• International Journal of Highway Engineering
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• v.2 no.2
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• pp.139-148
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• 2000

Currently existing Accelerated Pavement Testing (APT) systems developed in several countries have been employed mainly to test the performance of asphalt pavement. Meanwhile, the length of concrete pavement is similar to that of asphalt pavement in expressways of Korea. and is expected to increase due to its durability and compatibility to our weather condition. To meet the society's demand of having our own APT system which can examine the long-term performance of concrete pavement, a contract study to develop Korea Accelerated Loading and Environment Simulator (KALES) for concrete pavement has been performed for 3 years from 1997 through 1999. Through the project, a detailed design was Peformed for the KALES system in which the entire structure of KALES, loading mechanism, wandering mechanism, suspension system, driving system were proposed. Also in advance to design a full-scale KALES system, a sample scale model was manufactured and tested for operating motion and force distribution. It is evident that the proposed prototype KALES system will provide higher degree of traffic simulation and durable operation, based on the satisfactory fatigue analysis.

• Journal of Korean Society of Transportation
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• v.31 no.1
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• pp.15-24
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• 2013

To accommodate urban concentration of population, multi-purpose super-tall buildings have been introduced, but they induce many travel demands causing regional traffic problems. While several travel demand management policies such as transit promotion or parking limits are presented to alleviate such problems, transportation infrastructure are still insufficient to meet high demands. In this study, super-tall buildings are categorized by scale and purpose, then mode-specific derived demand is estimated using modal share of each category. Optimal transportation infrastructure level is determined by condition-based average changing amount yielded by street network delay (in case of road) or the number of transit routes (in case of transit).

• Fire Science and Engineering
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• v.18 no.2
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• pp.49-56
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• 2004

Today's popular ventilation systems include the combined jet fans and electrostatic precipitation systems or the combined jet fans and vertical shaft system. Tunnels with these two ventilation systems applied have been designed and opened, more and more interest has been put in maintenance of a tunnel after opening. Therefore. it is to become more important to come up with the optimal operation mode and the method for the evaluation of ventilation system. In this study, to evaluate a tunnel ventilation and its economy, a dynamic simulation program was developed which can simulate the unsteady-state tunnel air velocity and concentration of pollutants according to the traffic flow variations and operation condition of a ventilation system. We clarified the effectiveness usage on tunnel ventilation by using it and also we could found the most economical ventilation operation mode by application in real exit tunnel. We obtained that combination of fan system and electrostatic precipitation system was more economical than jet fan priority operation mode.

• Smart Structures and Systems
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• v.24 no.2
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• pp.243-256
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• 2019

Determination of the most meaningful structural modes and gaining insight into how these modes evolve are important issues for long-term structural health monitoring of the long-span bridges. To address this issue, modal parameters identified throughout the life of the bridge need to be compared and linked with each other, which is the process of mode tracking. The modal frequencies for a long-span bridge are typically closely-spaced, sensitive to the environment (e.g., temperature, wind, traffic, etc.), which makes the automated tracking of modal parameters a difficult process, often requiring human intervention. Machine learning methods are well-suited for uncovering complex underlying relationships between processes and thus have the potential to realize accurate and automated modal tracking. In this study, Gaussian mixture model (GMM), a popular unsupervised machine learning method, is employed to automatically determine and update baseline modal properties from the identified unlabeled modal parameters. On this foundation, a new mode tracking method is proposed for automated mode tracking for long-span bridges. Firstly, a numerical example for a three-degree-of-freedom system is employed to validate the feasibility of using GMM to automatically determine the baseline modal properties. Subsequently, the field monitoring data of a long-span bridge are utilized to illustrate the practical usage of GMM for automated determination of the baseline list. Finally, the continuously monitoring bridge acceleration data during strong typhoon events are employed to validate the reliability of proposed method in tracking the changing modal parameters. Results show that the proposed method can automatically track the modal parameters in disastrous scenarios and provide valuable references for condition assessment of the bridge structure.

• Journal of the Korean Institute of Rural Architecture
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• v.21 no.2
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• pp.11-18
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• 2019

This study aims to identify the actual condition of local food stores that serve as a regional activation space within the highway rest area. It analyzes and examines user awareness, and presents desirable directions for the establishment of new local food stores and improvement of existing facilities. The research method was conducted as follows: the status of 226 rest areas were examined which were installed on national highways, location conditions and convenience facilities. Second, a physical survey was conducted on 116 local food stores(floor area, location) and a user awareness survey on 63 local food stores. The results of the analysis and review have been concluded as follows. First, it is necessary to consider the establishment of a local food store in order to promote the local community by using various cultural and environmental conditions in the highway rest area, and to secure a public space to promote exchanges with local residents and revitalize the local economy. Second, considering the continuous increase of highway users, location, and traffic conditions, diversification of convenience functions including local food stores should be considered even if it is a medium and small highway rest area. Third, the floor area of local food stores is generally planned within a range of $75m^2$ to $125m^2$, and its location should be integrated with the rest area as much as possible. Inevitably, when you need to construct separately at the exit or entrance, you need to consider a unique design that ensures accessibility and visibility.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.391-398
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• 2019

In general, truck-involved crashes increase severity in terms of both injury level and crash impact level. Recently, although the frequency and fatality of truck-involved crashes in Korea are rising, their associative studies are very limited. Therefore, the objective of this study is to identify critical factors influencing on injury severity of truck-involved crashes on Korean freeway system. To carry out this objective, this study uses an ordered probit model (OPM) based on a 6-year crash dataset from 2012 to 2017. From the analysis, eight variables were found to have a great effect on injury severity: older driver, crash speed, rear-end collision, number of vehicles involved, drowsy driving, nighttime (0:00 to 6:00) driving, overturn or rollover, and vehicle's fire after crash. However, injury severity was less severe in crashes under snowy condition and crashes to traffic facilities (i.e., crash alone).

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.11-16
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• 2021

At the present time, the number of accidents has enlarged speedily and in country like India per day there are about 204 accidents occurred. Accidents of two-wheeler compose a foremost segment of every accident and it can be true for the reason that two-wheelers like bikes not able to produce as many as security measurements normally incorporated in cars, truks and bus etc. General main rootcost of the two-wheeler accidents happen only when people community not remember to wearing a device helmet and during the driving time feels like sleep condition, alcohol disbursement, many of the drivers doesn't know heavy vehicles like Loory and buses approaching into very closer to their two wheelers, contravention of two wheelers in traffic rules and regulations. Let's overcome the above situations; our important objective is to develop an intelligent system device that can successfully facilitate in avoidance of every kind of problems. Suppose any of the above stated situations occurs, at that moment how system device identify and represents the commanders and community, and finally the stated situation be able to taken care of straight away without any further delay. A smart intelligent helmet system is a defending head covering used by rider for making bike riding safer than earlier. This is finished by incorporating sophisticated features like detecting the usage of helmet by the rider, connected Bluetooth module in helmet. In order to maintain the temperature inside the helmet device we need to include CPU fan module inside the device. RF based helmet prevents road accidents and identify whether people community is not using a component helmet or used. Main responsibility of the system is to detect accidents by vibration sensors, accelerometers and also with the help of modules global positioning system and global system for mobile commnicaiton module. A wireless communication device used to discover the accident area site location and likewise notifying the two-wheeler drived people's relatives and short message text information passed to the positioned hospitals.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.3
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• pp.173-180
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• 2022

The operation and transportation environment for an unmanned aerial vehicle will be completely different from those for the conventional air and ground transportation. The requirement for a traffic management system for its safe operation has been emerging. Accordingly, investigation is being conducted to analyze the danger that unmanned aerial vehicle may encounter during the flight and to provide the countermeasure by the simulation. When the drones operate in an urban environment, they may be affected by the wind around the building. Thus it is essential to predict the influence of the gust and analyze the resulting risk. In this paper, a method for evaluating the safety for a flight mission under the gust is suggested. By using the precise 6-degree-of-freedom flight simulation that is capable of simulating the gust condition, possible deviation from the pre-planned flight path in terms of the attitude orientation will be predicted. A method of quantifying the probability of the flight mission failure will also be presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1874-1881
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• 2021

Black ice, which occurs mainly on the road, vehicle traffic bridges and tunnel entrances due to the sub-zero temperature due to the slip of the road due to heavy snow, is not recognized because the image of asphalt is transmitted in the driver's view, so the vehicle loses braking power because it causes serious loss of life and property. In this paper, we propose a method to identify the black ice by using infrared camera and to identify the road condition by using deep learning to compensate for the disadvantages of existing black ice detection methods (artificial satellite imaging, checking the pattern of slip by ultrasonic reception, measuring the temperature of the road surface, and checking the difference in friction force of the tire during vehicle driving) and to reduce the size of the sensor to detect black ice.

• Journal of Environmental Science International
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• v.31 no.6
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• pp.503-513
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• 2022

This research investigated the effect of the eruption of Japan Sakurajima volcano on the concentration of ultrafine particle when the north Pacific high pressure exists in the Busan in summer. As a result of analyzing the forward trajectory using the HYSPLIT model, the air parcel from Sakurajima volcano passed through the sea in front of Busan at 1500 LST on July 17, 24 hours after the volcanic eruption. As a result of analyzing the PM₁₀ and PM_2.5 concentrations in the Busan for two days from July 16 to 17, 2018, the Sakurajima eruption in Japan, it can be seen that there was a high increase in PM₁₀ and PM_2.5 concentrations compared to the previous day. As a result of analyzing the backward trajectory, the air mass that reached Busan at 1300 LST on July 17, 2018 has moved near the Sakurajima volcano at 1,500 m, 2,000 m, and 3,000 m. The concentration of SO₄^2- in PM_2.5, the concentration of all three stations in Busan showed a sharp increase from 1000 LST on July 17th. Looking at the NH₄⁺ concentration in PM_2.5, it shows a very similar variation trend to SO₄^2-, and the correlation coefficient between the two components is 0.96 for Jangrimdong and Yeonsandong, and 0.85 for Busan New Port. Looking at the NO₃^- concentration in PM_2.5, the same high concentrations as SO₄² and NH₄⁺ were not observed in the afternoon of July 17th.