• 한국도로학회:학술대회논문집
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• 2008.03a
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• pp.79-87
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• 2008

• Journal of the Korean Society of Safety
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• v.25 no.6
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• pp.103-108
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• 2010

In this study, tank truck incidents of road transport of hazardous materials to experimental investigated the potential fire hazard. Real scale fire was to perform experiments for on this qualitative and quantitative data collection and analysis. Particularly affected by radiant heat from the flames caused and damage estimates range investigated accordingly. Flame temperature, internal temperature of tank and emitted radiation from the flames was investigated. The flame of light oil spill caused a fire at a temperature of about $300^{\circ}C$ high in comparison with the methanol by combustion of diesel and methanol, according to the difference, the flame duration changes varies depending on the Burning rate, amount of radiant heat flux from light oil fire was 4 times increases compared with fire of methanol. Depending on spill locations(kinds of road surfaces, absorbing rate) and the longer the duration of the flame important factors for the internal temperature of tank truck rise was found. Dirt roads than paved road accident in a fire caused by leakage of hazardous was could the higher the damaged. Therefor, Fire suppression activities should be required in particular to be around.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.121-132
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• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.

• International Journal of Concrete Structures and Materials
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• v.10 no.1
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• pp.39-46
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• 2016

In this study, different proportions of glass beads used for road marking were added into the concrete samples to reduce the temperature gradient through the concrete pavement thickness. It is well known that decreasing the temperature gradient reduces the risk of thermal cracking and increases the service life of concrete pavement. The extent of alkali-silica reaction (ASR) produced with partial replacement of fine aggregate by glass bead was investigated and compressive strength of concrete samples with different proportion of glass bead in their mix designs were measured in this study. Ideal results were obtained with less than 0.850 mm diameter size glass beads were used (19 % by total weight of aggregate) for C30/37 class concrete. Top and bottom surface temperatures of two different C30/37 strength class concrete slabs with and without glass beads were measured. It was identified that, using glass bead in concrete mix design, reduces the temperature differences between top and bottom surfaces of concrete pavement. The study presented herein provides important results on the necessity of regulating concrete road mix design specifications according to regions and climates to reduce the temperature gradient values which are very important in concrete road design.

• Journal of Environmental Science International
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• v.25 no.11
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• pp.1589-1595
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• 2016

From December 2014 to November 2015, an automatic weather system (AWS) was installed over a wide road of Daegu to continuously measure meteorological factors and surface temperature. We investigated the effective operating period of the clean-road system using the daily maximum and minimum air and asphalt surface temperatures, with the aim of creating an optimum thermal environment. The clean-road system was installed over a part of the broad way of Dalgubul(Dalgubul-Daero) by Daegu Metropolitan City in 2011. Until now, the clean-road system has been operated from the middle of April to the end of September. We assumed that it was desirable that the clean-road system could be operated when the discomfort index was above 55. In conformity with the conditions, we concluded that the optimum operation period of the clean-road system is from the end of March to about the middle of October.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.1
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• pp.82-89
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• 2024

Black ice is very difficult to recognize and reduces the friction of the road surface, causing automobile accidents. Since black ice is difficult to detect, there is a need for a system that identifies black ice in real time and warns the driver. Various studies have been conducted to prevent black ice on road surfaces, but there is a lack of research on systems that identify black ice in real time and warn drivers. In this paper, an real-time image-based analysis system was developed to identify the condition of asphalt road surface, which is widely used in Korea. For this purpose, a dataset was built for each asphalt road surface image, and then the road surface condition was identified as dry, wet, black ice, and snow using deep learning. In addition, temperature and humidity data measured on the actual road surface were used to finalize the road surface condition. When the road surface was determined to be black ice, the salt spray equipment installed on the road was automatically activated. The surface condition recognition system for the asphalt concrete pavement and black ice automatic prevention system developed in this study are expected to ensure safe driving and reduce the incidence of traffic accidents.

• Journal of the Korean Applied Science and Technology
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• v.38 no.6
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• pp.1355-1369
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• 2021

This study improved the algorithm for the road ice prediction algorithm and analyzed the prediction rate when comparing actual field measurement data and algorithm prediction value. For analysis, road and weather conditions were measured in Geumdong-ri, Sinbuk-myeon, Pocheon-si. First algorithm selected previous research result algorithm. And the 4th algorithm was improved according to the actual freezing conditions and measured values. Finally, five algorithms were developed: freezing by condensation, freezing by precipitation, freezing by snow, continuous freezing, and freezing by wind speed. When forecasting using an algorithm at the Pocheon site, the freezing hit rate was improved to 93.2%. When calculating the combination ratio for the algorithm. the algorithm for freezing due to condensation and the continuation of the frozen state accounted for 95.7%.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2256-2261
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• 2008

The electric snow melting and deicing system by electric heating cable which is adopted in this study is a part of road facilities to keep surface temperature of the road higher than freezing point of water for melting the snow or ice accumulated on it. The electric heating cables are buried under paved road at a certain depth and a certain pitch and operated automatically and manually. Design theory, amount of heating, and installation standard vary according to economic situation, weather condition, and installation place. A main purpose of this study is figuring out the appropriate range of required heat capacity and installation depth and pitches for solving snowdrifts and freezing problems with minimum electric power consumption. This study was performed under the ambient air temperature($-2^{\circ}C$, $-5^{\circ}C$), the pitches of the electric heating cables (200 mm, 300 mm), heating value ($250\;W/m^2$, $300\;W/m^2$, $350\;W/m^2$).

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.873-882
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• 2021

In this study, a study was conducted to develop a system for predicting/responding to black ice occurring on roads in winter. Tests conditions were studied by making models of cement concrete pavement and asphalt concrete pavement. In order to freeze water on the manufactured model package, an tests was conducted at a temperature below zero using a freezer, and the freezing process was photographed using a thermal imaging camera. Black ice is generated when water is present on the road surface and the temperature is below freezing or the road surface temperature is below the dew point temperature. Under sub-zero conditions, the pavement, water, and ice were classified with a thermal imaging camera. As a result of the tests, it was possible to distinguish with a thermal imaging camera at a temperature below freezing in the same freezer due to the difference in the emissivity of the packaging, water, and ice. In the process of changing from water to ice during the tests, it was analyzed that ice and water were clearly distinguished by the thermal imaging camera due to the difference in emissivity and reflectance, so black ice could be predicted using the thermal imaging camera.

• 한국도로학회:학술대회논문집
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• 2002.10a
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• pp.177-184
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• 2002