Construction and Building Materials

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1 Construction and Building Materials 42 (13) 5 10 Contents lists available at SciVerse ScienceDirect Construction and Building Materials journal homepage: The influence of Buton asphalt additive on skid resistance based on penetration index and temperature Sigit Pranowo Hadiwardoyo a,, Eky Supriadi Sinaga a, Husnul Fikri b a Department of Civil Engineering, Universitas Indonesia, Kampus UI Depok 16424, Indonesia b Department of Civil Engineering, Politeknik Negeri Bandung, Indonesia highlights " Modified method of measuring skid resistance to the effects of temperature. " Influence the level of asphalt penetration index in the asphalt concrete to the skid number. " Models of skid number caused by the temperature and the penetration index asphalt. " Contribution Buton Asphalt additive in asphalt penetration index value. article info abstract Article history: Received 9 July 12 Received in revised form 26 November 12 Accepted 17 December 12 Keywords: Skid resistance Asphalt concrete Temperature Skid resistance on pavement surfaces can affect the safety of road users and impact their travel efficiency. This value specifies the frictional forces on the wheels of vehicles that will avoid the occurrence of slip in wet or dry conditions. This study tested skid resistance using tools a Skid Resistance Tester and a British Pendulum Tester. Analyses were performed to evaluate the surface roughness of an asphalt concrete wearing course (AC-WC) with bitumen /70 and a Buton asphalt additive blend with the same aggregate composition. Buton asphalt additive is made by refining bitumen rocks with low penetration. The addition of this substance reduces the penetration of asphalt at 25 C. The tests were performed on wet surface conditions at a temperature ranging from C to 55 C and varying penetration index in asphalt concrete mixtures. The skid resistance value decreased with increasing surface temperature. The additive caused a change in the asphalt penetration index in asphalt concrete, resulting in a higher skid resistance value than that of virgin bitumen /70. Ó 13 Elsevier Ltd. All rights reserved. 1. Introduction The development of automotive technology has allowed users to drive at higher speeds on roads, but such technology requires good road conditions for safety. Surface roughness is one of these requirements. The skid resistance of a given surface is a function of the actual speed, and in normal highway conditions, the higher the speed, the lower the skid resistance [1]. Another dominating factor, especially in Indonesia, is weather conditions that can affect performance of a road surface. We know that a wet surface is more slippery than a dry surface. On dry pavement, the skid resistance is sufficient to counteract the friction demand in most cases. However, when the pavement is wet, the skid resistance diminishes considerably and may be insufficient depending on pavement conditions. Consequently, previous skid-related Corresponding author. Tel.: ; fax: address: sigit@eng.ui.ac.id (S.P. Hadiwardoyo). safety studies and testing procedures have focused on wet-pavement conditions [2]. To improve a road s surface roughness, engineers must focus not only on the asphalt pavement layer, but also on the concrete coating. When the surface of the concrete pavement surface wears down due to friction with vehicle tires, the surface roughness can be improved by coating the road with an asphalt concrete mixture. Pavement variables can be further classified as mix design variables (aggregate gradation, Marshall Stability, air voids, asphalt content, and others) or surface texture variables (macro- and microtexture). The relationship between skid resistance and pavement texture is complex, but micro-texture generally has more influence at lower speeds. Macro-texture becomes a dominant factor in skid resistance as speed increases. The correspondingly increased need for drainage channels on the pavement surface to prevent a buildup of water between the tire and pavement [3]. Other external factors that can affect skid resistance include dust, sand, oil, and the condition of the vehicle tire surface, which can reduce the contact between tire and road /$ - see front matter Ó 13 Elsevier Ltd. All rights reserved.

2 6 S.P. Hadiwardoyo et al. / Construction and Building Materials 42 (13) 5 10 Skid resistance is a very difficult parameter to estimate. The tire-pavement friction is affected by a large number of parameters, such as the tire type, tread pattern and depth, pressure and condition of tires, the vehicle suspension and braking system, speed, type, load and load distribution, temperature, existence of water and water film thickness, existence of soil, detritus or other substances on the pavement surface, driver experience, highway geometries, pavement age, traffic intensity, surface conditions, structural deficiencies, mix design, type of surface and aggregate petrography, angularity, hardness, density, gradation and size [4]. One of the most popular procedures used to evaluate the friction resistance of road surfaces is the Portable British Pendulum Tester, which is standardized in the ASTM E3 test method. The British Pendulum Tester is a dynamic pendulum impact type tester. That is based on the energy loss occurring when a rubber slider edge is propelled across a test surface [5]. Bazlamit and Reza [3] cited the work of Bianchini et al. [6] has been shown that the data expressing friction versus temperature have a linear curve fit. With an R 2 of , the resulting equation is: BPN T ¼ 125:2508 0:232T K where BPN T = British Pendulum Number at temperature T K and T K = pavement temperature value measured in degrees Kelvin. Correlations between skid number and BPN are available in the literature. The authors chose to utilize the following equation that indicates a linear relationship between SN and BPN [3]: SN ¼ 0:862ðBPNÞ 9:69 Experiments have been performed on asphalt concrete mixtures with the Buton Natural Asphalt (BNA) additive material to increase the asphalt s resistance to temperature. The results have shown that the addition of BNA has changed the value of the penetration asphalt at 25 C and led to a decreased. The existence of these changes has indicated the value of adding BPN at the same temperature [7]. Therefore, the goal of this study was to observe the effect of changes in temperature and the penetration index asphalt on skid resistance using a Skid Resistance Tester and British Pendulum Tester (Fig. 1). The changes to the value of penetration index were made by adding BNA to petroleum asphalt (/70) at different percentages. 2. Materials and methods The characteristics of asphalt concrete and cement concrete mixtures are dictated by the mechanical and physical properties of its constituent materials. Asphalt concrete mixtures consist of asphalt and aggregates in proportions meeting performance needs. One performance factor measured in this study is the skid resistance value. Fig. 1. Modified British Pendulum Skid Resistance Tester. ð1þ ð2þ The skid number does not indicate the stopping characteristics of the vehicle, driver, or climate condition, but it is a useful tool that can be employed to evaluate surface friction properties depending on aggregate types, asphalt mix design, and pavement construction methods [5]. The skid resistance value is influenced by aggregate and bitumen characteristics, including aggregate composition and bitumen content in asphalt mixtures, as well as physical properties such as asphalt penetration index, softening point, ductility and other factors that determine the performance of the mixture. In general, measured frictional resistance values have been negatively related to aggregate gap width and positively related to the magnitude of the sliding contact surface and the number of gaps within the sliding area [8]. The materials used in this study consisted of aggregates obtained from the Rumpin Bogor quarry in West Java and petroleum asphalt grade /70 from PT Pertamina in Indonesia. BNA was used as an additive to vary the penetration value Aggregate This study used an asphalt concrete wearing course mix (AC-WC) in which the largest aggregate size was 19 mm. The test results on the characteristics of the coarse aggregate and fine medium are displayed in Table 1. Only one aggregate gradation, shown in Fig. 2, was selected for use in the study Buton Natural Asphalt (BNA) Large rock asphalt deposits exist on Buton Island, South East Sulawesi, Indonesia, and are referred to locally as Aspal Buton (ASBUTON). The use of ASBUTON in Indonesian road infrastructure development is increasing because the deposits are estimated to be 677 million tons while current annual production is only approximately,000 tons [9]. ASBUTON is composed of two main elements, asphalt and minerals. The bitumen content of ASBUTON ranges from 13% to %. It is obtained by open pit mining in the form of boulders of many sizes [10]. BNA is produced by refining Buton Island rock asphalt to separate minerals and increase the bitumen content from 13 % to 55 %. BNA is more widely used as an additive because of its very low penetration as shown in Table 2. Researchers have worked to make the most of this natural asphalt by studying how to better perform the purification process and separate the bitumen content from the mineral content. Despite this process, the properties of BNA, as shown in Table 2, still include filler. This table includes the properties of Indonesian grade asphalt /70 for reference Bitumen blend Standard tests were performed on mixtures of bitumen /70 with additive BNA, as shown in Table 3, to measure penetration, softening point, fire point and other parameters. The addition of BNA lowered the penetration, ductility and fire point, but increased the softening point. Adding a certain percentage of BNA produced an asphalt mixture that was more resistant to the effects of increased temperature. Table 1 Coarse, medium and fine aggregate [11]. No. Laboratory test Method Results Coarse aggregate 1 Bulk specific gravity (Gsb) AASHTO T84/T Surface saturated dry gravity (SSD) AASHTO T84/T Apparent specific gravity (SG) AASHTO T84/T Absorption (%) AASHTO T84/T Los Angeles abrasion (%) AASHTO T Solubility (%) 98 7 Impact SNI Angularity >95 9 Flat and elongated particles (%) BS Medium aggregate 1 Bulk specific gravity (Gsb) AASHTO T84/T Surface saturated dry gravity (SSD) AASHTO T84/T Apparent specific gravity (SG) AASHTO T84/T Absorption (%) AASHTO T84/T Sand equivalent (%) AASHTO T Specific gravity ASTM C Fine aggregate 1 Passing no. 0 (%) Specific gravity ASTM C

3 S.P. Hadiwardoyo et al. / Construction and Building Materials 42 (13) Percent Passing (%) Sieve Size (mm) Fig. 2. Aggregate gradation used for asphalt concrete mixes. Table 2 Test results showing BNA properties. Fig. 3. Compaction sample for wheel tracking test. Laboratory test Method Unit BNA Indonesian asphalt /70 Penetration at 25 C ASTM-D5 0.1 mm Softening point ASTM-D-36 C Flash point (Cleveland) ASTM D-92 C Ductility at 25 C (cm) ASTM D-113 cm 1 >100 Specific gravity at 25 C ASTM D-70 g/cm Loss on heating (TFOT) % Penetration after TFOT ASTM-D5 % Filler content % 36.5 Table 3 Asphalt properties with different percentages of additive BNA [16,17]. No. Laboratory test Percentage of additive BNA % 25% % 35% % 1 Penetration at 25 C Softening point ( C) Flash point (Cleveland) Ductility at 25 C (cm) Specific gravity Loss on heating (TFOT) Penetration after TFOT Penetration Index Skid resistance measurement The factors affecting pavement skid resistance can be separated into four groups: vehicle factors, road surface factors, aggregate and load factors, and environmental factors. Road authorities can develop material and construction specifications that influence the second category, which in turn influences the micro- and macro-texture of an asphalt pavement surface [12]. A harsh surface pavement has an average micro-texture depth of 0.05 mm (50 lm). Micro-texture is measured directly by photomicrographs of the pavement surface. Indirectly, the value of British Pendulum Number (BPN) provides a good approximation of the pavement micro-texture size [4]. A needle-scale indicator shows the number listed on the scale plate measured with BPN units. The BPN s reading will be greater when the surface being tested is more resistant to friction. Each test must be performed four times when using natural rubber (British rubber) or five times when using synthetic rubber (AASHTO M 261) [13 15]. This study tested five types of asphalt concrete mixture with a specific aggregate gradation and different penetration index (PI) values [16,17], combined with hot mix at an optimum bitumen content of 5.9%. The samples were made using a mold wheel tracking test at a size of mm, compacted with a roller compacter (Fig. 3) and cut into 15 sections corresponding to the size of the skid resistance test ( mm) (Fig. 4). The specimens with five different penetration index ( 0.34, 0.22, 0.07, and 0.351) were tested at temperatures of C, 35 C, C, 45 C, 50 C and 55 C (type 1). Each sample used for the experiment of the temperature measurements carried out five times, but at temperatures of 55 C where any changes in temperature used different samples (type 2). The tests were performed by submerging samples in water baths heated by an electric heater as shown in Fig. 5. The water level was set at the surface of the specimen by using the faucet on the tub. This method was used to ensure that the temperature was evenly distributed on the sample. Fig. 4. Briquette sample for British Pendulum skid resistance test. The surface temperature was measured according to the requirements for testing temperature as shown in Fig. 5. The skid resistance test was performed by removing the pendulum once the bath reached the desired temperature. 3. Results and discussion The results of testing on the five types asphalt concrete mixtures with different penetration index and at different temperature changes are shown in Table 4. BPN value measurement could not be performed at temperatures approaching the softening point of asphalt concrete pavement. The BPN value was generated from the Skid Resistance Tester and British Pendulum Tester and converted into a skid number (SN) using Eq. (2). The values in Figs are in SN units Effect of asphalt penetration index The SN of asphalt concrete mixture specimens increased with increasing asphalt penetration index (Fig. 6). Sixth curve by applying different temperatures has shown a change in its characteristics. The square polynomial curve for the SN values versus asphalt penetration index in the five sample types, with R 2 values of , as shown in Table 5. The asphalt concrete mixture with an asphalt penetration index of 0.34 had a smaller SN than in the mixture with a PI of It showing that a mixture s SN can be increased by increasing its PI. Than with a lower PI, the SN also decreased in asphalt concrete mixtures. Viewed from the sixth curve between SN and PI values (Fig. 6) shows the form of equation (Table 5) there is a maximum value at dy/dx = 0, and thus increase the value of PI at this condition as the optimal value. SN optimum value this study reached at a temperature of C in the PI of Effect of temperature change Fig. 7 shows a nonlinear regression between SN and temperature 55 C with R 2 values of (Table 6). The

4 8 S.P. Hadiwardoyo et al. / Construction and Building Materials 42 (13) Model development To examine the relationships between skid resistance, temperature and asphalt penetration index, the authors used the concept of polynomial regression, which has shown results more in line with test data in the formation of curves. The skid number was taken as an independent variable, and the temperature and asphalt penetration index were the dependent variables. Quadratic polynomial regression models are acceptable for both high- and low-penetration index asphalt pavements. The data showed that the curved relationships between the SN and temperature and the SN and asphalt penetration index showed a fairly strong correlation (R 2 = ). In general, the equation is formed as follows: Y ij ¼ a ij X 2 ij þ b ijx ij þ c ij ð3þ Fig. 5. Water bath with heater box. regression curves in asphalt concrete mixtures with low asphalt penetration index ( 0.34 and 0.22) tended to be close to linear, but the mixes with higher PIs ( 0.07, 0.14 and 0.35) had nonlinear curves. These results show that linear regression between the SN and temperature changes occurs only in asphalt concrete mixtures with asphalt PIs smaller than Observations on the shape of the curve and equation (Table 6), the increase in the value of PIs will have an impact on increasing the value of SN. However, this asphalt to be more sensitive to the effects of temperature. The increase in temperature in the asphalt mixture with high PI will decrease faster than the value of SN asphalt mixtures with lower PIs values. Asphalt mixtures with high PI value creates realistic SN higher also, but be aware of the decline can occur due to increased temperature. In this study, the use of additive BNA by 35 % give a higher SN. This value is still higher despite the change of temperature compared with AC-WC asphalt mixtures without additive. where a ij, b ij and c ij are the regression coefficients, i is the coefficient of temperature ( 55 C) and j is the coefficient of asphalt penetration index ( 0.34 to 0.35). The quadratic polynomial regression between skid resistance and asphalt penetration index gave the regression coefficients a j, b j and c j shown in Table 5. Then, the coefficients of the equation were obtained by varying the temperature relationships to provide a linear regression with R 2 = as shown in Figs The relationship resulted in the following equations: a ij ¼ 1:452X i 102:7 b ij ¼ 0:286X i þ 38:65 c ij ¼ 0:594X i 78:15 The relationship between the SN equations with the temperature and asphalt penetration index in Eq. (3) was obtained by combining Eqs. (4) (6): ð4þ ð5þ ð6þ Table 4 BPN values for different temperatures and asphalt penetration index. Sample type PI Temperature C 35 C C Average Temperature 45 C 50 C 55 C Average PI: asphalt penetration index.

5 S.P. Hadiwardoyo et al. / Construction and Building Materials 42 (13) Skid Number (SN) Penetration Index Fig. 6. Relationship between skid number and asphalt penetration index. coef. c temperature o C Fig. 10. Relationship between temperature and c ij coefficient regression of asphalt penetration index. Skid Number (SN) PI PI PI 0.14 PI 0.35 PI Table 5 Polynomial squared of asphalt penetration index for different temperatures. Temp ( C) Equation R 2 y = 54.43x x y = 52.39x x y = 52.84x x y =.80x x y =.01x x y = 25.43x x Temperature ( o C) Fig. 7. Relationship between skid number and temperature ( C). coef. a Y ij ¼ð1:452X i 102:7ÞX j þð 0:286X i þ 38:65ÞX j þð 0:594X i 78:15Þ temperature o C Fig. 8. Relationship between temperature and a ij coefficient regression of asphalt penetration index. coef. b temperature o C Fig. 9. Relationship between temperature and b ij coefficient regression of asphalt penetration index. where X i is the dependent variable temperature (t in C) and X j is the dependent variable asphalt penetration index (PI). From this, the authors proposed a model Eq. (7) as follows: ð7þ Table 6 Polynomial squared of temperature for different asphalt penetration index. Penetration index Equation R y = 0.002x x y = 0.001x x y = 0.010x x y = 0.013x x y = 0.017x x SNMeasured Value SN ¼ 1:452ðt 70:73ÞPI 2 0:286ðt 153:5656ÞPI 0:594ðt 131:5656Þ where t = temperature C and PI = asphalt penetration index. Comparison between the experimental results and calculations using the model confirmed the appropriateness of the very strong relationship shown in Fig. 11 with a value of R 2 = Conclusions o C 35 o C o C 45 o C 50 o C 55 o C SN Model Fig. 11. Correlation of skid number between experimental results and model. This study produced methods to determine the effects of the asphalt penetration index and the temperature on the skid number. ð8þ

6 10 S.P. Hadiwardoyo et al. / Construction and Building Materials 42 (13) 5 10 The following conclusions were made based on the experimental results: 1. Samples were immersed in a tub filled with water heaters and equipped with control devices, which gave an accurate measurement of the skid resistance value at the sample surface temperature. The measurements were performed in two directions, from the lowest temperature to highest temperature and vice versa. 2. A model was successfully developed to obtain skid number values based on temperature and asphalt penetration index. 3. Skid number values decreased with increasing temperature. The measurement of skid resistance could only be performed at a position below the softening point of the asphalt because the surface was destroyed when attempting to measure resistance at temperatures near the softening point. 4. The skid number could be controlled based on the resistance needs of the asphalt concrete and its asphalt penetration index while accounting for the effects of fluctuating ambient temperatures. 5. BNA could play an additive role in increasing the resistance of asphalt mixtures while accounting for the effects of temperature and increasing asphalt penetration index. Acknowledgements The authors express their gratitude to the Directorate for Research and Community Service at the Universitas Indonesia, which provided funding in a 10 Research Grant for this research activity. References [1] Fulop IA, Bogardi I, Gulyas A, Csicsely-Tarpay M. Use of friction and texture in pavement performance modeling. J Transport Eng 00;126(3). [2] Pardillo JM, Pina RJ. An assessment of the skid resistance effect on traffic safety under wet-pavement conditions. Accid Anal Prevent 09;41: [3] Bazlamit SM, Reza F. Changes in asphalt pavement friction components and adjustment of skid number for temperature. J Transport Eng 05;131(6): [4] Panagouli OK, Kokkalis AG. Skid resistance and fractal structure of pavement surface. Chaos, Solitons Fract 1998;9(3): [5] Asi I. Evaluating skid resistance of different asphalt concrete mixes. Build Environ 07;42: [6] Bianchini A, Heitzman M, Maghsoodloo S. Evaluation of temperature influence on friction measurements. J Transport Eng 11;137(9):6 7. [7] Hadiwardoyo SP, Fikri H. Kontribusi buton natural aspal (BNA) terhadap kinerja campuran beton aspal. In: 9th National conference on pavement development, indonesian road development association, Jakarta, November 11. [8] Fwa TF, Choo YS, Liu YR. Effect of aggregate spacing on skid resistance of asphalt pavement. J Transport Eng 03;129(4). [9] Subagio BS, Siswosoebrotho BI, Karsaman RH. Development of laboratory performance of indonesia rock asphalt (ASBUTON) in hot rolled asphalt mix. Proc Eastern Asia Soc Transport Stud 03;4(October). [10] Hanafi LA. Kajian deformasi permanen dan modulus resilien campuran beton aspal lapis pengikat (AC-BC) memakai buton granular asphalt (BGA) lawele. Master thesis, Bandung Institute of Technology, Bandung, Indonesia, June 10. [11] American association of state highway and transportation officials (AASHTO), AASHTO guide for design of pavement structures, Washington DC; [12] Rezaei A, Masad E, Chowdhury A. Development of a model for asphalt pavement skid resistance based on aggregate characteristics and gradation. J Transport Eng 11;137(12): [13] Indonesian National Standardization Agency. Test method of pavement surface roughness using a tool British Pendulum Tester (BPT), SNI 4427; 08. [14] ASTM D1559. Standard test method for resistance to plastic flow of bituminous mixtures using marshall apparatus; [15] ASTM E Standard test method for measuring surface frictional properties using the British Pendulum Tester, vol West Conshohocken (PA): ASTM; 00. [16] ASTM D5-97. Standard test method for penetration of bituminous materials; [17] Whiteoak D. Shell bitumen handbook. London (UK): Shell Bitumen; 1990.