• Journal of the Society of Disaster Information
• /
• v.16 no.4
• /
• pp.849-856
• /
• 2020

Purpose: Greenhouse gases are one of the major causes of global warming, a global disaster. It aims to improve how effective the GHG reduction policy, which is the main cause of global warming in the transportation sector, has been effective on the highway and how to calculate GHG emissions. Method: Using the DSRC raw data, we estimate the emissions of Namhae Expressway (Yeongam-Suncheon) from 2017 to 2019 in two ways, a macro method (conventional) and a micro method (individual vehicle). Result: As a result of calculating the emission of the highway, the result was far exceeding the estimated emission, and it was found that when the calculation was performed for each vehicle, it was underestimated by more than 20%. Conclusion: If more emissions are continuously emitted than expected in the current transportation sector, additional emission reduction policies are needed to achieve the current greenhouse gas reduction targets. In addition, in the calculation of emissions, which is the basis of this policy, analysis was conducted for each individual vehicle using the current DSRC raw data, but using GPS afterwards will enable precise emission calculation through a more microscopic analysis.

• Korean Journal of Optics and Photonics
• /
• v.32 no.1
• /
• pp.1-8
• /
• 2021

We have studied a tiled-aperture coherent-beam-combining system based on constructive interference, as a way to overcome the power limitation of a single laser. A 1-watt-level, 3-channel coherent fiber laser and a 3-channel fiber array of triangular tiling with tip-tilt function were developed. A monitoring system, phase controller, and 3-channel phase modulator formed a closed-loop control system, and the SPGD algorithm was applied. Eventually, phase-locking with a rate of 5-67 kHz and peak-intensity efficiency comparable to the ideal case of 53.3% was successfully realized. We were able to develop the essential elements for a tiled-aperture coherent-beam-combining system that had the potential for highest output power without any beam-combining components, and a multichannel coherent-beam-combining system with higher output power and high speed is anticipated in the future.

• Journal of the Korea Society for Simulation
• /
• v.30 no.1
• /
• pp.55-63
• /
• 2021

As a study on ballistic protection performance of a weapon system that is used in combat simulation, this paper aims to propose an improvement effect of the ballistic protection performance varying with incident angle of a bullet. For this, live-fire ballistic tests were performed to determine either complete penetration(CP) and partial penetration(PP) of three types of general armor plates made of uniformly rolled steel plates against a small caliber threat using 5.45 mm bullets with various speed. The major test parameter was the material of the weapon system and incident angle of the bullet with the target. Further, to quantitatively analyze the ballistic protection performance, three existing measurement methods were used for ballistic limit velocity. The test results showed that the ballistic protection performance with the incident angle of 30 degrees was 4% to 14% varying with the material of the armor plates greater than that of 0 degrees, which was approximately 1.1 times the performance improvement on average when compared to the conventional angle of incidence of the 0 degree. Those test results are expected to contribute to developing a more realistic combat simulation addressing the parameter improving the ballistic protection performance of an armor plate.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1395-1406
• /
• 2022

This study investigated the effects of the urban forest and street trees on flow and temperature distribution in the Daegu National Debt Redemption Movement Memorial Park. For this, we implemented tree-drag and tree-cooling parameterization schemes in a computational fluid dynamics (CFD) model and validated the simulated wind speeds, wind directions, and air temperatures against the measured ones. We used the wind speeds, wind directions, air temperatures predicted by the local data assimilation and prediction system (LDAPS) as the inflow boundary conditions. To investigate the flow and thermal characteristics in the presence of trees in the target area, we conducted numerical experiments in the absence and presence of trees. In the absence of trees, strong winds and monotonous flows were formed inside the park, because there were no obstacles inducing friction. The temperature was inversely proportional to the wind speed. In the presence of trees, the wind speeds(temperatures) were reduced by more than 40 (5)% inside the park with a high planting density due to the tree drag (cooling) effect, and those also affected the wind speeds and temperatures outside the park. Even near the roadside, the wind speeds and temperatures were generally reduced by the trees, but the wind speeds and air temperatures increased partly due to the change in the flow pattern caused by tree drag.

• Journal of Conservation Science
• /
• v.37 no.2
• /
• pp.135-143
• /
• 2021

Conservation treatment that involved filling the lifting parts of wooden cultural heritage is carried out by obtaining wood or wood powder of the same species and mixing it with synthetic resin or natural glue to charge the blank area. Various concentrations and mixing ratios of adhesives and additives are used, depending on the type and condition of the target. Accordingly, in this study, we determined the conditions of the filler suitable for conservation treatment of wooden sculptures with lifted or separated bark in the National Museum of Modern and Contemporary Art. The optimal filler conditions for each adhesive were selected based on drying speed, shrinkage and expansion rates, and physical deformation degree. Then, to verify their actual applicability, these fillers were applied to wood and exposed to high-humidity environment and their cross-sections were observed. The fillers showed stable application in the following order: animal glue, PVAc adhesive, acrylic adhesive. In conclusion, a 1:2 mixture of animal glue and wood powder is a suitable filler for conservation treatment of wooden sculpture with lifted bark. The results of this study suggest appropriate ways to stabilize the bark that was lifted or separated from a wooden sculpture, thus enabling the future conservation treatment of the artworks under similar conditions.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.5
• /
• pp.15-21
• /
• 2021

Electrically powered airplanes can reduce CO₂ emissions from fossil fuel use and reduce airplane costs in the long run through efficient energy use. For this reason, advanced aviation countries such as the United States and the European Union are leading the development of innovative technologies to implement the full-electric airplane in the future. Currently, the research and development to convert existing two-seater engine airplanes to electric-powered airplanes are underway domestically. The airplane converted to electric propulsion is the KLA-100, which aims to carry out a 30-minute flight test with a battery pack installed using the engine mounting space and copilot space. The lithium-ion battery installed on the airplane converted to electric propulsion was designed with a specific power of 150Wh/kg, weight of 200kg, and a C-rate 3~4. This study confirmed the possibility of a 30-minute flight with a designed battery pack before conducting a flight test of a modified electrically propelled airplane. The battery performance was verified by dividing the 30-minute flight profile into start/run stage, take-off stage, climbing stage, cruise stage, descending stage, and landing/run stage. The final target of the 30-minute flight was evaluated by calculating the battery capacity required for each stage. Furthermore, the flight performance of the electrically propelled airplane was determined by calculating the flight availability time and navigation distance according to the flight speed.

• Journal of Broadcast Engineering
• /
• v.27 no.6
• /
• pp.936-939
• /
• 2022

As air combat system technologies developed in recent years, the development of air defense systems is required. In the operating concept of the anti-aircraft defense system, selecting an appropriate armament for the target is one of the system's capabilities in efficiently responding to threats using limited anti-aircraft power. Much of the flying threat identification relies on the operator's visual identification. However, there are many limitations in visually discriminating a flying object maneuvering high speed from a distance. In addition, as the demand for unmanned and intelligent weapon systems on the modern battlefield increases, it is essential to develop a technology that automatically identifies and classifies the aircraft instead of the operator's visual identification. Although some examples of weapon system identification with deep learning-based models by collecting video data for tanks and warships have been presented, aerial vehicle identification is still lacking. Therefore, in this paper, we present a model for classifying fighters, helicopters, and drones using a convolutional neural network model and analyze the performance of the presented model.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.1243-1244
• /
• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• The Journal of Bigdata
• /
• v.7 no.1
• /
• pp.15-27
• /
• 2022

In the past five years, the fatality rate of single-vehicle accidents has been 4.7 times higher than that of all accidents, so it is necessary to establish a system that can detect and respond to single-vehicle accidents immediately. The IoT(Internet of Thing)-based real-time traffic accident recognition system proposed in this study is as following. By attaching an IoT sensor which detects the impact and vehicle ingress to the guardrail, when an impact occurs to the guardrail, the image of the accident site is analyzed through artificial intelligence technology and transmitted to a rescue organization to perform quick rescue operations to damage minimization. An IoT sensor module that recognizes vehicles entering the monitoring area and detects the impact of a guardrail and an AI-based object detection module based on vehicle image data learning were implemented. In addition, a monitoring and operation module that imanages sensor information and image data in integrate was also implemented. For the validation of the system, it was confirmed that the target values were all met by measuring the shock detection transmission speed, the object detection accuracy of vehicles and people, and the sensor failure detection accuracy. In the future, we plan to apply it to actual roads to verify the validity using real data and to commercialize it. This system will contribute to improving road safety.

• Journal of Korean Society of Disaster and Security
• /
• v.16 no.3
• /
• pp.1-15
• /
• 2023

This study focuses on modeling the impact of ammonia leakage from the storage tank in a combined cycle power plant's flue gas denitrification facility. It employs accident impact assessments and diffusion models to determine the optimal scenarios for ammonia storage tank leakage accidents. The study considers the operating conditions of variables as standard conditions for predicting the extent of damage. The Taean combined cycle power plant is chosen as the target area, taking into account seasonal factors such as temperature, humidity, wind speed, atmospheric stability, and wind direction. By utilizing a Gaussian diffusion model, the concentration of ammonia gas at various locations is estimated to assess the potential extent of external damage resulting from a leak. The study reveals that in conditions of high temperature and stable atmosphere within the specified range, lower wind speeds contribute to increased damage to the human body due to ammonia diffusion.