation of surface textures on pervious concrete slabs

Pervious concrete slabs with 5–10 mm basalt crushed stones as coarse aggregates, are manufactured from diverse raw materials and different mixtures [8]. As shown in Fig. 12, although there are different Dm_i and κ_i for two groups of slab specimens, the abrasion processes are similar in essence. There are two main features during the abrasion: first, very low Dm_i and κ_i in accordance with the same abrasion cycles, compared to test results from grooved concrete slabs, and second, steady abrasion process without intense changes of abrasion speed.

N_BP and D_T are marked in Fig. 13. There is no remarkable and stable descending of both N_BP and D_T with the accumulated abrasion cycles. Different from grooved concrete and exposed aggregate concrete, pervious concrete has an identical constitution materials and a homogeneous structure along its depth. During the abrasion process, every single abraded layer, successively contacting with heavy wheel, is stochastic but statistically identical, and there is no weak layer within pervious concrete. Besides, a slight rise of abrasion speed should be taken into consideration in practice, which is attributed to the accumulated internal damages within pervious concrete caused by moving wheels for a long period of time.

Fig. 12 Abrasion process on pervious concrete slabs:

Fig. 13 Attenuation of surface texture on pervious concrete slabs:

4 Conclusions

1) Fractal dimension (D), an index of the complexity and hierarchy of transect contour curves of pervious concrete pavement, is proved to indicate the macrotexture, microtexture and their distributions on the surface, and overcome the shortcomings of D_T and N_BP.

2) Combined with Fujikawa-Koike tire/road contact model, the surface texture parameters of pervious concrete pavement are successfully optimized as a single index D. And the optimization of the surface texture parameters is in essence to seek the maximum value of D.

3) Based on accelerated abrasion test, it is found that as far as the abrasion resistance and theoretical service life of skid-resistant texture are concerned, pervious concrete pavement is the most durable.

4) The analysis in the presented study is qualitative, not quantitative, for the reason that every factor of constituent materials such as cement brand, coarse aggregate type, gradation and mix proportion may affect the test results. With more and more engineering practices of pervious concrete pavement in China, more research on the surface textures and skid resistance of pervious concrete pavement should be conducted.

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(Edited by HE Yun-bin)

Foundation item: Project(kfj080205) supported by Key Laboratory of Road Structure and Material of Ministry of Transport of Changsha, China

Received date: 2011–11–29; Accepted date: 2012–02–24

Corresponding author: CHEN Yu, PhD, Associate Professor; Tel: +86–731–85779355; E-mail: just4ujust43@163.com