• Journal of Korean Tunnelling and Underground Space Association
• /
• v.13 no.1
• /
• pp.1-8
• /
• 2011

Spray density of the water spray system which is installed in long road tunnels and hazardous vehicle tunnels is applied without proper performance assessment process. In this study, the requirements of Spray Density Guidelines at the standard pressure is investigated through spray test set up the nozzle of a water spray system in a simulated road tunnel. The results showed that all the nozzles used in the test area did not meet the requirements of the Guidelines. The absence of performance test codes and inspection process on the nozzle at real scale in tunnels may have caused this practice. Therefore, it is suggested that the performance test regulations of the nozzle on the water spray system is established in order to properly assess the system performance.

• Journal of Positioning, Navigation, and Timing
• /
• v.6 no.4
• /
• pp.159-166
• /
• 2017

The position of autonomous driving vehicle is basically acquired through the global positioning system (GPS). However, GPS signals cannot be received in tunnels. Due to this limitation, localization of autonomous driving vehicles can be made through sensors mounted on them. In particular, a 3D Light Detection and Ranging (LIDAR) system is used for longitudinal position error correction. Few feature points and structures that can be used for localization of vehicles are available in tunnels. Since lanes in the road are normally marked by solid line, it cannot be used to recognize a longitudinal position. In addition, only a small number of structures that are separated from the tunnel walls such as sign boards or jet fans are available. Thus, it is necessary to extract usable information from tunnels to recognize a longitudinal position. In this paper, fire hydrants and evacuation guide lights attached at both sides of tunnel walls were used to recognize a longitudinal position. These structures have highly distinctive reflectivity from the surrounding walls, which can be distinguished using LIDAR reflectivity data. Furthermore, reflectivity information of tunnel walls was fused with the road surface reflectivity map to generate a synthetic reflectivity map. When the synthetic reflectivity map was used, localization of vehicles was able through correlation matching with the local maps generated from the current LIDAR data. The experiments were conducted at an expressway including Maseong Tunnel (approximately 1.5 km long). The experiment results showed that the root mean square (RMS) position errors in lateral and longitudinal directions were 0.19 m and 0.35 m, respectively, exhibiting precise localization accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.5
• /
• pp.637-644
• /
• 2016

This paper is a follow-up to previous papers entitled, "Development of Tunnel-Environment Monitoring System and Its Installation" I [1] and II [2]. The target tunnel of these studies is the Solan Tunnel, which is a loop-type, single-track, 16.7-km-long tunnel located in mountainous terrain and passing through the Baekdudaegan mountain range. It is an ordinary railway tunnel designed for both freight and passenger trains. We analyzed the environmental conditions of the tunnel using temperature and humidity data recorded over approximately one year. The data were recorded using the Tunnel Rough Environment Measuring System (TREMS), which measures environmental data in subway and high-speed train tunnels and is installed in three locations inside the tunnel. Previous studies analyzed environmental conditions inside tunnels located in or near a city, whereas the tunnel in this study is located in a mountainous area. The tunnel conditions were compared with those measured outside the tunnel for each month. Hourly changes during summer and winter periods were also analyzed, and the environmental conditions at different locations inside the tunnel were compared. The results are widely applicable in studies on the thermal environment and air quality of tunnels, as well as for computer analysis of tunnel airflow such as tunnel ventilation and fire simulations.

• Tunnel and Underground Space
• /
• v.13 no.4
• /
• pp.287-293
• /
• 2003

A long vertical duct is an essential installation for extracting smoke to the ground level when a fire occurs in an underground space. Due to the limitations of its basic assumptions, the existing two-layer zone model is unsuitable to model smoke dispersion through a long vertical duct. Therefore, an assessment was made to investigate the applicability of the field model, which is based on the computational fluid dynamics (CFD). A similar configuration to the published experimental work was modeled to test the validity. It is clear that under a consistent decision criterion based on the mass fraction, the field model (CFD) is able to predict that the diffusion front progresses up the shaft with exactly the same rate as that in the empirical correlation equation. This result is for better than the mathematically obtained equations in previously published research. Therefore, it can be said that the field model is an excellent option to predict the smoke dispersion through the long vertical shaft.

• Fire Science and Engineering
• /
• v.30 no.2
• /
• pp.27-34
• /
• 2016

This paper studies a fire detection system using an optical fiber linear detector which can minimize damage from a fire by the most adaptable even in poor environmental conditions such as a tunnel or utility-pipe conduit vulnerable to fire. Using a strand of optical fiber, temperature can be displayed in intervals of meters and a fire can be detected remotely from a distance of several kilometers. Thanks to its strengths such as high reliability and long life, it is widely applied in harsh environments in the overseas. Therefore demands are expected to grow greatly in Korea as well. However, all optical signal drive and analysis module except for the optical fiber linear detector, tend to rely on import. Firstly this study deduced the location and the method of processing signals measuring temperature by using the optical fiber linear detector in order to develop a technology for a domestic model of fire detection system. Secondly this study designed and manufactured the optical analysis test module, and then we checked its performance.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.24 no.4
• /
• pp.305-316
• /
• 2022

Hydrogen energy is emerging as an alternative to the depletion of fossil fuels and environmental problems, and the use of hydrogen vehicles is increasing in the automobile industry as well. However, since hydrogen has a wide flammability limit of 4 to 75%, there is a high concern about safety in case of a hydrogen car accident. In particular, in semi-enclosed spaces such as tunnels and underground parking lots, a fire or explosion accompanied by hydrogen leakage is highly likely to cause a major accident. Therefore, it is necessary to review hydrogen safety through analysis of flammability areas caused by hydrogen leakage. Therefore, in this study, the effect of the air velocity in the tunnel on the flammability area was investigated by analyzing the hydrogen concentration according to the hydrogen leakage conditions of hydrogen vehicles and the air velocity in the tunnel in a road tunnel with standard section. Hydrogen leakage conditions were set as one tank leaking and three tanks leaking through the TPRD at the same time and a condition in which a large crack occurred and leaked. And the air velocity in the tunnel were considered 0, 1, 2.5, and 4.0 m/s. As a result of the analysis of the flammability area, it is shown that when the air velocity of 1 m/s or more exists, it is reduced by up to 25% compared to the case of air velocity of 0 m/s. But there is little effect of reducing the flammability area according to the increase of the wind speed. In particular, when a large crack occurs and completely leaks in about 2.5 seconds, the flammability area slightly increases as the air velocity increases. It was found that in the case of downward ejection, hydrogen gas remains under the vehicle for a considerably long time.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.12 no.3
• /
• pp.215-222
• /
• 2010

An experimental study was carried out on a reduced scale model tunnel to investigate the efficiency of disaster prevention at underground and ground ventilation equipments for the fire in road tunnels. Based on Froude modeling, the 1/50 scaled model tunnel (20 m long) was manufactured. The vertical shafts that are used in the analysis of efficiency of disaster prevention are the two models that had considered when the real tunnels are designed and the amounts of smoke exhaust are applied the miniature of the real tunnels' smoke exhaust, 560 and $280\;m^3/s$. As the result of analysis, it is the possible the emissions of the entire quantity of CO gas through the vertical shafts. In the ground ventilation equipments, the concentration of CO is discharged 2.23~2,73 ppm smaller than the underground ventilation equipments. And the temperature rise in the ground ventilation equipments is $0.53{\sim}0.94^{\circ}C$ lower than in the underground ventilation equipments because of a cooling effect of the surface of the tunnel wall. As a result of analysis of CO concentration and the temperature rise in the modeling ventilation equipment, the position of ground ventilation equipment is more effective than the underground ventilation equipment in disaster prevention measures.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.6
• /
• pp.917-922
• /
• 2013

In this paper, we propose a smoke detection system in order to detect a fire in a wide space, such as tunnel, airports using infra-red and visible laser. The proposed smoke detection system is composed of infra-red laser transmitter and receiver, visible laser and Zigbee wireless communication network. A visible laser is used to match transmitter and receiver and Zigbee network is utilized to propagate warnings of fire. If smoke is appeared between transmitter and receiver, received signals are decreased and it can be considered as occurring smoke. As IR laser transmitter and receiver are separated by long distance, it is difficult to match due to large variations caused by small change of direction. In this paper, it is proposed to match effectively using visible laser. When smoke is detected, warning informations are propagated by Zigbee network in the developed smoke detection system.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.18 no.5
• /
• pp.128-134
• /
• 2014

Recently, design and construction of street tunnels tend to focus on cost reduction and preservation of nature. Accordingly, research is actively being carried out to quickly detect fires when they occur in tunnels, which have partially closed structures. Among such research, fire detection methods using optical fiber sensors have a wide bandwidth and fast transmission speed, while using light as a medium. Therefore, it does not receive electrical interference and there is almost no loss of information during transmission, while also having little noise as well. In relation to this, a fire monitoring system that can accurately detect the location of fires in real time using shape memory alloy and optical cables was developed in this study. In order to verify the developed method, light loss measurement test was conducted according to indoor temperature changes, while also conducting fire simulation tests by installing test beds in common underground zones with different external environments of temperature and distance. Upon carrying out experiments, the fire monitoring system developed in this study was found to be able to detect fires in long distance sections in real time.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.21 no.3
• /
• pp.419-432
• /
• 2019

Most of deep learning model training was proceeded by supervised learning, which is to train labeling data composed by inputs and corresponding outputs. Labeling data was directly generated manually, so labeling accuracy of data is relatively high. However, it requires heavy efforts in securing data because of cost and time. Additionally, the main goal of supervised learning is to improve detection performance for 'True Positive' data but not to reduce occurrence of 'False Positive' data. In this paper, the occurrence of unpredictable 'False Positive' appears by trained modes with labeling data and 'True Positive' data in monitoring of deep learning-based CCTV accident detection system, which is under operation at a tunnel monitoring center. Those types of 'False Positive' to 'fire' or 'person' objects were frequently taking place for lights of working vehicle, reflecting sunlight at tunnel entrance, long black feature which occurs to the part of lane or car, etc. To solve this problem, a deep learning model was developed by simultaneously training the 'False Positive' data generated in the field and the labeling data. As a result, in comparison with the model that was trained only by the existing labeling data, the re-inference performance with respect to the labeling data was improved. In addition, re-inference of the 'False Positive' data shows that the number of 'False Positive' for the persons were more reduced in case of training model including many 'False Positive' data. By training of the 'False Positive' data, the capability of field application of the deep learning model was improved automatically.