Given the hazards posed by black ice, it is crucial to investigate the conditions that contribute to its formation. Two ensemble machinelearning algorithms, Random Forest (RF) and Extreme Gradient Boosting (XGBoost), were employed to forecast the occurrence of black ice using atmospheric data. Additionally, explainable artificial intelligence techniques, including Feature Importance (FI) and partial dependence Plot (PDP), were utilized to identify atmospheric conditions that significantly increase the likelihood of black ice formation. The machinelearning algorithms achieved a forecasting accuracy of 90%, demonstrating reliable performance. FI analysis revealed distinct key predictors between the algorithms: relative humidity was the most critical for RF, whereas wind speed was paramount for XGBoost. The PDP analysis identified the specific atmospheric conditions under which black ice was likely to form. This study provides detailed insights into the atmospheric precursors of frost/fog-induced black ice formation. These findings enable road managers to implement proactive winter road maintenance strategies, such as optimizing anti-icing patrol routes and displaying warnings on various message signs, thereby enhancing road safety.

PURPOSES : The aim of this study is to develop a road fog information system based on the geostationary meteorological satellite (GK2A) for road weather services on highways. METHODS : Three threshold values sensitive to fog intensity in the GK2A fog algorithm were optimized using multi-class receiver operating characteristic analysis to produce road fog information depending on day and night. The developed a GK2A road fog algorithm that can detect three levels of road fog based on the visibility distance criteria (1km, 500m, and 200m). Furthermore, the GK2A road fog product was not only substituted with visibility objective analysis data in unknown and cloud-covered areas of satellite data, but also integrated with visibility distance data obtained from visibility gauges and CCTV image analysis to improve the accuracy of road fog information. RESULTS : The developed road fog algorithm based on meteorological satellite data provides real-time road fog information categorized into three levels (attention, caution, and danger) based on the visibility distance, with a spatial resolution of 1km × 1km and temporal resolution of 5 minutes. The road fog algorithm successfully detected road fog in five out of seven fog-related traffic accidents reported by Korean media outlets from 2020 to 2022, resulting in a detection success rate of 71.4%. The Korea Meteorological Administration is currently in the process of installing additional visibility gauges on 26 highways until 2025, and the next high-resolution meteorological satellite (GK5) is planned to be launched in 2031. We look forward to significantly improving the accuracy of the road fog hazard information service in the near future. CONCLUSIONS : The road fog information test service was initiated on the middle inner highway on July 27, 2023, and this service is accessible to all T-map and Kakao-map users through car navigation systems free of charge. After 2025, all drivers on the 26 Korean highways will have access to real-time road fog information services through their navigation systems.

PURPOSES : Demonstrated performance degradation of LiDAR for vehicle and pedestrian dummy in rainy and foggy road conditions. METHODS : In real-scale rain and fog road conditions, adjust the distance between LiDAR and the measurement target from 10m to 70m (in 10m interval), measure LiDAR NPC (number of point cloud) and intensity, and compare the resulting numerical values. RESULTS : LiDAR's NPC and Intensity showed statistically significant differences by overall weather condition (normal, rain, fog), and the values were found to be larger in the order of normal>rainfall>fog. In the case of vehicles, sunder rain conditions, NPC and intensity are recognized even at 70m as in normal conditions, but under fog conditions, NPC and intensity are measured only up to 30m. In the case of pedestrians, the reflective area size is smaller than that of vehicles, so they are recognized only up to 30m in rainy conditions, and NPC and intensity are measured only up to 20m in fog conditions. CONCLUSIONS : It was confirmed that LiDAR performance deteriorates in rain and fog compared to normal.

기상불량으로 인해 발생하고 있는 해양사고 중 해무 발생에 따른 시계제한은 선박의 좌초, 선저 파손 등의 사고를 유발하는 것과 동시에 사고에 따른 인명피해를 동시에 수반하고 있으며 이는 매년 지속적으로 발생하고 있다. 또한 해상에서의 저시정은 지역간 국소적으로 차이가 존재하는 경우에도 일괄적으로 여객선에 대한 운항 지연 및 통제 조치를 하고 있어 섬주민들의 교통수단 이용에 상당 한 불편을 초래하는 등의 사회적 문제로 대두되고 있다. 더욱이 이와 같은 조치는 지역적 편차나 사람마다 관측의 판단 기준이 상이하여 이를 객관적으로 정량화하지 못하고 있어 더욱 문제가 심화되고 있는 실정이다. 현재 각 항만의 VTS에서는 시정거리가 1km 미만인 경우 선박의 운항을 통제하고 있으며, 이 경우 저시정에 따른 해무 가시거리를 시정계 혹은 육안에 의한 목측(目測)에 의존하고 있을 정도로 객관적인 데이터 수집을 통한 평가에 있어서는 한계가 있다. 정부에서는 이와 같은 해양교통안전 저해요소를 해결하기 위한 일환으로 해 무 탐지 및 예측을 위한 해양기상신호표지 및 해상안개관측망을 구축하여 운용하고 있으나, 국지적으로 발생하는 해무를 관측하기 위한 시스템은 매우 부족한 현실적 어려움에 놓여있다. 이에 따라 본 논문에서는 해상에서의 저시정으로 인해 발생하고 있는 여러 사회적 문 제를 해결하기 위한 국내․외 정책동향에 대해 살펴보고, 이와 관련한 일반국민 및 현장 이해관계자의 인식 정도를 조사․분석하여 해무 에 따른 해상교통안전을 확보하기 위한 정부지원(해무 탐지 및 예측 기술을 기반으로 한 해상교통운영 체계 개발 등)의 필요성에 대한 기 초자료를 제공하고자 한다. 또한 이는 궁극적으로 해무로 인해 발생할 수 있는 해상안전 위험요소를 사전에 차단함으로써 보다 안정된 해상교통운영체계를 마련하는데 그 목적을 두고 있다.

PURPOSES : In this study, a system is investigated and developed to remove fog by injecting air onto a road using high-pressure air generated by turbo blowers installed on both edges of the road without using artificial chemicals. METHODS : A test device was constructed on a scaled road measuring 5 m long. A 225 kW class turbo blower was used to supply air. An air injection nozzle was installed to allow high-pressure air supplied from the turbo blower to be sprayed vertically from the edge of the road and horizontally from the surface of the road. Ten micro humidifiers were used to generate fog. RESULTS : Experimental results show that when ground fog occurs on the road, spraying air only in the vertical direction cannot effectively remove the fog. However, when vertical and horizontal nozzles are used simultaneously, both ground fog and flowing fog are removed effectively. CONCLUSIONS : A system for removing fog by spraying air jet is constructed, and fog is generated using a micro humidifier. Results from the fog removal performance test show that the system effectively removes fog.

국내 감염병 매개 모기인 흰줄숲모기(Aedes albopictus), 중국얼룩날개모기(Anopheles sinensis s.l.), 빨간집모기(Culex pipens), 작은빨간집 모기(Cx. tritaeniorhynchus)를 대상으로 살충제 deltamethrin, etofenprox, bifenthrin를 석유, 등유, 그리고 물로 희석하여 휴대용 가열연막과 차량용 가열연막의 방제효과를 측정하였다. 실험은 야외에서 일정한 거리에 암컷모기가 들어있는 노출장을 매단 스탠드를 세우고 실시하였다. 세 종류의 살충제를 각각 경유에 희석하여 살포한 휴대용 가열연막은 10 m 이내의 모기에 대해 평균 52.0%의 치사율을 보였고, 살충제를 물로 희석하여 사용한 휴대용 가열연막의 모기 치사율은 평균 64.0%였다. 살충제를 경유로 희석한 차량용 가열연막은 모기에 대해 살포 거리 50 m 이 내에서 평균 34.8%의 치사율을 보였다. 가열연막용 살충제의 희석제로 사용되는 경유와 등유의 모기 치사효과는 등유가 경유에 비해 1.9배 높게 나타났다.

본 연구에서는 하절기 토마토 재배 시 주간 포그 냉방, 야간 히트펌프 냉방을 처리를 하여 냉방 처리가 온실 내 온습도, 작물의 생육 및 수확량에 미치는 영향을 분석하였다. 하절기 주간에 차광 처리한 대조구 온실의 평균 온습도는 32.1°C, 59.4%였고, 포그 처리한 시험구 온실의 평균 온도는 30.0°C, 74.3%로 나타났다. 이 때 외부의 평균 온습도는 31.4°C, 57.7%로 대조구 온실의 온도는 외기보다 0.7°C 높았으나 시험구 온실의 온도는 외기보다 1.4°C, 대조구보다 2.1°C 낮게 나타났다. 평균 습도는 시험구 온실 74.3%, 대조구 온실 59.4%로 포그 처리를 한 시험구에서 높게 나타났다. 야간 대조구 온실의 평균 온습도는 25.2°C, 85.1%였고, 히트펌프로 냉방을 한 시험구 온실의 평균 온습도는 23.4°C, 82.4%, 로 나타났다. 야간 외부의 평균 온습도는 24.4°C, 88.2%로 대조구 온실의 온도는 외기보다 0.8°C 높았으나 시험구 온실의 온도는 외기보다 1.0°C, 대조구보다 1.8°C 낮게 나타났다. 평균 습도는 시험구 온실 82.4%, 대조구 온실 85.1%로 나타나 시험구 온실의 습도가 더 낮게 나타났다. 작물 생육은 정식하고 8주 후에는 두 온실 간의 큰 차이는 없는 것으로 나타났으나 냉방 처리 후에는 시험구 온실의 작물이 대조구에 비해 경경, 초장, SPAD 값이 높게 나타났다. 토마토의 수확량은 냉방을 시작하고 2주 후까지 총 생산량의 차이는 1.2%로 큰 차이 없었으나 3주 후와 4주 후의 일 생산량이 시험구에서 대조구보다 많게 나타났다. 최종적으로는 시험구의 수확량이 81.3kg, 대조구의 수확량이 73.8kg으로 시험구가 대조구에 비해 10.2% 많게 나타남으로써 하절기 주간 포그 냉방, 야간 히트펌프 냉방이 작물 성장에 적합한 환경을 조성해 줌으로써 생육 및 생산성에 영향을 미친 것으로 판단된다. 냉방 처리에 따른 경제성을 비교해보면 대조구 온실에서는 142,166원의 수익이 있었던 반면 시험구 온실에서는 28,727원의 손해가 발생하여 냉방 처리는 경제성이 떨어지는 것으로 나타났다. 그러나 재식 밀도, 히트펌프 운용 시간 및 기간을 조절하여 에너지 사용은 줄이면서 생산성을 증가시킨다면 경제성도 확보할 수 있을 것으로 기대되며 이에 대한 추가 연구가 필요할 것으로 판단 된다.

PURPOSES : This study aimed to examine the effect of fog on the optical properties of taillights and the relationship between luminous intensity and the visibility distance of taillights on the road. METHODS : Changes in luminous intensity were measured using a light meter. Participants subjectively evaluated visibility distance. The artificial fog was reproduced using weather-generating facilities at the Center of Road Weather Proving Ground (CRPG). RESULTS : As expected, the average luminous intensity under intermediate fog conditions was reduced to 72% compared to normal weather conditions and 44% under heavy fog conditions in the case of the tail lamp-only lit condition. In the case of the tail lamp and brake lamp lit condition, the average luminous intensity was reduced to 76% under heavy fog conditions and 55% under intermediate fog conditions compared to normal dry conditions. In addition, the average visibility distance was reduced by 41% when fog conditions changed from intermediate to heavy in the case of the tail lamp-only lit condition and 39% in the case of the tail lamp and brake lamp lit conditions. Changes in visibility distance corresponding to the gradual change in luminous change were evaluated by participants, and the linearly regressed equations for the relationship between the intensity levels and the visibility distance were derived and examined for their meaning in terms of road traffic safety concerning stopping sight distance. CONCLUSIONS : Luminous intensities were suggested, given the design speeds, to satisfy the minimum stopping distances. In addition, the required speed reduction allowances were suggested given the design speeds if the luminous intensity remains unchanged.

This study was conducted to provide a basis for raising farm income by increasing the yield and extending the cultivation period by creating an environment where crops can be cultivated normally during high temperatures in summer. The maximum cooling load of the multi-span greenhouse with a floor area of 504 m2 was found to be 462,609 W, and keeping the greenhouse under 32°C without shading the greenhouse at a high temperature, it was necessary to fog spray 471.6 L of water per hour. The automatic fog cooling control device was developed to effectively control the fog device, the flow fan, and the light blocking device constituting the fog cooling system. The fog cooling system showed that the temperature of the greenhouse could be lowered by 6°C than the outside temperature. The relative humidity of the fog-cooled greenhouse was 40-80% during the day, about 20% higher than that of the control greenhouse, and this increase in relative humidity contributed to the growth of cucumbers. The relative humidity of the fog cooling greenhouse during the day was 40-80%, which was about 20% higher than that of the control greenhouse, and this increase in relative humidity contributed to the growth of cucumbers. The yield of cucumbers in the fog-cooled greenhouse was 1.8 times higher in the single-span greenhouse and two times higher in the multi-span greenhouse compared to the control greenhouse.

A coal dust scattered from storage and transfer facilities of coal power plant is led to a air pollution. It is difficult to reduce some scattered coal dust by used filter system such as bag filter and electric precipitator because of being scattered in the large area. The need to cut down coal dust generation has been increased as being reinforced regulation to reduce dust from coal power plant. So this is a experimental basic study which reduces coal dust generation. This study is to reduce scattering rate of the coal dust by collision and interception between fine fog droplet and coal dust particles. The reducing rate of coal dust is evaluated by droplet size of 10㎛ sprayed. It is evaluated that capture efficiency is lower as a coal dust concentration become higher. And also it is increase as droplet size is decrase and droplet density is increase. It is resulted that coal dust coefficient to optimize the fog system design is 25μg/m3/l/hr and capture efficiency of coal dust is about 80%.