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Researchers
Abstract
Keywords
Introduction
Materials and Methods
Result and Discussions
Conclusions
Acknowledgement
References
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Sam Ang Keo1
1 Cerema, Research team ENDSUM, 23 Amiral Chauvin Avenue, 49130 Les Ponts-de-Cé, France, sam-ang.keo@cerema.fr / keo_samang@yahoo.com
Chan-Young Yune2
2 Department of Civil Engineering, Gangneung-Wonju National University, Jukheon-gil 7, Gangneung-si, Gangwon-do 25457, Republic of Korea, yune@gwnu.ac.kr
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Abstract
In South Korea, tunnels are essential infrastructures for transportation system because most parts of the country are covered by mountains. Facing to cold climate, many damages have occurred at various parts of the tunnels, especially frost damage which is mainly related to temperature inside the tunnels. That is why monitoring the temperature inside the tunnels, especially during winter, is crucial. The paper presents Structural Health Monitoring (SHM) of the tunnels in cold region by analyzing temporal temperature inside 10 tunnels in Ganwon province (the coldest region in South Korea). In this research, three short tunnels (less than 500 m long), four medium-length tunnels (from 500 m to 1000 m long), and three long tunnels (greater than 1000 m long) were investigated. The temperature inside the tunnels (one-way, and two-way) were measured during winter season by using iButton sensors installed on the surface of the tunnel linings. The temperature distributions obtained from the sensors were used for analysis with data (meteorological and transportation) obtained from the traffic monitoring system and meteorological administration of South Korea. The results from the analysis show that the highest temperature gradient occurred at 30 m from the entrance or the exit for the short and medium-length tunnels, and at approximately 100 m from the entrance or exit for the long tunnels. The results also show that the vehicle induced wind (related to traffic volume) and its velocity as well as the rainfall are the main factors influencing the temperature in the tunnels.
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| Keywords: Structural Health Monitoring (SHM), Frost hazard, Tunnels, Field measurement, Cold region, Temperature distribution, iButton sensors. |
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Introduction
Tunnels are compulsory elements of the transportation system in mountainous regions. These elements efficiently facilitate various traffic flows throughout the mountains. During the service life, the infrastructures may have damages due to different factors. In cold regions, frost hazard is really critical for the tunnels (for the linings) [1], and it is related to temperature change inside the tunnels [2], [3]. Due to the relationship between the damage and the temperature inside the tunnels, field temperature investigations have been conducted [4] with many tunnels in the Gangwon province of South Korea (which is a cold area) where risk to frost damage is really high. However, in the previous studies, there were no detail of the temporal temperature variation.
In the present paper, temperatures in ten tunnels in different locations of the Gangwon province are discussed in detail. The temperature degrees were obtained from continuous measurement campaigns during the whole winter season (the most critical climate for the frost hazard of the tunnels) with temperature sensors. Regarding to the length, there are three types of tunnels in the study: short (less than 500 m long), medium (from 500 m to 1000 m long), and long (longer than 1000 m).Transportation and meteorological data is also analyzed for the discussing different effects on the temperatures. Novelty of the study lies in detailed temperature distribution inside the investigated tunnels during the whole winter, which allows to locate the most critical areas facing to frost hazard in the tunnels (the minimum temperature is below zero degree).
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Materials and Methods
1 - Sensor for temperature measurement
The temperatures inside the tunnels were measured using iButton sensors from Maxime integrated (Figure 1). It is a high-resolution model (0.0625 °C) for low temperature applications (from −40 to +85 °C). The temperatures were recorded at every hour.
: Structural Health Monitoring (SHM), Frost hazard, Tunnels, Field measurement, Cold region, Temperature distribution, iButton sensors.
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| Figure 1. iButton sensors, (a) Dimensions in mm, (b) Photos of the sensors |
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| The sensors used for measuring the temperatures are distributed in the tunnels as shown in Figure 2(c). |
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| Figure 2. Distribution of the sensors for the temperature measurement, (a) cross-section, (b) longitudinal, (c) position of the sensors inside the tunnel |
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Positions of the sensors installed in one-way (on the left) and two-way (on the right) tunnels are shown in Figure 2(a). The sensors were always placed on the right-hand side (in each driving direction) for both types of tunnel: on one side for one-way tunnels, two sides for two-way tunnels. The positions of the sensors along the length of the tunnels are shown in Figure 2(b). Two sensors were placed outside each tunnel (or each measured side of the tunnel): one sensor at 1 m from the entrance, and another sensor at 1 m from the exit. Apart from both sensor positions on each measured side, the sensors were distributed at every 30 and 40 m until 100 m in distance. From those points, regular intervals of 100 m were used.
- Locations of the investigated tunnels
Ten tunnels of varying lengths and locations in the Gangwon province were selected as shown in the Figure 3. In South Korea, transportation tunnels have an average length of 700 m, and can be classified as short (<500 m), medium (between 500 m and 1000 m), and long (longer than 1000 m) [4]. In the present study, three short, four medium-length tunnels, and another three long ones. Only two tunnels (one medium and one long) are two-way tunnels. All other tunnels are one-way. Locations, vehicle driving directions, and tunnel lengths are shown in Table 1.
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| Figure 3. Locations of the investigated tunnels |
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Table 1. Tunnel length, location and number of measuring sensors
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N°
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Tunnel Name
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Location
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Tunnel direction
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Tunnel length
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Number of Sensors
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(m)
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(EA)
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1
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Gohan (up)
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Jeongseon-gun, Gangwon
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One-way
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505
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12
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2
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Macha1 (up)
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Samcheok-si, Gangwon
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One-way
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435
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11
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3
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Seockhang 1 (up)
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Yeongwol-gun, Gangwon
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One-way
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960
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13
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4
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Youngwol 1 (down)
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Yeongwol-gun, Gangwon
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One-way
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381
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11
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5
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Dutgaesu (up&down)
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Pyeongchang-gun, Gangwon
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Two-way
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650
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12
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6
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650
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12
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7
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Cheoljeong (up)
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Hongcheon-gun, Ganwon
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One-way
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326
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10
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8
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Maeji (up)
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Wonju-si, Gangwon
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One-way
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690
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13
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9
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Jochimryeong (up&down)
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Inje-gun, Gangwon
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Two-way
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1132
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15
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10
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1132
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15
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11
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Misiryeong (down)
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Inje-gun, Gangwon
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One-way
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3610
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25
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12
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Misiryeong (up)
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Goseong-gun, Gangwon
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One-way
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3620
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25
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Result and Discussions
1- Temperature inside the tunnels
Figure 4 shows the mean temperature for all positions along the length of all 10 tunnels in January (the coldest month according to the collected temperature degrees). The temperature in this month almost had the same distribution as December for all tunnels: only Dutgaesu (Up and Down) and Jochimryeong (Up and Down) had a steady downward tendency of temperature along their length. Moreover, the highest temperature variation was still at the tunnel entrance and exit for all the tunnels.On the other hand, Gohan (Up) had the lowest temperature at the tunnel entrance in this month, which was approximately -4.8 °C, whereas the lowest temperature at the tunnel exit was in Dutgaesu (Down) at -5.3 °C.
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| Figure 4. Mean temperature for all the tunnels in January 2017 |
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2 - Analysis incorporated with meteorological and transportation data
Recent studies showed that the analysis of field temperature measurements of tunnels should consider various effects such as convection-conduction [5], air flow inside the tunnel [6], ortrain-induced winds [7]. For these reasons, the results on temperature distribution were analyzed with meteorological and transportation data obtained from the traffic monitoring system and meteorological administration of South Korea. The analysis was performed for one full month, because the temperature in other months was affected in the same way.
In this study, the analyzed data in December for three tunnels is presented. Figure 5 shows the data for Seockhang 1 (Up) tunnel.
The volume of vehicular traffic is represented by the black wavy curve (in Figure 5a) as a function of time (the units are hours). The temporal variation of the temperature exhibits the same tendency as the air temperature inside the tunnel. Moreover, there is a concordance between the fluctuation of those temperature variations and the vehicle traffic volume. Obviously, the temperature curves reach their maximum peaks at the same instant as those of the traffic volume. The temporal gradient between 30 and 930 m from the tunnel entrance, and between the entrance and the mid-length of the tunnel, are shown in Figure 5b (with the corresponding temporal traffic volume). The gradient between the entrance and mid-length position (in/out temperature variation) also displayed a cyclical variation conforming to the fluctuations of traffic volume. The gradient between 30 and 930 m from the entrance displayed a contrasting tendency to that between the entrance and mid-length position, because the temperature at 930 m was higher than at 30 m (an increasing temperature tendency along the length of the tunnel). On the other hand, the fluctuation of all these temperature variations also changed according to the wind velocity (Figure 5c) and the wind direction (Figure 5d) simultaneously: from 500 to 560 h, the wind velocity increased to 7.5 m/s (higher than at 450 h) with a daily rainfall of approximately 17.5 mm. Further, when the wind direction was 180º to the tunnel and the temperature was above zero, the variance of the temperature gradient between 0 and 480 m was eliminated. |
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Figure 5. Data in December for "Seockhang 1" (Up)
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Conclusions
In the present study, temperatures inside 10 tunnels in South Korea were monitoring during a whole winter by using iButton sensors. The temporal temperatures obtained from the measurements were analyzed. Incorporated with meteorological and transportation data, the following conclusions can be drawn:
• For the short and medium tunnels: the highest temperature gradient occurred between the tunnel entrance and 30 m from the tunnel entrance, and between the tunnel exit and approximately 30 m from the tunnel exit.
• For the long tunnels, the highest gradient is between the entrance and 100 m from the entrance, and between the exit and approximately 100 m from the tunnel exit
• The form of the temporal temperature along the length of the tunnel corresponds to that of the vehicular traffic volume in the tunnel, showing that both the temperature gradient and distribution are affected by vehicular traffic volume
• The fluctuation of the temporal temperature distribution inside the tunnel may be modified or eliminated by wind velocity, wind direction, and the presence of rainfall.
Finally, the wind induced by vehicle traffic, the wind velocity and direction, and the presence of rainfall are the main factors which influence the temperatures inside the tunnels.
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Acknowledgement
The authors would like to acknowledge The Ministry of Education of South Korea for the financial support through the Basic Science Research Program with the National Research Foundation of Korea (2021R1A6A1A03044326).
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References
[1] Z. Ji, K. C. Lu, and C. C. Ma, ‘Classification, Causes of Tunnel Frost Damages in Cold Region and Several New Technologies to Prevent them’, Appl. Mech. Mater., vol. 170–173, pp. 1504–1510, May 2012.
[2] Y. Lai, Z. Wu, S. Zhang, W. Yu, and Y. Deng, ‘Study of Methods to Control Frost Action in Cold Regions Tunnels’, J. Cold Reg. Eng., vol. 17, no. 4, pp. 144–152, Dec. 2003.
[3] R. Xing, S. Jiang, and P. Xu, ‘Long-term temperature monitoring of tunnel in high-cold and high-altitude area using distributed temperature monitoring system’, Measurement, vol. 95, pp. 456–464, Jan. 2017,
[4] K.-J. Jun, Y.-C. Hwang, and C.-Y. Yune, ‘Field measurement of temperature inside tunnel in winter in Gangwon, Korea’, Cold Reg. Sci. Technol., vol. 143, pp. 32–42, Nov. 2017.
[5] Y. Zeng, K. Liu, X. Zhou, and L. Fan, ‘Tunnel temperature fields analysis under the couple effect of convection-conduction in cold regions’, Appl. Therm. Eng., vol. 120, pp. 378–392, Jun. 2017.
[6] W. Li, Y. Wu, H. Fu, and J. Zhang, ‘Long-term Continuous In-situ Monitoring of Tunnel Lining Surface Temperature in Cold Region and Its Application’, Int. J. Heat Technol., vol. 33, no. 2, pp. 39–44, Jun. 2015.
[7] X. Zhou, Y. Zeng, and L. Fan, ‘Temperature field analysis of a cold-region railway tunnel considering mechanical and train-induced ventilation effects’, Appl. Therm. Eng., vol. 100, pp. 114–124, May 2016.
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