• Fire Science and Engineering
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• v.32 no.6
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• pp.34-39
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• 2018

In this paper, the architecture of a safe stove with an automatic fire suppression function using a sound wave fire extinguisher has been proposed and developed for the first time. A microcontroller connected to a fire sensor detects and suppresses a fire by driving a fire extinguisher. The sound wave fire extinguisher is composed of a speaker and collimator, and is driven by a driver module including an audio amplifier. The attenuation of the sound wave is reduced by preventing the sound diffusion with an enclosure surrounding a stove. The frequency of the sound wave is set to 50 Hz, and the sound pressure of 93 dBA is measured at the distance of 0.5 m. It takes maximum 8 and 15 seconds to suppress the flame from 7-cc and 14-cc flammable liquid, respectively, which corresponds to 24% and 42% of the natural extinguishing time. Since the proposed safe stove is non-toxic and leaves no residues over the conventional ones, it would combine with various home appliances to suppress early-stage fires and prevent fire expansion.

• The Journal of the Acoustical Society of Korea
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• v.37 no.6
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• pp.396-403
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• 2018

In this paper, a high-performance and low-noise centrifugal fan is developed for cooling automotive seats which provide a driver with pleasant driving environment. First, the flow characteristics of the existing fan unit was analyzed using a fan performance tester and CFD (Computational Fluid Dynamics) simulations. The analysis of the predicted flow field indicated vortex flow near the tip of fan hub and stagnation flow on the top of fan hub. Two design points are devised to reduce the vortex flow and the stagnation flow observed in the existing fan unit. First, the cut-off clearance which is the minimum distance between the fan blade and the fan housing is increased to reduce the vortex strength and, as a result, to reduce the overall sound pressure level. Second, the hub shape is more modified to eliminate the stagnation flow. The validity of proposed design is confirmed through the numerical analysis. Finally, a prototype is manufactured with a basis on the numerical analysis result and its improved flow and noise performances are confirmed through the P-Q curves measured by using the Fan Tester and the SPL (Sound Pressure Level) levels measured in the anechoic chamber.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.129-143
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• 2019

As the importance of autonomous vehicle safety is emphasized, the application of ISO-26262, a development verification guideline for improving safety and reliability, and the safety verification of autonomous vehicles are becoming increasingly important, in particular, SAE standard level 3 or higher level autonomous vehicles detect and decision the surrounding environment instead of the human driver. Therefore, if there is and failure or malfunction in the autonomous driving function, safety may be seriously affected. So autonomous vehicles, it is essential to apply and verity the safety concept against failure and malfunctions. In this study, we study the fault injection scenarios for safety evaluation and verification of autonomous vehicles using ISO-26262 part3 process and STPA were studied and safety measures for safety concept design were studied through simulation bases fault injection test.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.29-34
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• 2019

In this study, a gasoline test vehicle was evaluated for drive quality in emissions and fuel economy tests. The measurement results were compared with the manufacturer's suggested values to evaluate whether the tolerance ranges (fuel efficiency -5%, greenhouse gas +5%) were exceeded. We carried out tests with test subjects based on the SAE J2951 evaluation method. The test vehicle was a 2L gasoline vehicle. The drive following performance was found to increase under deliberate driving conditions and decreased in smooth driving conditions. As a result of the analysis of the drive following performance, the closer the value is to 1, the more accurate the driving is. (-) indicates harsh conditions, and (+) indicates gentle conditions. The basic data on the driver following between testers was obtained by analysis of the tests. The fuel efficiency correlation with the drive following performance within the target speed range of the fuel consumption mode. In the future, these measurement results can serve as key data for securing an exhaust gas database and fuel efficiency system for each measurement mode.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.204-210
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• 2019

In case of a fire inside a tunnel, unlike ordinary roads, it is very difficult for a driver to obtain visibility, and a large accident is highly likely to occur. In this study, the smoke behavior, visible distance, and CO concentration of a jet fan were analyzed using the NIST fire simulation (FDS). All analyses were set to HRRPUA (Heat Release Rate Per Area) 3.6MW/m and all the analysis times were set to 600s. In all analyses by CFD, the results were confirmed at y=30m and y=110m, and smoke behavior analysis, visible range analysis, and carbon monoxide concentration were confirmed according to the diameter and flow rate. As the size and flow rate of the jet fan increased, the visibility distance was high at y=30m, and the concentration of carbon monoxide was also confirmed to be 0 ppm. Therefore, proper setting of the jet fan diameter and flow rate will be an excellent solution for fires in tunnels, and taking refuge at upstream area of a re-ventilated fan can reduce the number of casualties.

• Safety and Health at Work
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• v.10 no.3
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• pp.377-383
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• 2019

Objectives: Exposure to fine particles in urban air has been associated with a number of negative health effects. High levels of fine particles have been detected at underground stations in big cities. We investigated the exposure conditions in four occupational groups in the Stockholm underground train system to identify high-exposed groups and study variations in exposure. Methods: $PM_1$ and $PM_{2.5}$ were measured during three full work shifts on 44 underground workers. Fluctuations in exposure were monitored by a real-time particle monitoring instrument, pDR, DataRAM. Qualitative analysis of particle content was performed using inductively coupled plasma mass spectrometry. Nitrogen dioxide was measured using passive monitors. Results: For all underground workers, the geometric mean (GM) of $PM_1$ was $18{\mu}g/m^3$ and of $PM_{2.5}$ was $37{\mu}g/m^3$. The particle exposure was highest for cleaners/platform workers, and the GM of $PM_1$ was $31.6{\mu}g/m^3$ [geometric standard deviation (GSD), 1.6] and of $PM_{2.5}$ was $76.5{\mu}g/m^3$ (GSD, 1.3); the particle exposure was lowest for ticket sellers, and the GM of $PM_1$ was $4.9{\mu}g/m^3$ (GSD, 2.1) and of $PM_{2.5}$ was $9.3{\mu}g/m^3$ (GSD, 1.5). The $PM_1$ and $PM_{2.5}$ levels were five times higher in the underground system than at the street level, and the particles in the underground had high iron content. The train driver's nitrogen dioxide exposure level was $64.1{\mu}g/m^3$ (GSD, 1.5). Conclusions: Cleaners and other platform workers were statistically significantly more exposed to particles than train drivers or ticket sellers. Particle concentrations ($PM_{2.5}$) in the Stockholm underground system were within the same range as in the New York underground system but were much lower than in several older underground systems around the world.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.4
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• pp.505-512
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• 2019

This study is a basic study to prepare safety measures for the tram that is being introduced into Korea by reviewing accident analysis and accident compensation system of the tram. Analysis of accident characteristics of the tram was analyzed based on overseas data. Five years after the inauguration of the tram, accidents were halved and stabilized. Deaths accounted for 0.5 % of all casualties, most accidents were minor. Accidents with other mean transportation were high 84.1 %, among them accidents with passenger cars was found to be highest. The frequent points of accidents were analyzed as intersections and tram stop, and measures for pedestrian accidents were found to be important. Those are proposed safety measures through analyzing tram accident characteristics: Monitoring accidents which occur within five years of its inauguration, developing accident database input system, installation of fences for preventing people from jaywalking, operating traffic signal for preventing people from jaywalking through connection of pedestrian signals and tram signals, clamping down on illegal U-turn cars and jaywalking pedestrian, Also, those are proposed accident treatment measures based on general driver receptively and overseas data: property damage liability coverage (PI) of car insurance, comparative negligence when the accident occurs between car and tram.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.477-484
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• 2019

As the residence time in the vehicle increases, the passenger desires a pleasant and stable riding environment in addition to the high driving performance of the vehicle. The windshield defrosting performance is one of the performance requirements that is essential for driver's safe driving. In order to improve the defrosting performance of the windshield of a vehicle, relevant elements such as the shape of the defrost nozzle should be appropriately designed. In this paper, CFD based numerical analysis is conducted to improve defrost performance of small electric vehicles. The defrost performance analysis was performed by changing the angle of the defrost nozzle and the guide vane that spray hot air to the windshield of the vehicle. Numerical simulation results show that the defrosting performance is best when the defrost nozzle angle is $70^{\circ}$ and the guide vane installation angle is $60^{\circ}$. Based on the analytical results, the defrosting experiment was performed by fabricating the defrost nozzle and the guide vane. As a result of the experiment, it is confirmed that the frost of windshield is removed by 80% within 20 minutes, and it is judged that the defrost performance satisfying the FVMSS 103 specification is secured.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.622-629
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• 2019

Recently, the government is taking new approaches to change the fact that the accident rate and accident death rate of the construction industry account for a high percentage of the whole industry. Especially, it is investing heavily in the development of construction technology that is fused with ICT technology in line with the current trend of the 4th Industrial Revolution. In order to cope with this situation, this paper proposed a concept to recognize and share the work situation information between the construction machine driver and the surrounding worker to enhance the safety in the place where construction machines are operated. In order to realize the part of the concept, we applied image processing technology using camera based on artificial intelligence to earth-moving work. Especially, we implemented an algorithm that can recognize the surrounding worker's circumstance and identify the risk situation through the experiment using the compaction equipment. and image processing algorithm based on YOLO-v3. This algorithm processes 15.06 frames per second in video and can recognize danger situation around construction machine with accuracy of 90.48%. We will contribute to the prevention of safety accidents at the construction site by utilizing this technology in the future.