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Development of permeability test method for porous concrete block pavement materials considering clogging
Construction and Building Materials 118 (2016) 20–26
Contents lists available at ScienceDirect
Construction and Building Materials journal homepage: www.elsevier.com/locate/conbuildmat
Development of permeability test method for porous concrete block pavement materials considering clogging Wuguang Lin a, Dae-Geun Park b, Sung Woo Ryu c, Byeong-Tae Lee d,⇑, Yoon-Ho Cho e a
College of Transport and Communications, Shanghai Maritime Univ., 1550 Haigang Ave., Shanghai, PR China Pavement Research Center, Seoul Metropolitan Government Quality Inspection Office, 131 Taebong-ro, Seocho-gu, Seoul 137-900, Republic of Korea c Korea Expressway Corporation Research Institute, 208-96, Dongbu-daero 922 beon-gil, Dongtan-myeon, Hwaseong-si, Gyeonggi-do, Republic of Korea d Dept. of Civil and Environmental Engineering, Chung-Ang Univ., 84 Heukseok-Ro, Dongjak-Gu, Seoul 156-756, Republic of Korea e Dept. of Civil and Environmental Engineering, Chung-Ang Univ., 84 Heukseok-Ro, Dongjak-Gu, Seoul, Republic of Korea b
h i g h l i g h t s The causes of clogging were investigated and a clogging simulator was developed to evaluate the sustainable permeability of porous concrete block
pavement. Furthermore, a test method for verifying the sustainability of infiltration which can predict and assess the permeability performance was proposed. It was found that the pores were easily clogged with the vibration frequency increased, but with the amount of contaminants increased to a degree
clogging had less influence on vibration.
a r t i c l e
i n f o
Article history: Received 21 August 2015 Received in revised form 7 March 2016 Accepted 20 March 2016
Keywords: Clogging simulator Porous concrete block materials Sustainable permeability test
a b s t r a c t Pervious pavement has been used widely due to efficient hydrological characteristics such as reduction of runoff during floods, providing delay of rainwater into sewer systems and ground water quality improvement. However, clogging prevents it from functioning properly due to sedimentation after a short period of service, which results to poor permeability and performance of pervious pavement. In this study, the causes of clogging were investigated and a clogging simulator was developed in order to evaluate the sustainable permeability of porous concrete block pavement in advance. Furthermore, a test method for verifying the sustainability of infiltration which can predict and assess the permeability performance by years of service was proposed. In addition, the penetration of contaminants also varies depending on vehicle vibration and the rainwater that permeates together with it. It was found that the pores were easily clogged with the vibration frequency increased, but with the amount of contaminants increased to a degree clogging had less influence on vibration. When various types of porous concrete block pavers were evaluated with the proposed sustainable permeability test method, the coefficient of permeability before and after the test have shown very high correlation. Ó 2016 Published by Elsevier Ltd.
1. Introduction Pervious pavement has been widely used because of efficient hydrologic characteristics, such as driving safety during rainy days, runoff reduction and ground water quality improvement etc. The permeability of new pervious pavement is known to be at least 4500 mm/h (equivalent to 1.25 mm/s) before traffic opening, and ⇑ Corresponding author. E-mail addresses: [email protected] (W. Lin), [email protected] (D.-G. Park), [email protected] (S.W. Ryu), [email protected] (B.-T. Lee), [email protected] (Y.-H. Cho). http://dx.doi.org/10.1016/j.conbuildmat.2016.03.107 0950-0618/Ó 2016 Published by Elsevier Ltd.
the performance of some pervious pavement systems is 0.03 0.3 mm/h even after service for 15–20 years (Yong et al. 2013) [1]. The service life of pervious pavement is defined as the period until the pervious function of pavement drops due to clogging up to a level at which it cannot cope with the design storm and requires maintenance such as cleaning (Wong, 2006) [2]. Clogging phenomenon refers to the loss of permeable function due to the clogging of pores with various foreign particles on the road entering the pervious pavement after traffic opening, thus lowering the coefficient of permeability and hydraulic conductivity. Kayhanian et al. (2012) [3] took the images of core specimens using X-ray and found that most cases of clogging occurred on the
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surface of pavement. A majority of the specimens, which were collected from field were clogged from the surface down to 25 mm. and some of them were even clogged down to 100 mm. Pratt et al. (1995) [4] claimed that the accumulation of fine particles in the pores of pervious pavement caused clogging and the mass of the cumulative sediments was the most critical factor. Furthermore, the particle size of sediments can be another influencing factor because small sediment particles are locked by large particles, and the more small particles there are, the faster the pores get clogged (Colandini et al., 1995) [5]. According to the findings from the study by Kayhanian et al. (2012) [3], the content of dust with 38 lm or smaller particle diameter is the major influencing factor of clogging. The test method of permeability for the porous medium is mainly divided into lab tests and field performance tests, but it is difficult to predict the permeability of the pervious pavement inservice by using these methods. Further, since it is difficult to simulate rainwater containing pollutants, the actual evolution of surface infiltration is unknown. A typical field permeability test methods for pervious pavement are introduced by the ASTM C 1701 [6] which is based on constant head permeability test. Another typical laboratory test method for permeable pavement materials is introduced by KS F 4419 [7]. The limitation of these test methods is that they cannot predict the permeability after it is open to traffic. Unlike typical porous medium, traffic is loaded on the pervious pavement in most cases after construction. This means the process of contamination penetrating into the voids can vary due to traffic load, such as pressure by its weight and vibration by driving on the pavement. It will further be accelerated by the pore clogging caused by tire friction or compression forces. However, it was confirmed that there are no case studies on clogging of the porous medium by applying vibration. Therefore, the test method for evaluating the permeability of pervious pavement considering the characteristics of the traffic will be required. In this study, a method of evaluating the sustainable permeability of pervious pavement materials was proposed after simulating the clogging process through a lab test with contaminants on actual roads.
constructed by typical asphalt pavement with 3.5 m width for each lane. Hence, the total investigating area concerned for collecting contaminants is 157,500 m2. The roads in this area were cleaned each day. 2.2. Dust contaminants grain-size analysis Table 1 shows the weight of the collected contaminants per day. The cleaning equipment automatically classifies large contaminants and fine dusts, and stores them separately. The weights of contaminants shown in Table 2 were calculated depending on distance and area of the cleaning equipment operated. To examine the characteristics of road dusts affecting clogging, the average grain size of contaminants was analyzed using six samples that were collected each from large and fine dust bins. The grain sizes of the large contaminants and fine dusts following t-distribution at 95% confidence level are shown in Fig. 1. Most of the contaminants filtered through No. 4 sieve were leaves and cigarette butts which would not greatly affect clogging over time. The largest percentage of the contaminants was the grain sizes between No. 30 and No. 50 sieves, which are mainly sand and dust with the particle diameters between 0.60 and 0.36 mm. They were regarded as causing clogging as they come in contact with water and became agglomerated. The collected large contaminants and fine dusts were combined at 56:44 ratios in the laboratory and the gradation was shown in Fig. 2. The permeability of pervious pavement decreases as the service period increases. The correlations between permeability and service period were analyzed on the basis of the amount of collected contaminants. As a result of the analysis of the contaminants collected by cleaning equipment in Eupyeong-gu, Seoul, the variation of the amount of contaminants was not significant. Therefore, it was assumed that the same amount of contaminants was generated every year. The amount of daily contaminants per unit area was calculated as 332 mg/m2/day. 3. Clogging simulator and test method 3.1. Clogging simulator
2. Dust contaminants collection and grain-size analysis 2.1. Dust contaminants collection The movements of contaminants on the roads are classified into siltation, suspension, and creep. Siltation is the movement of small particles with a diameter of 70–500 lm, which fly from the surface of pavement and move along the shape of orbit under the influence of the resistance of air and the gravity. This consists of 55–72% of all movements. Suspension refers to the floating and moving of particles in air by wind at a distance before being precipitated. The diameter of these particles is smaller than 70 lm. Suspension accounts for 3–10% of all movements. Creep refers to the rolling or slow moving of sands and aggregate-sized particles under the influence of silting particles and accounts for 7–25% of all movements. Among these particles, large sand particles gather on the pervious pavement and the spaces between them are filled with dusts or fine particles generated from worn out pavement surface and vehicle tires, which decrease permeability and clog the pores, thereby making the pavement impervious (Amirjani, 2010) [8]. To identify the characteristics of fine dusts in roads, the contaminants on the roads were collected for two consecutive days with a road cleaning equipment that was being used by local government of Seoul city. The recommended operating speed of the vehicles was 10–15 km/h and the total length of the sections that were passed through was 45 km. The local roads investigated were
The clogging simulator was developed to simulate the event in which the pores of pervious pavement can be clogged by contaminants in water initially. Furthermore, a motor was attached to simulate the vibration of the vehicle on the road and early clogging. A mold of a certain size was used to evaluate the pervious pavement as shown in Fig. 3 that indicates the details of the clogging simulator. On the asphalt road at a constant vehicle speed of 60 km/h, torsion resonance of the tire exhibits a large peak around the frequency of 40 Hz (Umeno, 2002) [9]. The vibration motor can simulate the vehicle movement in the vertical direction, which can be controlled to 0–60 Hz with the increment of 0.1 Hz. The main body and table were fixed with springs to minimize the test error when the table is vibrated. The size of the mold to mount pervious material is 200 200 150 mm, and the porous blocks which are sold in large numbers at present in Korea can be tested. Sponge was attached to an iron plate so as to prevent gaps between Table 1 Comparison of weights of contaminants collected at local road in Seoul. 1st Day (kg) Large contaminants Fine dusts Total contaminants
2nd Day (kg) 27.60 9.45 10.45 47.50
Large contaminants Fine dusts Total contaminants
Average (kg) 30.70 17.15 9.30 57.15
29.15 23.18 52.33
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Table 2 Weight of contaminants by unit distance and area.
4. Evaluation of different test methods
Division
Large contaminants
Fine dusts
Total contaminants
Weight of contaminants by distance (mg/m) Weight of contaminants by area (mg/m2)
647.78
515.11
1162.89
185.08
147.17
332.25
100 Coarse_lower Coarse_upper Fine_lower Fine_upper
Passing ratio (%)
80
60
40
20
0 No.4
No.8
No.16
No.30
No.50
No.100
No.200
Pan
Sieve number Fig. 1. Gradation envelopes of large contaminants and fine dusts.
100 Lower Upper Active
Passing ratio (%)
80
60
40
To determine the process of permeating contaminants, a trial test was conducted in three conditions. First one is a dry method that supplies contaminants only through the vibration of equipment without water (case 1, dry method). Second is the application of vibration in dry method with no water for 50% of the total vibration time and then conduct a vibration test while adding water for the remaining 50% (case 2, dry and wet method). Third is the application of vibration while supplying contaminants and water simultaneously to clog the pores of the pervious pavement (case 3, wet method). For the test specimen, porous blocks having a dimension of 200 mm 200 mm 60 mm are used. The porosity and coefficient of permeability of the porous blocks are about 15% and 0.56 mm/s, respectively. The effect of contaminant application methods on the permeability coefficient is shown in Fig. 5. The critical condition for clogging pores was case 3 (wet method) followed by case 2 (dry and wet method) and case 1 (dry method). In particular, the wet method and dry method showed 2 mm/s or greater difference in permeability coefficient. The reason for this seems that when the contaminants are washed out with rainwater, the resistance between the dust particles and pavement material could be decreased, allowing the contaminants to easily penetrate and clog the pores. Furthermore, all cases with clogged pores in the pervious blocks are most critical one in the 60-second vibration time as shown in Fig. 5. Before the test, it was expected that the longer the vibration time, the lower the permeability coefficient. On the contrary, the permeability coefficient recovered between 60 s and 90 s. In cases 1 and 2 particularly, the permeability coefficient recovered by at least 0.05 mm/s. The reason for this is that as the vibration time becomes longer, the particles escaped below the specimen due to excessive vibration. Therefore, case 3 was adopted for contamination penetrating method of this test because it can simulate the worst case, and additional tests were conducted by changing the contaminant input quantity, vibration frequency, and vibration time. 5. Clogging by vibration frequency, duration and service period
20
0 No.4
No.8
No.16
No.30
No.50
No.100
No.200
pan
Sieve number Fig. 2. Gradation envelope of synthesized contaminants.
the mold and specimen when the specimen is fixed. The fixing frame is designed to hold the mold mounted on the table during vibration which is fastened. A hose was connected to the table for drainage. 3.2. Permeability test method A test method for evaluating clogging by contaminants of pervious pavement using the new apparatus is shown schematically in Fig. 4. The pervious pavement materials are mounted in the mold in keeping the level, and a specific amount of the modified contaminants scattered homogeneously on the specimen. While applying vibration with a motor, the amount of contaminants is checked. After the contaminants have permeated, the specimen is separated from the mold, and the coefficient of permeability is measured through the constant head test method presented in KS F 4419 [7].
Various tests were conducted to evaluate the effects of the contaminant amount, frequency and duration of vibration on the change of the permeability coefficient. The amount of contaminants supplied in this test is equal to the daily generated per unit area as previously calculated above, and the periods were set to 1, 2, 5, 7, and 9 years. The frequency of vibration was varied from 20 to 60 Hz with 10 Hz intervals. The vibration duration time was varied to 15, 30, 45, 60, and 90 s. A total of 3 specimens were used for a total of 125 variations. The pervious pavement specimen is identical to the specimen used in the test method establishment process. Statistical analysis was conducted to determine the experimental error, and the result is shown in Fig. 6. The average value of the difference between the individual measurements for each test variable and the standard deviation were 0.002 and 0.04, respectively. The test results by vibration frequency and time for each input quantity are shown in Fig. 7. The result corresponding to the first year after traffic opening is shown in Fig. 7(a). There was no effect varying frequency for the same duration. Further, no effects of different vibration time at the same frequency were found either. As a result of the test, the permeability coefficient did not change much in general and was close to the initial value before the contaminants were processed. The average permeability coefficient was 0.49 mm/s and the standard deviation was 0.03 mm/s. In the results corresponding to the second year of service as shown in Fig. 7(b), the permeability coefficient was generally lower
W. Lin et al. / Construction and Building Materials 118 (2016) 20–26
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Fig. 3. Contaminant penetration apparatus: ① Mold, ② Waterproof plate, ③ Main Body, ④ Pervious pavement, ⑤ Mold fixing frame, ⑥ Spring, ⑦ Controller, ⑧ Vibration motor.
Fixing the specimen
Permeation process of contaminants
Evaluation of permeability performance
Fig. 4. Contaminant penetration method.
Coefficient of permeability (mm/sec)
0.6 Case 1 Case 2 Case 3
0.5
0.4
0.3
0.2
0.1
0.0 0
20
40
60
80
100
Duration of vibration (sec)
Fig. 6. Difference in average values by test variable.
Fig. 5. Difference in permeability coefficient by water supply in vibration test.
when the vibration frequency was higher, except for some test results. As the vibration time increased from 15 s to 60 s, the permeability coefficient decreased. However, the permeability coefficient by vibration frequency converged at 90 s of vibration time. It means that there is a time when the change of the permeability coefficient slows down after a specific vibration duration time, and it will be possible to identify the difference in clogging effect by different amount contaminant.
The test results for the fifth year of service showed similar trends as the second year test results. As the vibration frequency increased, the coefficient of permeability decreased, and also as the vibration time increased, the permeability coefficient decreased. When contaminants corresponding to the 7th and 9th year of service were inputted, the change of the coefficient of permeability by vibration frequency and time showed similar trends. The coefficient of permeability still decreased as the vibration frequency increased, but the decrement was smaller compared to the test results for the 2nd and 5th years.
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W. Lin et al. / Construction and Building Materials 118 (2016) 20–26 0.6
Coefficient of permeability (mm/sec)
Coefficient of permeability (mm/sec)
0.6
0.5
0.4
0.3
0.2 20 Hz 30 Hz 40 Hz 50 Hz 60 Hz
0.1
(a) 0.0
20 Hz 30 Hz 40 Hz 50 Hz 60 Hz
0.5
0.4
0.3
0.2
0.1
(b) 0.0
0
20
40
60
80
100
0
20
Duration of vibration (sec) 0.6
60
80
100
0.6
20 Hz 30 Hz 40 Hz 50 Hz 60 Hz
0.5
Coefficient of permeability (mm/sec)
Coefficient of permeability (mm/sec)
40
Duration of vibration (sec)
0.4
0.3
0.2
0.1
20 Hz 30 Hz 40 Hz 50 Hz 60 Hz
0.5
0.4
0.3
0.2
0.1
(d)
(c) 0.0
0.0 0
20
40
60
80
0
100
20
Duration of vibration (sec)
40
60
80
100
Duration of vibration (sec)
Coefficient of permeability (mm/sec)
0.6 20 Hz 30 Hz 40 Hz 50 Hz 60 Hz
0.5
0.4
0.3
0.2
0.1
(e) 0.0 0
20
40
60
80
100
Duration of vibration (sec) Fig. 7. Test results by contaminant input quantity, vibration frequency, and vibration time: (a) 1 year (b) 2 years (c) 5 years (d) 7 years (e) 9 years.
For the effects by vibration duration time, the permeability coefficient decreased with the vibration duration time increased until 60 s. Therefore, once the contaminant quantity increases up to a certain level, it becomes a main factor in lowering the permeability coefficient rather than the vibration duration. Based on the above test results, clogging can be maximized by setting the vibration time to 60 s and the vibration frequency to 60 Hz to evaluate the sustainable permeability of the pervious pavement materials.
To analyze the pores in the pervious concrete blocks that were clogged over time, the correlations between the permeability coefficient and service life were investigated. Each results of 1, 2, 5, 7, and 9 years of service was statistically analyzed, regardless of the vibration time and frequency, and the results are shown in Fig.8. The permeability predictor for pervious concrete block pavement was presented below (Eq. (1)):
K ¼ 0:17 þ 0:41expð0:57xÞ
ð1Þ
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W. Lin et al. / Construction and Building Materials 118 (2016) 20–26
lnðKÞ ¼ 7:03 2:55x 1:22y þ f 1 ðxÞ þ f 2 ðyÞ
ð2Þ
where, K in Eq. (2) = permeability at average of the left and right wheel paths (traffic loading area, unit = cm/s), x and y in Eq. (2) = age and total sediment mass of particles <38 lm, respectively. f 1 ðxÞ and f 2 ðyÞ are presented below:
f 1 ðxÞ ¼ 0:99 þ 1:65x 1:16 2 þ 0:30 3; x < 2:0 ¼ 1:09 0:62x þ 0:05x2 ;
2:0 < x < 3:5
¼ 0:65 þ 0:10x 0:005x2 þ 0:008x3 ;
x > 3:5
f 2 ðyÞ ¼ 0:46 þ 7:61y 2:07y2 4:32y3 ;
y < 0:47
0:47 < y < 0:60 ¼ 1:23 þ 28:77y 3:19y2 34:58y3 ; 0:60 < y < 0:87 ¼ 52:59 10:20y 84:06y2 þ 36:60y3 ; ¼ 56:92 28:46y þ 139:73y2 57:69y3 ; y > 0:87 Fig. 9 gave the result comparison between two models. Even though the permeability coefficient calculated by two hydrologic models shown totally different results, but both of the model shown the permeability decreased most serious began from the 2nd year. Also, the permeability coefficient decreased sharply from the 2nd year after service base on the test results in Fig. 8. To avoid the hydrological failure by clogging, infiltration maintained job by
Coefficient of permeability (mm/sec)
0.6
0.5
0.4
K = 0.17+0.41exp(-0.57x) 0.3
0.2
0.1
K = exp(7.03-2.55x-1.22y+f1(x)+f2(y))
0.0 0
2
4
6
8
10
Performance period (year) Fig. 9. Coefficient of permeability comparison between two models.
2.5
Coefficient of permeability after test (mm/sec)
where, K in Eq. (1) = permeability, x = age. As the years increased, the permeability coefficient tended to decrease exponentially, and its change rate also decreased. In the 1st year, the permeability coefficient decreased by about 13% compared to the initial value, and in the 2nd year, it decreased sharply by 44%. The test results of the 5th and 9th years showed similar permeability coefficient and decreased by about 33% compared to the initial value. This suggests that the sustainability of the permeability coefficient is closely associated with the contaminant quantity, but the effect on the permeability performance reaches a critical limit when the pores are clogged to a certain degree. According to the graph showing trend of permeability coefficient by Interpave (2010) [10], the value of the pervious pavement drops by about 40% after five years of service. After that, the change of the permeability performance is insignificant. Similar test results were derived in this study as well. Therefore, the contaminant quantity to evaluate the sustainable permeability of pervious pavement was standardized until 5 years. To verify the validity of the permeability predictor and provide the appropriate cleaning time for pervious concrete block pavement, the developed model (Eq. (1)) was compared with the hydrologic model presented by Kayhanian et al. (2012) [3] which base on field test results (Eq. (2))
2.0
1.5
1.0
0.5
y = 0.469x-0.004 R2 = 0.88
0.0 0.0
0.5
1.0
1.5
2.0
2.5
Coefficient of permeability before test (mm/sec) Fig. 10. Comparison of the coefficient of permeability between before and after the sustainable permeability test.
periodic vacuum cleaning was suggested within two years after the pavement placed. When the pavement is almost completely clogged, cleaning is difficult and expensive.
Coefficient of permeability (mm/sec)
1.0 Active Curve fit line
6. Verify the test method
0.8
0.6
y = 0.17+0.41*exp(-0.57*x) 0.4
R2 =0. 91 0.2
0.0 0
2
4
6
8
10
Performance period (year) Fig. 8. Reduction trend of the coefficient of permeability by years of service.
To verify the validity of the test method, 63 types of pervious pavement materials were evaluated. The permeability coefficients were compared before and after the sustainable permeability test. The quantity of contaminants used in the test corresponds to five years accumulation, and the vibration frequency and vibration time were set to 60 Hz and 60 s, respectively. The test results are shown in Fig. 10. The permeability coefficients before and after the test showed a high correlation (R2 = 0.88). Through the correlation equation the permeability coefficient after 5 years could be predicted from the coefficient of permeability before applying contamination. Furthermore, it will be possible to tentatively use the initial coefficient of permeability values to model permeability reduction due to clogging in a hydrological analysis. Although there were variations by the type of pervious pavement, the permeability coefficient decreased by 54% on average.
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7. Conclusions Clogging prevents pervious pavement from functioning properly because the pavement becomes impervious after a short period of service. In this study, to evaluate the sustainable permeability of pervious pavement in advance, the causes of clogging were investigated and a clogging simulation apparatus was developed. Furthermore, a test method for verifying the sustainability of infiltration which can predict and assess the permeability performance by years of service was presented. i. The clogging has been found to be greatly affected by the years of service, which means the cumulative quantity of contaminants. However, when pores are clogged to some degree, the change of the coefficient of permeability slows down. ii. Furthermore, the penetration characteristics of contaminants vary depending on whether there is vehicle vibration or whether rainwater permeates together with them. When the vibration frequency was set up from 20 Hz to 60 Hz, the pores were easily clogged with the increase in vibration frequency. The permeability had less influence on vibration with supplying increment amounts of cumulative contaminants. iii. To avoid the hydrological failure by clogging, infiltration maintenance job by periodic vacuum cleaning was suggested within two years after the pavement placed. When the pavement is almost completely clogged, cleaning is difficult and expensive. iv. When 63 types of porous concrete block pavers were evaluated with the proposed permeability test method, the coefficients of permeability before and after the test showed a very high correlation (R2 = 0.88) between them, and the coefficient of permeability decreased by 54% (maximum = 76%, minimum = 20%) on average. Based on these
findings, it will be possible to tentatively use the initial coefficient of permeability values to model permeability reduction due to clogging in the hydrological analysis. In the future, more research is needed to comparatively analyze the reduction trend of permeability and the findings of this study through continuous monitoring about pervious pavement materials installed on the roads. Acknowledgements This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korea government (MSIP) (No. 2014R1A2A2A01007697). References [1] C.F. Yong, D.T. McCarthy, A. Deletic, Predicting physical clogging of porous and permeable pavements, J. Hydrol. 481 (2013) 48–55. [2] T.H.F. Wong, Water Sensitive urban design – The story thus far, Aust. J. Water Resour. 10 (2006) 213–221. [3] M. Kayhanian, D. Anderson, J.T. Harvey, D. Jones, B. Muhunthan, Permeability measurement and scan imaging to assess clogging of pervious concrete pavements in parking lots, J. Environ. Manage. 95 (2012) 114–123. [4] C.J. Pratt, J.D.G. Mantle, P.A. Schofield, UK Research into the performance of permeable pavement, reservoir structures in controlling stormwater discharge quantity and quality, J. Water Sci. Technol. 32 (1995) 63–69. [5] V. Colandini, M. Legret, Y. Brosseaud, J.D. Balades, Metallic pollution in clogging materials of urban porous pavements, J. Water Sci. Technol. 32 (1995) 57–62. [6] ASTM C 1701/C 1701M – 09, Standard Test Method for Infiltration Rate of in Place Pervious Concrete, ASTM International, West Conshohocken, PA, 2009. [7] KS F 4419, Concrete Interlocking Block for Side Walk and Road, Korea Industrial Standards, 2009. [8] M. Amirjani, Clogging of Permeable Pavements in Semi-Areas (Master of Science thesis), Delft University of Technology, 2010. [9] T. Umeno, Estimation of tire–road friction by tire-rotational vibration model, R&D Rev. Toyota CRDL 37 (2002) 53–58. [10] Interpave. Guide to the Design, Construction and Maintenance of Concrete Block Permeable Pavements, sixth ed., The Precast Concrete Paving and Kerb Association, UK, 2010.
Contents lists available at ScienceDirect
Construction and Building Materials journal homepage: www.elsevier.com/locate/conbuildmat
Development of permeability test method for porous concrete block pavement materials considering clogging Wuguang Lin a, Dae-Geun Park b, Sung Woo Ryu c, Byeong-Tae Lee d,⇑, Yoon-Ho Cho e a
College of Transport and Communications, Shanghai Maritime Univ., 1550 Haigang Ave., Shanghai, PR China Pavement Research Center, Seoul Metropolitan Government Quality Inspection Office, 131 Taebong-ro, Seocho-gu, Seoul 137-900, Republic of Korea c Korea Expressway Corporation Research Institute, 208-96, Dongbu-daero 922 beon-gil, Dongtan-myeon, Hwaseong-si, Gyeonggi-do, Republic of Korea d Dept. of Civil and Environmental Engineering, Chung-Ang Univ., 84 Heukseok-Ro, Dongjak-Gu, Seoul 156-756, Republic of Korea e Dept. of Civil and Environmental Engineering, Chung-Ang Univ., 84 Heukseok-Ro, Dongjak-Gu, Seoul, Republic of Korea b
h i g h l i g h t s The causes of clogging were investigated and a clogging simulator was developed to evaluate the sustainable permeability of porous concrete block
pavement. Furthermore, a test method for verifying the sustainability of infiltration which can predict and assess the permeability performance was proposed. It was found that the pores were easily clogged with the vibration frequency increased, but with the amount of contaminants increased to a degree
clogging had less influence on vibration.
a r t i c l e
i n f o
Article history: Received 21 August 2015 Received in revised form 7 March 2016 Accepted 20 March 2016
Keywords: Clogging simulator Porous concrete block materials Sustainable permeability test
a b s t r a c t Pervious pavement has been used widely due to efficient hydrological characteristics such as reduction of runoff during floods, providing delay of rainwater into sewer systems and ground water quality improvement. However, clogging prevents it from functioning properly due to sedimentation after a short period of service, which results to poor permeability and performance of pervious pavement. In this study, the causes of clogging were investigated and a clogging simulator was developed in order to evaluate the sustainable permeability of porous concrete block pavement in advance. Furthermore, a test method for verifying the sustainability of infiltration which can predict and assess the permeability performance by years of service was proposed. In addition, the penetration of contaminants also varies depending on vehicle vibration and the rainwater that permeates together with it. It was found that the pores were easily clogged with the vibration frequency increased, but with the amount of contaminants increased to a degree clogging had less influence on vibration. When various types of porous concrete block pavers were evaluated with the proposed sustainable permeability test method, the coefficient of permeability before and after the test have shown very high correlation. Ó 2016 Published by Elsevier Ltd.
1. Introduction Pervious pavement has been widely used because of efficient hydrologic characteristics, such as driving safety during rainy days, runoff reduction and ground water quality improvement etc. The permeability of new pervious pavement is known to be at least 4500 mm/h (equivalent to 1.25 mm/s) before traffic opening, and ⇑ Corresponding author. E-mail addresses: [email protected] (W. Lin), [email protected] (D.-G. Park), [email protected] (S.W. Ryu), [email protected] (B.-T. Lee), [email protected] (Y.-H. Cho). http://dx.doi.org/10.1016/j.conbuildmat.2016.03.107 0950-0618/Ó 2016 Published by Elsevier Ltd.
the performance of some pervious pavement systems is 0.03 0.3 mm/h even after service for 15–20 years (Yong et al. 2013) [1]. The service life of pervious pavement is defined as the period until the pervious function of pavement drops due to clogging up to a level at which it cannot cope with the design storm and requires maintenance such as cleaning (Wong, 2006) [2]. Clogging phenomenon refers to the loss of permeable function due to the clogging of pores with various foreign particles on the road entering the pervious pavement after traffic opening, thus lowering the coefficient of permeability and hydraulic conductivity. Kayhanian et al. (2012) [3] took the images of core specimens using X-ray and found that most cases of clogging occurred on the
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surface of pavement. A majority of the specimens, which were collected from field were clogged from the surface down to 25 mm. and some of them were even clogged down to 100 mm. Pratt et al. (1995) [4] claimed that the accumulation of fine particles in the pores of pervious pavement caused clogging and the mass of the cumulative sediments was the most critical factor. Furthermore, the particle size of sediments can be another influencing factor because small sediment particles are locked by large particles, and the more small particles there are, the faster the pores get clogged (Colandini et al., 1995) [5]. According to the findings from the study by Kayhanian et al. (2012) [3], the content of dust with 38 lm or smaller particle diameter is the major influencing factor of clogging. The test method of permeability for the porous medium is mainly divided into lab tests and field performance tests, but it is difficult to predict the permeability of the pervious pavement inservice by using these methods. Further, since it is difficult to simulate rainwater containing pollutants, the actual evolution of surface infiltration is unknown. A typical field permeability test methods for pervious pavement are introduced by the ASTM C 1701 [6] which is based on constant head permeability test. Another typical laboratory test method for permeable pavement materials is introduced by KS F 4419 [7]. The limitation of these test methods is that they cannot predict the permeability after it is open to traffic. Unlike typical porous medium, traffic is loaded on the pervious pavement in most cases after construction. This means the process of contamination penetrating into the voids can vary due to traffic load, such as pressure by its weight and vibration by driving on the pavement. It will further be accelerated by the pore clogging caused by tire friction or compression forces. However, it was confirmed that there are no case studies on clogging of the porous medium by applying vibration. Therefore, the test method for evaluating the permeability of pervious pavement considering the characteristics of the traffic will be required. In this study, a method of evaluating the sustainable permeability of pervious pavement materials was proposed after simulating the clogging process through a lab test with contaminants on actual roads.
constructed by typical asphalt pavement with 3.5 m width for each lane. Hence, the total investigating area concerned for collecting contaminants is 157,500 m2. The roads in this area were cleaned each day. 2.2. Dust contaminants grain-size analysis Table 1 shows the weight of the collected contaminants per day. The cleaning equipment automatically classifies large contaminants and fine dusts, and stores them separately. The weights of contaminants shown in Table 2 were calculated depending on distance and area of the cleaning equipment operated. To examine the characteristics of road dusts affecting clogging, the average grain size of contaminants was analyzed using six samples that were collected each from large and fine dust bins. The grain sizes of the large contaminants and fine dusts following t-distribution at 95% confidence level are shown in Fig. 1. Most of the contaminants filtered through No. 4 sieve were leaves and cigarette butts which would not greatly affect clogging over time. The largest percentage of the contaminants was the grain sizes between No. 30 and No. 50 sieves, which are mainly sand and dust with the particle diameters between 0.60 and 0.36 mm. They were regarded as causing clogging as they come in contact with water and became agglomerated. The collected large contaminants and fine dusts were combined at 56:44 ratios in the laboratory and the gradation was shown in Fig. 2. The permeability of pervious pavement decreases as the service period increases. The correlations between permeability and service period were analyzed on the basis of the amount of collected contaminants. As a result of the analysis of the contaminants collected by cleaning equipment in Eupyeong-gu, Seoul, the variation of the amount of contaminants was not significant. Therefore, it was assumed that the same amount of contaminants was generated every year. The amount of daily contaminants per unit area was calculated as 332 mg/m2/day. 3. Clogging simulator and test method 3.1. Clogging simulator
2. Dust contaminants collection and grain-size analysis 2.1. Dust contaminants collection The movements of contaminants on the roads are classified into siltation, suspension, and creep. Siltation is the movement of small particles with a diameter of 70–500 lm, which fly from the surface of pavement and move along the shape of orbit under the influence of the resistance of air and the gravity. This consists of 55–72% of all movements. Suspension refers to the floating and moving of particles in air by wind at a distance before being precipitated. The diameter of these particles is smaller than 70 lm. Suspension accounts for 3–10% of all movements. Creep refers to the rolling or slow moving of sands and aggregate-sized particles under the influence of silting particles and accounts for 7–25% of all movements. Among these particles, large sand particles gather on the pervious pavement and the spaces between them are filled with dusts or fine particles generated from worn out pavement surface and vehicle tires, which decrease permeability and clog the pores, thereby making the pavement impervious (Amirjani, 2010) [8]. To identify the characteristics of fine dusts in roads, the contaminants on the roads were collected for two consecutive days with a road cleaning equipment that was being used by local government of Seoul city. The recommended operating speed of the vehicles was 10–15 km/h and the total length of the sections that were passed through was 45 km. The local roads investigated were
The clogging simulator was developed to simulate the event in which the pores of pervious pavement can be clogged by contaminants in water initially. Furthermore, a motor was attached to simulate the vibration of the vehicle on the road and early clogging. A mold of a certain size was used to evaluate the pervious pavement as shown in Fig. 3 that indicates the details of the clogging simulator. On the asphalt road at a constant vehicle speed of 60 km/h, torsion resonance of the tire exhibits a large peak around the frequency of 40 Hz (Umeno, 2002) [9]. The vibration motor can simulate the vehicle movement in the vertical direction, which can be controlled to 0–60 Hz with the increment of 0.1 Hz. The main body and table were fixed with springs to minimize the test error when the table is vibrated. The size of the mold to mount pervious material is 200 200 150 mm, and the porous blocks which are sold in large numbers at present in Korea can be tested. Sponge was attached to an iron plate so as to prevent gaps between Table 1 Comparison of weights of contaminants collected at local road in Seoul. 1st Day (kg) Large contaminants Fine dusts Total contaminants
2nd Day (kg) 27.60 9.45 10.45 47.50
Large contaminants Fine dusts Total contaminants
Average (kg) 30.70 17.15 9.30 57.15
29.15 23.18 52.33
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Table 2 Weight of contaminants by unit distance and area.
4. Evaluation of different test methods
Division
Large contaminants
Fine dusts
Total contaminants
Weight of contaminants by distance (mg/m) Weight of contaminants by area (mg/m2)
647.78
515.11
1162.89
185.08
147.17
332.25
100 Coarse_lower Coarse_upper Fine_lower Fine_upper
Passing ratio (%)
80
60
40
20
0 No.4
No.8
No.16
No.30
No.50
No.100
No.200
Pan
Sieve number Fig. 1. Gradation envelopes of large contaminants and fine dusts.
100 Lower Upper Active
Passing ratio (%)
80
60
40
To determine the process of permeating contaminants, a trial test was conducted in three conditions. First one is a dry method that supplies contaminants only through the vibration of equipment without water (case 1, dry method). Second is the application of vibration in dry method with no water for 50% of the total vibration time and then conduct a vibration test while adding water for the remaining 50% (case 2, dry and wet method). Third is the application of vibration while supplying contaminants and water simultaneously to clog the pores of the pervious pavement (case 3, wet method). For the test specimen, porous blocks having a dimension of 200 mm 200 mm 60 mm are used. The porosity and coefficient of permeability of the porous blocks are about 15% and 0.56 mm/s, respectively. The effect of contaminant application methods on the permeability coefficient is shown in Fig. 5. The critical condition for clogging pores was case 3 (wet method) followed by case 2 (dry and wet method) and case 1 (dry method). In particular, the wet method and dry method showed 2 mm/s or greater difference in permeability coefficient. The reason for this seems that when the contaminants are washed out with rainwater, the resistance between the dust particles and pavement material could be decreased, allowing the contaminants to easily penetrate and clog the pores. Furthermore, all cases with clogged pores in the pervious blocks are most critical one in the 60-second vibration time as shown in Fig. 5. Before the test, it was expected that the longer the vibration time, the lower the permeability coefficient. On the contrary, the permeability coefficient recovered between 60 s and 90 s. In cases 1 and 2 particularly, the permeability coefficient recovered by at least 0.05 mm/s. The reason for this is that as the vibration time becomes longer, the particles escaped below the specimen due to excessive vibration. Therefore, case 3 was adopted for contamination penetrating method of this test because it can simulate the worst case, and additional tests were conducted by changing the contaminant input quantity, vibration frequency, and vibration time. 5. Clogging by vibration frequency, duration and service period
20
0 No.4
No.8
No.16
No.30
No.50
No.100
No.200
pan
Sieve number Fig. 2. Gradation envelope of synthesized contaminants.
the mold and specimen when the specimen is fixed. The fixing frame is designed to hold the mold mounted on the table during vibration which is fastened. A hose was connected to the table for drainage. 3.2. Permeability test method A test method for evaluating clogging by contaminants of pervious pavement using the new apparatus is shown schematically in Fig. 4. The pervious pavement materials are mounted in the mold in keeping the level, and a specific amount of the modified contaminants scattered homogeneously on the specimen. While applying vibration with a motor, the amount of contaminants is checked. After the contaminants have permeated, the specimen is separated from the mold, and the coefficient of permeability is measured through the constant head test method presented in KS F 4419 [7].
Various tests were conducted to evaluate the effects of the contaminant amount, frequency and duration of vibration on the change of the permeability coefficient. The amount of contaminants supplied in this test is equal to the daily generated per unit area as previously calculated above, and the periods were set to 1, 2, 5, 7, and 9 years. The frequency of vibration was varied from 20 to 60 Hz with 10 Hz intervals. The vibration duration time was varied to 15, 30, 45, 60, and 90 s. A total of 3 specimens were used for a total of 125 variations. The pervious pavement specimen is identical to the specimen used in the test method establishment process. Statistical analysis was conducted to determine the experimental error, and the result is shown in Fig. 6. The average value of the difference between the individual measurements for each test variable and the standard deviation were 0.002 and 0.04, respectively. The test results by vibration frequency and time for each input quantity are shown in Fig. 7. The result corresponding to the first year after traffic opening is shown in Fig. 7(a). There was no effect varying frequency for the same duration. Further, no effects of different vibration time at the same frequency were found either. As a result of the test, the permeability coefficient did not change much in general and was close to the initial value before the contaminants were processed. The average permeability coefficient was 0.49 mm/s and the standard deviation was 0.03 mm/s. In the results corresponding to the second year of service as shown in Fig. 7(b), the permeability coefficient was generally lower
W. Lin et al. / Construction and Building Materials 118 (2016) 20–26
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Fig. 3. Contaminant penetration apparatus: ① Mold, ② Waterproof plate, ③ Main Body, ④ Pervious pavement, ⑤ Mold fixing frame, ⑥ Spring, ⑦ Controller, ⑧ Vibration motor.
Fixing the specimen
Permeation process of contaminants
Evaluation of permeability performance
Fig. 4. Contaminant penetration method.
Coefficient of permeability (mm/sec)
0.6 Case 1 Case 2 Case 3
0.5
0.4
0.3
0.2
0.1
0.0 0
20
40
60
80
100
Duration of vibration (sec)
Fig. 6. Difference in average values by test variable.
Fig. 5. Difference in permeability coefficient by water supply in vibration test.
when the vibration frequency was higher, except for some test results. As the vibration time increased from 15 s to 60 s, the permeability coefficient decreased. However, the permeability coefficient by vibration frequency converged at 90 s of vibration time. It means that there is a time when the change of the permeability coefficient slows down after a specific vibration duration time, and it will be possible to identify the difference in clogging effect by different amount contaminant.
The test results for the fifth year of service showed similar trends as the second year test results. As the vibration frequency increased, the coefficient of permeability decreased, and also as the vibration time increased, the permeability coefficient decreased. When contaminants corresponding to the 7th and 9th year of service were inputted, the change of the coefficient of permeability by vibration frequency and time showed similar trends. The coefficient of permeability still decreased as the vibration frequency increased, but the decrement was smaller compared to the test results for the 2nd and 5th years.
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W. Lin et al. / Construction and Building Materials 118 (2016) 20–26 0.6
Coefficient of permeability (mm/sec)
Coefficient of permeability (mm/sec)
0.6
0.5
0.4
0.3
0.2 20 Hz 30 Hz 40 Hz 50 Hz 60 Hz
0.1
(a) 0.0
20 Hz 30 Hz 40 Hz 50 Hz 60 Hz
0.5
0.4
0.3
0.2
0.1
(b) 0.0
0
20
40
60
80
100
0
20
Duration of vibration (sec) 0.6
60
80
100
0.6
20 Hz 30 Hz 40 Hz 50 Hz 60 Hz
0.5
Coefficient of permeability (mm/sec)
Coefficient of permeability (mm/sec)
40
Duration of vibration (sec)
0.4
0.3
0.2
0.1
20 Hz 30 Hz 40 Hz 50 Hz 60 Hz
0.5
0.4
0.3
0.2
0.1
(d)
(c) 0.0
0.0 0
20
40
60
80
0
100
20
Duration of vibration (sec)
40
60
80
100
Duration of vibration (sec)
Coefficient of permeability (mm/sec)
0.6 20 Hz 30 Hz 40 Hz 50 Hz 60 Hz
0.5
0.4
0.3
0.2
0.1
(e) 0.0 0
20
40
60
80
100
Duration of vibration (sec) Fig. 7. Test results by contaminant input quantity, vibration frequency, and vibration time: (a) 1 year (b) 2 years (c) 5 years (d) 7 years (e) 9 years.
For the effects by vibration duration time, the permeability coefficient decreased with the vibration duration time increased until 60 s. Therefore, once the contaminant quantity increases up to a certain level, it becomes a main factor in lowering the permeability coefficient rather than the vibration duration. Based on the above test results, clogging can be maximized by setting the vibration time to 60 s and the vibration frequency to 60 Hz to evaluate the sustainable permeability of the pervious pavement materials.
To analyze the pores in the pervious concrete blocks that were clogged over time, the correlations between the permeability coefficient and service life were investigated. Each results of 1, 2, 5, 7, and 9 years of service was statistically analyzed, regardless of the vibration time and frequency, and the results are shown in Fig.8. The permeability predictor for pervious concrete block pavement was presented below (Eq. (1)):
K ¼ 0:17 þ 0:41expð0:57xÞ
ð1Þ
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W. Lin et al. / Construction and Building Materials 118 (2016) 20–26
lnðKÞ ¼ 7:03 2:55x 1:22y þ f 1 ðxÞ þ f 2 ðyÞ
ð2Þ
where, K in Eq. (2) = permeability at average of the left and right wheel paths (traffic loading area, unit = cm/s), x and y in Eq. (2) = age and total sediment mass of particles <38 lm, respectively. f 1 ðxÞ and f 2 ðyÞ are presented below:
f 1 ðxÞ ¼ 0:99 þ 1:65x 1:16 2 þ 0:30 3; x < 2:0 ¼ 1:09 0:62x þ 0:05x2 ;
2:0 < x < 3:5
¼ 0:65 þ 0:10x 0:005x2 þ 0:008x3 ;
x > 3:5
f 2 ðyÞ ¼ 0:46 þ 7:61y 2:07y2 4:32y3 ;
y < 0:47
0:47 < y < 0:60 ¼ 1:23 þ 28:77y 3:19y2 34:58y3 ; 0:60 < y < 0:87 ¼ 52:59 10:20y 84:06y2 þ 36:60y3 ; ¼ 56:92 28:46y þ 139:73y2 57:69y3 ; y > 0:87 Fig. 9 gave the result comparison between two models. Even though the permeability coefficient calculated by two hydrologic models shown totally different results, but both of the model shown the permeability decreased most serious began from the 2nd year. Also, the permeability coefficient decreased sharply from the 2nd year after service base on the test results in Fig. 8. To avoid the hydrological failure by clogging, infiltration maintained job by
Coefficient of permeability (mm/sec)
0.6
0.5
0.4
K = 0.17+0.41exp(-0.57x) 0.3
0.2
0.1
K = exp(7.03-2.55x-1.22y+f1(x)+f2(y))
0.0 0
2
4
6
8
10
Performance period (year) Fig. 9. Coefficient of permeability comparison between two models.
2.5
Coefficient of permeability after test (mm/sec)
where, K in Eq. (1) = permeability, x = age. As the years increased, the permeability coefficient tended to decrease exponentially, and its change rate also decreased. In the 1st year, the permeability coefficient decreased by about 13% compared to the initial value, and in the 2nd year, it decreased sharply by 44%. The test results of the 5th and 9th years showed similar permeability coefficient and decreased by about 33% compared to the initial value. This suggests that the sustainability of the permeability coefficient is closely associated with the contaminant quantity, but the effect on the permeability performance reaches a critical limit when the pores are clogged to a certain degree. According to the graph showing trend of permeability coefficient by Interpave (2010) [10], the value of the pervious pavement drops by about 40% after five years of service. After that, the change of the permeability performance is insignificant. Similar test results were derived in this study as well. Therefore, the contaminant quantity to evaluate the sustainable permeability of pervious pavement was standardized until 5 years. To verify the validity of the permeability predictor and provide the appropriate cleaning time for pervious concrete block pavement, the developed model (Eq. (1)) was compared with the hydrologic model presented by Kayhanian et al. (2012) [3] which base on field test results (Eq. (2))
2.0
1.5
1.0
0.5
y = 0.469x-0.004 R2 = 0.88
0.0 0.0
0.5
1.0
1.5
2.0
2.5
Coefficient of permeability before test (mm/sec) Fig. 10. Comparison of the coefficient of permeability between before and after the sustainable permeability test.
periodic vacuum cleaning was suggested within two years after the pavement placed. When the pavement is almost completely clogged, cleaning is difficult and expensive.
Coefficient of permeability (mm/sec)
1.0 Active Curve fit line
6. Verify the test method
0.8
0.6
y = 0.17+0.41*exp(-0.57*x) 0.4
R2 =0. 91 0.2
0.0 0
2
4
6
8
10
Performance period (year) Fig. 8. Reduction trend of the coefficient of permeability by years of service.
To verify the validity of the test method, 63 types of pervious pavement materials were evaluated. The permeability coefficients were compared before and after the sustainable permeability test. The quantity of contaminants used in the test corresponds to five years accumulation, and the vibration frequency and vibration time were set to 60 Hz and 60 s, respectively. The test results are shown in Fig. 10. The permeability coefficients before and after the test showed a high correlation (R2 = 0.88). Through the correlation equation the permeability coefficient after 5 years could be predicted from the coefficient of permeability before applying contamination. Furthermore, it will be possible to tentatively use the initial coefficient of permeability values to model permeability reduction due to clogging in a hydrological analysis. Although there were variations by the type of pervious pavement, the permeability coefficient decreased by 54% on average.
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7. Conclusions Clogging prevents pervious pavement from functioning properly because the pavement becomes impervious after a short period of service. In this study, to evaluate the sustainable permeability of pervious pavement in advance, the causes of clogging were investigated and a clogging simulation apparatus was developed. Furthermore, a test method for verifying the sustainability of infiltration which can predict and assess the permeability performance by years of service was presented. i. The clogging has been found to be greatly affected by the years of service, which means the cumulative quantity of contaminants. However, when pores are clogged to some degree, the change of the coefficient of permeability slows down. ii. Furthermore, the penetration characteristics of contaminants vary depending on whether there is vehicle vibration or whether rainwater permeates together with them. When the vibration frequency was set up from 20 Hz to 60 Hz, the pores were easily clogged with the increase in vibration frequency. The permeability had less influence on vibration with supplying increment amounts of cumulative contaminants. iii. To avoid the hydrological failure by clogging, infiltration maintenance job by periodic vacuum cleaning was suggested within two years after the pavement placed. When the pavement is almost completely clogged, cleaning is difficult and expensive. iv. When 63 types of porous concrete block pavers were evaluated with the proposed permeability test method, the coefficients of permeability before and after the test showed a very high correlation (R2 = 0.88) between them, and the coefficient of permeability decreased by 54% (maximum = 76%, minimum = 20%) on average. Based on these
findings, it will be possible to tentatively use the initial coefficient of permeability values to model permeability reduction due to clogging in the hydrological analysis. In the future, more research is needed to comparatively analyze the reduction trend of permeability and the findings of this study through continuous monitoring about pervious pavement materials installed on the roads. Acknowledgements This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korea government (MSIP) (No. 2014R1A2A2A01007697). References [1] C.F. Yong, D.T. McCarthy, A. Deletic, Predicting physical clogging of porous and permeable pavements, J. Hydrol. 481 (2013) 48–55. [2] T.H.F. Wong, Water Sensitive urban design – The story thus far, Aust. J. Water Resour. 10 (2006) 213–221. [3] M. Kayhanian, D. Anderson, J.T. Harvey, D. Jones, B. Muhunthan, Permeability measurement and scan imaging to assess clogging of pervious concrete pavements in parking lots, J. Environ. Manage. 95 (2012) 114–123. [4] C.J. Pratt, J.D.G. Mantle, P.A. Schofield, UK Research into the performance of permeable pavement, reservoir structures in controlling stormwater discharge quantity and quality, J. Water Sci. Technol. 32 (1995) 63–69. [5] V. Colandini, M. Legret, Y. Brosseaud, J.D. Balades, Metallic pollution in clogging materials of urban porous pavements, J. Water Sci. Technol. 32 (1995) 57–62. [6] ASTM C 1701/C 1701M – 09, Standard Test Method for Infiltration Rate of in Place Pervious Concrete, ASTM International, West Conshohocken, PA, 2009. [7] KS F 4419, Concrete Interlocking Block for Side Walk and Road, Korea Industrial Standards, 2009. [8] M. Amirjani, Clogging of Permeable Pavements in Semi-Areas (Master of Science thesis), Delft University of Technology, 2010. [9] T. Umeno, Estimation of tire–road friction by tire-rotational vibration model, R&D Rev. Toyota CRDL 37 (2002) 53–58. [10] Interpave. Guide to the Design, Construction and Maintenance of Concrete Block Permeable Pavements, sixth ed., The Precast Concrete Paving and Kerb Association, UK, 2010.