• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2006.04a
• /
• pp.216-221
• /
• 2006

This study provides a methodology for development of the Seismic Damage Evaluation System (SDES) in Korea. Major systems and status of database related to road networks in Korea are investigated to analyze the usability of the required information for developing the SDES. In this study, the SDES is composed of four components that are the road network component, the ground motion component, the fragile structure component, and the cost component. In addition, the procedures for the construction of database which support the SDES is proposed, and a prototype of the SDES for expressway of Korea is developed based on the developed methodology. The National Geospatial Information System (NGIS) and the National Earthquake Information System (NEIS) are used to develop the road network component and ground motion component, respectively. For the fragile structure component and the cost component, Highway Bridge Management System (HEMS) was used.

• Smart Structures and Systems
• /
• v.14 no.3
• /
• pp.469-477
• /
• 2014

As a kind of intelligent materials, conductive asphalt concrete has a broad application prospect including melting ice and snow on the pavement, closing cracks in asphalt concrete, sensing pavement damage, and so on. Conductive pavement will be suffered from fatigue failure as conventional pavement in the process of service, and this fatigue damage of internal structure can be induced by electrical signal output. The characteristics of electrical signal variation of conductive asphalt concrete in the process of fatigue cracking were researched in this paper. The whole process was clearly divided into three stages according to resistance changes, and the development of fatigue damage wasn't obvious in stage I and stage II, while in stage III, the synchronicity between the resistance and damage began to appear. Thus, fatigue damage variable D and initial damage value $D_0$ represented by the functions of resistance were introduced in stage III. After calculating the initial damage value $D_0$ under different stress levels, it was concluded that the initial damage value $D_0$ had no noticeable change, just ranged between 0.24 and 0.25. This value represented a critical point which could be used to inform the repair time of early fatigue damage in the conductive asphalt pavement.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.3
• /
• pp.106-118
• /
• 2019

In recent years, research and development on image object recognition using artificial intelligence have been actively carried out, and it is expected to be used for road maintenance. Among them, artificial intelligence models for object detection of road surface are continuously introduced. In order to develop such object recognition algorithms, a backbone network that extracts feature maps is essential. In this paper, we will discuss how to select the appropriate neural network. To accomplish it, we compared with 4 different deep neural networks using 6,000 road surface damage images. Based on three evaluation methods for analyzing characteristics of neural networks, we propose a method to determine optimal neural networks. In addition, we improved the performance through optimal tuning of hyper-parameters, and finally developed a light backbone network that can achieve 85.9% accuracy of road surface damage classification.

• Journal of Korean Society of Forest Science
• /
• v.76 no.2
• /
• pp.161-168
• /
• 1987

Forest road (10 Km) constructed for the demonstrational purpose by Forest Work Training Center (F.T.C.) in 1984 was partly damaged through the roadside landside and ditch erosion by the typhoon in 1986. The causes were investigated to apply for protecting against the damage of mountain forest road. The damaging length caused by roadside landside is around 3% out of total length of 10 Km forest road, and mostly coming from the curve road filled up more than 10 m slope length on the concave mountain slope, partly from the foot of fillslope along the ever-following valley and from the both side of fillslope under the outlet of culvert with ever-flowing water. In case of ditch erosion, the big damage at V-type ditch is coming from the overflow of valley water flowing down along the inside slope. Other problem is also showing in the steepness of longitudial gradient, which is felt as a problem in road to be constructed under more than 10 persent of gradient. Other cause of ditch erosion is coming from the bury of sand basin (water collecting wall) by the debris in small diameter culvert zone, namely less than 400mm, in diameter and by the soil mass slumped down from steep wall slope. From above results the causes of F.T.C. model road damage is showing to come from no-following the general guide or little experience to protect against the forest road damage. When improved above mentioned mistakes, F.T.C. Method of mountain forest road type could be developed as a model of Mountain forest road.

• Korean Journal of Environment and Ecology
• /
• v.37 no.6
• /
• pp.439-449
• /
• 2023

This study was conducted to verify the role of forest roads in the extinction of large forest fires in Korea. The study area was the forest fire-damaged area of Gangneung City, Gangwon Special Self-Governing Province, in April 2023, which is one of the areas with the highest road density among the major forest fires that have occurred so far. The scope of the forest fire damage area was confirmed through on-site survey, and the intensity of the fire was carried out through Sentinel-2 satellite imagery analysis. After that, the relationship between the damage range and intensity and the forest road was examined. About 59.6 km of roads were built within 50 m from the boundary of the forest fire damage area, which can easily access the entire 149.1 ha of forest fire damaged area. The road density is as high as 168.9 m/ha. All forests that were fragmented by roads were fragmented into 83 places, and all of these forests could be judged to have spread by spotting fire. As a result of analyzing the distribution of damage intensity by distance from the road to see the extent of damage according to the ease of access of fire extinguishing vehicles, it was confirmed that the proportion of areas with low-intensity damage has increased sharply even from 75 m or more away from the road. The results of analyzing the distribution of damage intensity by altitude to see the extent of damage according to the ease of access of fire extinguishing showed that the proportion of areas with low-intensity damage increased as the altitude increased, while the proportion of areas with damage of more than strong intensity decreased as the altitude increased. It was confirmed that there is no data that roads inside or adjacent to forests in the forest fire area of Gangneung City are effective in extinguishing forest fires. These results are contrary to the logic that increasing the road density in forests is effective in extinguishing forest fires. In the case of this fire area in Gangneung City, the road density is 43 times higher than the current road density in Korea claimed by the Korea Forest Service of 3.9 m/ha. This study suggests that roads can be a hindrance to extinguishing forest fires.

• Earthquakes and Structures
• /
• v.22 no.4
• /
• pp.387-399
• /
• 2022

To study the seismic damage of masonry structures and understand the characteristics of the multi-intensity region, according to the Dujiang weir urbanization of China Wenchuan earthquake, the deterioration of 3991 masonry structures was summarized and statistically analysed. First, the seismic damage of multistory masonry structures in this area was investigated. The primary seismic damage of components was as follows: Damage of walls, openings, joints of longitudinal and transverse walls, windows (lower) walls, and tie columns. Many masonry structures with seismic designs were basically intact. Second, according to the main factors of construction, seismic intensity code levels survey, and influence on the seismic capacity, a vulnerability matrix calculation model was proposed to establish a vulnerability prediction matrix, and a comparative analysis was made based on the empirical seismic damage investigation matrix. The vulnerability prediction matrix was established using the proposed vulnerability matrix calculation model. The fitting relationship between the vulnerability prediction matrix and the actual seismic damage investigation matrix was compared and analysed. The relationship curves of the mean damage index for macrointensity and ground motion parameters were drawn through calculation and analysis, respectively. The numerical analysis was performed based on actual ground motion observation records, and fitting models of PGA, PGV, and MSDI were proposed.

• International Journal of Highway Engineering
• /
• v.13 no.2
• /
• pp.21-29
• /
• 2011

Recently, typhoons or heavy rainfalls frequently occurred because of the effect of global warming, which caused serious damage such as landslide of mountain road, debris flow and uplift seepage pressure. Uplift seepage pressure induced on the pavement of mountain roads may cause serious pavement damage. It was known that subsurface drainage method is very effective to reduce uplift seepage pressure. Suitable permeability and stiffness of drainable base is very important to have the effectiveness of subsurface drainage. In this study, optimum particle size distribution of drainable base is investigate to meet the required permeability and bearing capacity of drainable base.

• Smart Structures and Systems
• /
• v.32 no.5
• /
• pp.309-318
• /
• 2023

The appropriate maintenance of highway roads is critical for the safe operation of road networks and conserves maintenance costs. Multiple methods have been developed to investigate the surface of roads for various types of cracks and potholes, among other damage. Like road surface damage, the condition of expansion joints in concrete pavement is important to avoid unexpected hazardous situations. Thus, in this study, a new system is proposed for autonomous expansion joint monitoring using a vision-based system. The system consists of the following three key parts: (1) a camera-mounted vehicle, (2) indication marks on the expansion joints, and (3) a deep learning-based automatic evaluation algorithm. With paired marks indicating the expansion joints in a concrete pavement, they can be automatically detected. An inspection vehicle is equipped with an action camera that acquires images of the expansion joints in the road. You Only Look Once (YOLO) automatically detects the expansion joints with indication marks, which has a performance accuracy of 95%. The width of the detected expansion joint is calculated using an image processing algorithm. Based on the calculated width, the expansion joint is classified into the following two types: normal and dangerous. The obtained results demonstrate that the proposed system is very efficient in terms of speed and accuracy.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.3
• /
• pp.95-105
• /
• 2019

In recent years, image processing techniques for detecting road surface damaged spot have been actively researched. Especially, it is mainly used to acquire images through a smart phone or a black box that can be mounted in a vehicle and recognize the road surface damaged region in the image using several algorithms. In addition, in conjunction with the GPS module, the exact damaged location can be obtained. The most important technology is image processing algorithm. Recently, algorithms based on artificial intelligence have been attracting attention as research topics. In this paper, we will also discuss artificial intelligence image processing algorithms. Among them, an object detection method based on an region-based convolution neural networks method is used. To improve the recognition performance of road surface damage objects, 600 road surface damaged images and 1500 general road driving images are added to the learning database. Also, supervised learning using background object recognition method is performed to reduce false alarm and missing rate in road surface damage detection. As a result, we introduce a new method that improves the recognition performance of the algorithm to 8.66% based on average value of mAP through the same test database.

• 한국방재학회:학술대회논문집
• /
• 2008.02a
• /
• pp.521-524
• /
• 2008

In addition the typhoon 'Lusa' of year 2002 has resulted 5,400 billion won of property damage and the damages for roads and railroads were approximated to be 2,860 billion won at 12,377 locations holding 53% damage of total. It was reported that the property damage due to the 2003 typhoon, 'Maemi' was 4,200 billion won. The recent typhoon, 'Aewinia', caused the 1,400 billion-won property damage including sweeping and flooding of 127 roads and 65 rivers, respectively. Therefore, this paper presented to estimate drainage size for debris flow