PDF Development of Asphalt Pavement Temperature Profile Model for ... - UNUD

(1)

Development of Asphalt Pavement Temperature Profile Model

for Tropical Climate Conditions in the Eastern Bali Region, Indonesia

I Made Agus Ariawan^a, Bambang Sugeng Subagio^b, Bagus Hario Setiadji^c

aUdayana University, Bali-Indonesia, Diponegoro University, Semarang-Indonesia

bBandung Institute of Technology, Bandung-Indonesia; E-mail:[email protected]

cDiponegoro University, Semarang-Indonesia; E-mail: [email protected]

Abstract. The temperature in the asphalt pavement layer varies which is influenced by climatic environment factors, such as air temperature, humidity, solar radiation, wind speed and the reflection of the pavement surface. Indonesia has a specific tropical climate characteristics and a temperature observation station was placed on the national road segment of Singaraja - Amlapura (Km 81 + 100 - Km 95 + 00) which is located in Karangasem regency in the eastern of Bali Region, Indonesia, to monitor air temperature, humidity and temperature of asphalt pavements at depths of 00 mm, 20 mm and 70 mm. It is obtained that, there was a positive linear relationship between the air temperature and asphalt pavement temperature. Based on the statistical analysis and test models, it can be concluded that both variables have a high correlation, and most of the asphalt pavement temperature variation can be explained by those two independent variables.

Keywords : Air temperature, relative humidity, asphalt pavement temperature, Bali Region.

1. INTRODUCTION

The temperature in the asphalt pavement layer varies because it is influenced by several factors, namely: air temperature, solar radiation, wind speed, and the reflection of the pavement surface. Temperature is one of the most important environmental factors that significantly affect the mechanical properties of asphalt mixtures (Matic et al., 2013). Air temperature variation directly affects the temperature of the asphalt pavement layer. The temperature distribution in the cross section of asphalt pavement layer is important to be understood in relation to the different characteristics of strength in a variety of asphalt pavement design. Indonesia has a specific climate characteristics, the territory of Indonesia is located on a small latitudes (6⁰ LU - 11⁰ LS) which is crossed by the equator. With this physical condition, Indonesia has a tropical climate which is characterized by hot or receives relatively long sunshine throughout the year. Indonesian territory traversed by two movements of the monsoon (west monsoon and east monsoon) which causes Indonesian region experienced two seasons, i.e. the rainy season in the period from October to March and the dry season in the period from April to September, and about 70% of the Indonesia territory in the form of water, so that Indonesia has a marine climate with characteristics such as: air is often cloudy, wet (high humidity) and has a high rainfall. Therefore, this study was conducted to investigate the asphalt pavement temperature profile for case study of Singaraja - Amlapura (Km 81 + 100 - Km 95 + 00) road segment, which is located in Karangasem regency in the eastern of Bali island, Indonesia.

(2)

2. CLIMATES IN BALI ISLAND

Asphalt pavement temperature profile is directly influenced by environmental factors such as energy balance within the conceptual shown in Figure 1 (Matic et al., 2013). Environmental factors include climatic conditions such as air temperature, humidity, wind speed, solar radiation, evaporation, long wave radiation and back radiation and absorption of heat beneath the asphalt pavement. The difference in latitude causes a region has a distinctive climate (tropical, sub-tropical climate, medium climate and cold climates) as shown in Figure 2.

Figure 1. Energy balance at the surface asphalt pavement (in Matic et al., 2013)

Figure 2. Climate types based on the latitude

The importance of temperature distribution with respect to the determination of pavement grade asphalt performance and capacity of its structure, in the last decade of research on this topic is still widely developed in many countries with different climates, such as in the United States, Oman, Saudi Arabia, Spain, Iran, China, Portugal, Lithuania, Serbia (Diefenderfer et al. (2003); Rathke & Macpherson (2006); Hassan et al. (2005); Wahhab et al.

(2001); Velasquez et al. (2008); Jia et al., (2008); Tabatabaie et al. (2008); Minhoto et al.

(2009); Paliukaite et al. (2011); Matic et al. (2011). In some studies, the models were developed by considering the same parameters. Previous studies were conducted in subtropical climate location which has four seasons (spring, summer, autumn and winter).

The model needs to be extended to other geographical location such as Indonesia which has a tropical climate. The tropical climate characteristic is receiving heat from the sun for a relatively longer time in a year, so that the average air temperature is high. Indonesia has two seasons: the rainy season in the period from October to March and the dry season in the

(3)

Indonesia has a marine climate with features such as: the air is often cloudy, rainfall occurrence and high humidity.

3. RESEARCH METHODOLOGY

The observation, measurement and recording of air temperature, air humidity and temperature of the asphalt pavement were conducted directly in the field by using a thermocouple which was equipped with a data logger. In general, the measurement system is shown in Figure 3 and the equipment used in this study is described as follows:

1) A type of DS18B20 is used for sensors and signal conditioning. This is a digital temperature sensor with a resolution between 9 and 12 Bit ± 0.5 ⁰C. In addition, it can be used to measure a temperature between 55 and 125 ⁰C. This sensor has a data communication system using a BUS 1 wire lane.

2) A microcontroller of ATMEGA 8 is used for signal processing. This part serves as signal processing and data communication control between sensors and computer.

3) An interface is a part of data logger which connecting between the microcontroller and a computer in a serial data format.

4) A computer monitor is used to display data measurement result using a customized application program.

5) A data recorder is used to record the measured data. In this study, a customized application program is developed using a visual basic programming language.

Figure 3. Temperature measurement system

4. DATA COLLECTIONS

4.1 Station of Pavement Monitoring

Mikrokontroller ATMEGA 8 Sensor

Sensor Sensor Sensor Sensor Sensor Sensor Sensor

Power Supply

BUS 1 wire Interface RS232

(4)

An observation station was placed on the national road of Singaraja - Amlapura (Km 81 + 100 - Km 95 + 00) segment, which is located in Karangasem regency in the eastern region of the Bali island, Indonesia (Figure 4) to monitor and record the fluctuations in the air temperature, humidity and temperature at various depths of the pavement. To minimize the influence of other climatic factors on pavement humidity, measurements were conducted during the sunny weather in the dry season.

Figure 4. Map of the study location on the Bali national road

Observations and measurements were made every day for the total of seven days in the month of August 2014 with the temperature readings was recorded every 30 minutes.

Asphalt pavement temperature measurements were carried out on the overlay layer that is on the surface of the asphalt pavement (00 mm), in 20 mm depth, which was in the middle of a thick layer of the surface (asphalt concrete wearing course - AC-WC) and in 70 mm depth, which was in the middle layer between (asphalt concrete binder course - AC-BC). Local air temperature was also measured at the height of approximately 1.5 meters above the surface of the asphalt pavement. Figure 5 shows the structure of asphalt pavement layer and position of the sensors to measure pavement temperature, while Figure 6 shows the position of the sensor for measuring temperature and humidity.

Figure 5. Sensors position for measurement of asphalt pavement temperature

A measurement sensor was connected to the signal processor using a microcontroller of ATMEGA 8 as shown in Figure 7. This was used to be the signal processing and data communications controller between sensors. In a serial data format, an interface connected the microcontroller with a computer to display and record the measured data through a customized application program developed by SAGA Technology as shown in Figure 8.

(5)

Figure 6. Sensor position for air temperature and relative humidity measurement

Figure 7. A Microcontroller of ATMEGA 8 Figure 8. Data recorder with a customized application program of SAGA Technology

5. RESULTS AND DISCUSSION

5.1 VARIATION OF TEMPERATURE AND HUMIDITY

Temperature and humidity data were collected for seven days in the sunny weather conditions in the month of August 2014, the pattern of hourly value variations are shown in Figure 8 and Figure 9. For the average values of air temperature, starting at 7:00, the air temperature tend to increase with the average maximum value of 32.99 ⁰C at 13:00, and after that the air temperature tend to decrease with the average minimum value of 24.35 ⁰C at 06:00. For the average value of the air humidity, the pattern is inversely proportional to the air temperature. The increase in humidity values started to occur from 17:00 until the average maximum value of 94.05% at 06:00 and after that it tended to decrease until reached a minimum value of 69.60% at 13:30.

Comparison between the average value of the data variation of air temperature and the temperature of the asphalt pavement measured on the surface (00 mm), in 20 mm depth and in 70 mm depth are shown in Figure 10 to Figure 13. It can be seen that for all values of temperature, a similar pattern occurred and follow the pattern of variation in air temperature.

A process of increasing and decreasing of the temperature occurred in the relatively same time scale. Along with the increase of the air temperature, the temperature of the asphalt

Sensor position

Road pavement Subgrade 1 – 2 meter

(6)

pavement at all depths have also increased with a high increase occurred during the period of 10:00 to 14:00.

Figure 8. Variations of hourly air temperature Figure 9. Variations of hourly relative humidity

Figure 10. Variations of hourly pavement temperature at 00 mm depth

Figure 11. Variations of hourly pavement temperature at 20 mm depth

Figure 12. Variation of hourly pavement temperature at 70 mm depth

Figure 13. Comparison between hourly average of air temperature, Humidity and asphalt pavement temperature

(7)

The average value of the maximum temperature in the T.00 mm = 59.37 ⁰C (14:00), T.20 mm = 53.06 ⁰C (14:30) and T.70 mm = 48.12 ⁰C (15:00). Time difference for maximum value of the temperature in the asphalt pavement layer was due to the time required in the process of heat conduction. For the average value of the minimum temperature, the T.00 mm

= 25.00 ⁰C (6:30), T.20 mm = 25.31 ⁰C (7:00) and T.70 mm = 27.31 ⁰C (7:00). Based on these data, it is interesting to note that the temperature in the asphalt pavement tend to be higher than the air temperature. During the heating process, response of the first layer is faster than the underlying pavement layers so that the temperature is higher. The same thing happened in the cooling process, so in a certain period of time, the temperature of the first layer is lower than the underlying pavement layers.

Figure 14. T.Amb vs T.00 mm in heating and cooling process.

Figure 15. RH vs T.00 mm in heating and cooling process.

(8)

The relationship between the average hourly air temperature and average hourly pavement temperature at depths of 00 mm, 20 mm, 70 mm is described in terms of patterns of heating and cooling on asphalt pavement structure as shown in Figure 14 and Figure 19.

5.2 MODEL DEVELOPMENT

Development of pavement temperature model used air temperature and humidity as independent variables. The model was developed in depth of 00 mm, 20 mm and 70 mm.

Table 1 shows the average value, standard deviation, mean, minimum and maximum for all variables.

Tabel 1. Summary statistics for all variables

T.Amb RH T.00 mm T.20 mm T.70 mm N

Valid 48 48 48 48 48

Missing 0 0 0 0 0

Mean 26.4068 80.4380 32.5214 31.8201 32.7251 Std. Error of Mean .34785 1.42096 1.40639 1.16889 .89345

Median 25.4690 85.0789 27.7357 28.0479 30.2361

Mode 23.72 63.40 24.02 24.37 26.32

Std. Deviation 2.40997 9.84472 9.74377 8.09827 6.19003 Variance 5.808 96.919 94.941 65.582 38.316

Minimum 23.72 62.45 24.02 24.37 26.32

Maximum 30.84 90.38 53.60 48.67 45.21

Sum 1267.53 3861.02 1561.03 1527.37 1570.80 Table 2. Variables correlation matrix

T.Amb RH T.00 mm T.20 mm T.70 mm T.Amb

Pearson Correlation 1 -.996^** .949^** .934^** .785^**