• Proceedings of the KSR Conference
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• 2004.06a
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• pp.1102-1107
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• 2004

High-speed railway bridges subject to effect of statical loads by temperature change as well as dynamic loads by interaction between vehicle load which run specially fast and behavior of bridges, If suitable longitudinal expansion by temperature change of bridge does not happened, it can cause unhealthy condition for the parts of bridges as well as can generate addition stress to bridges, For these reason, Analysis and Estimation of data about behavior of bridges occupies important factor in that estimate the remaining life of bridges and select the maintenance, repair and retrofit. In this paper, Analysis for the long-term behavior of bridges using Longitudinal displacement and Temperature data that is actuality measured data to the bridges of Seoul-Busan high speed railroad test section has been made.

• Journal of the Korean Society of Safety
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• v.15 no.2
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• pp.8-12
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• 2000

The fatigue crack propagation tests were performed in triangular and holding-time stress waveforms at $650^{\circ}C$. The behavior of fatigue crack propagation was investigated according to waveform. The analysis of high temperature fatigue crack propagation by the stress intensity factor range ${\Delta}K$, elastic fracture mechanics parameter, was not available. The behaviors of high temperature fatigue crack propagation by the J-integral(${\Delta}J_f$, J' and ${\Delta}J_c$), elasto-plastic fracture mechanics parameter, were investigated in a number of stress waveforms. The fast-fast waveform exhibited cycle-dependent(fatigue type), the slow-fast and the hold time with 500sec waveforms appear to be time-dependent(creep type) and the fast-slow and the hold time with 5, 25sec waveforms exhibited conbined behavior of both types(fatigue-creep conbined type).

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.146-153
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• 2004

Torsion beam rear suspension has been widely adopted to the rear suspension of vehicle by reason of simple structure and cost competitiveness. Since the kinematic characteristics of torsion beam rear suspension are determined by elastic behavior of torsion beam, quasi-static analysis based on finite element modeling of torsion beam has been conducted to obtain the kinematic parameters of torsion beam rear suspension. In this paper, simple kinematic equations with rear geometric parameters are derived to predict the kinematic behavior of torsion beam rear suspension. The suspension design parameters such as roll center height, roll stiffness, roll steer and roll camber can be easily obtained with the kinematic equations. The suggested kinematic equations are validated from comparison with the test results and solution offered by ADAMS. The suspension design parameters varied with the position of torsion beam are discussed.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.599-605
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• 2009

The aim of the present study is the characteristics of bridge rubber pads and suggested how to determine the stiffness the pads. A disk bearing is operated as an elastic bearing in the vertical direction and is composed of a Polyether Urethane (polyurethane) disk for elastic support and Polytetrafluoroethylene (PTFE) to accommodate movement. Static tests are conducted in a laboratory to determine the static behavior of a Polyurethane disk. Finite Element (FE) analysis is also performed to verify the static performance. For dynamic behavior, four disk bearings having the identical Polyurethane disk used in the static tests are installed in a full size railway bridge and tested under a running locomotive. From the tests results, the static and dynamic stiffness of disk bearings are estimated and compared with each other. In the procedure to estimate the stiffness of a pad, the dead load(pre-load) of a bridge and live load of a vehicle are considered.

• Journal of the Korean Society for Railway
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• v.16 no.1
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• pp.7-13
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• 2013

A scaled version of a roller rig is developed to demonstrate the dynamic characteristics of a railway vehicle for academic purposes. This rig is designed based on Jaschinski's similarity law. It is scaled to 1/10 of actual size and allows 9-DOF motion to examine the up and down vibration of a train set. The test rig consists of three sub-hardware components: (i) a driving roller mechanism with a three-phase AC motor and an inverter, (ii) a bogie structure with first and second suspensions, and (iii) the vehicle body. The motor of the rig is capable of 3,600rpm, allowing the test to simulate a vehicle up to a maximum speed of 400Km/hr. Because bearings and joints are properly connected to the sub-structures, various motion analyses, such as a lateral, pitching, and yawing motion, are allowed. The slip motion between the rail and the wheel set is also monitored by several sensors mounted in the rig. After the construction of the hardware, an experiment is conducted to obtain the natural frequencies of the dynamic behavior of the specimen. First, the test rig is run and data are collected from six sets of accelerometers. Then, a numerical analysis of the model based on the ADAMS program is derived. Finally, the measurement data of the first three fundamental frequencies are compared to the analytical result and the validation of the test rig is conducted. The results show that the developed roller rig provides good accuracy in simulating the dynamic behavior of the vehicle motion. Although the roller rig designed in this paper is intended for academia, it can easily be implemented as part of a dynamic experiment of a bogie and a vehicle body for a high-speed train as part of the research efforts in this area.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1153-1166
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• 2011

Detecting misbehavior in vehicular ad-hoc networks is very important problem with wide range of implications including safety related and congestion avoidance applications. Most misbehavior detection schemes are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners. Because of rational behavior, it is more important to detect false information than to identify misbehaving nodes. In this paper, we propose the variable precision rough sets based misbehavior detection scheme which detects false alert message and misbehaving nodes by observing their action after sending out the alert messages. In the proposed scheme, the alert information system, alert profile is constructed from valid actions of moving nodes in vehicular ad-hoc networks. Once a moving vehicle receives an alert message from another vehicle, it finds out the alert type from the alert message. When the vehicle later receives a beacon from alert raised vehicle after an elapse of time, then it computes the relative classification error by using variable precision rough sets from the alert information system. If the relative classification error is lager than the maximum allowable relative classification error of the alert type, the vehicle decides the message as false alert message. Th performance of the proposed scheme is evaluated as two metrics: correct ratio and incorrect ratio through a simulation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1D
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• pp.11-19
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• 2008

Currently, existing car following models among several basic systems of advanced vehicle systems are almost developed related to the physical relation between two vehicles except for the driver's behavior or environmental factors. But the consideration of driver's character and environmental factors on driving are very essential factors for actual application. Hence, we suggested calibrating the degree of driver's discomfort on driving that is the former study to develop a new car following model of advanced vehicle to use in actuality. The degree of driver's discomfortness (Measure-of-Alarmness; MOA)is measured related to the relationship between the following vehicle and the preceding vehicle, the environmental factors and driver's characters in ubiquitous traffic. We made up questions to drivers to obtain the general and the objective measurement of driver's MOA. And the fuzzy logic model for measurement of MOA was constructed based on the results of survey. We verified the suitability of fuzzy logic model through the computation of MOA with several scenarios. And we measured the quantitative degree of driver's discomfortness on car following related to several factors which affect drivers. In accordance with this study, development of car following model applying driver's MOA will promote the actual application of advanced vehicle more effectively than the existing models. Finally, we thought the measurement of driver's MOA will be applied significantly to evaluate safety and comfort of drivers on driving.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.224-239
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• 2023

C-ITS (Cooperative-Intelligent Transportation System) refers to user safety-oriented technology and systems that provide forward traffic situation information based on a two-way wireless communication technology between vehicles or between vehicles and infrastructure. Since the Daejeon-Sejong pilot project in 2016, the C-ITS infrastructure has been installed at various locations to provide C-ITS safety services through highway and local government demonstration projects. In this study, a methodology was developed to verify the effectiveness of the warning information using individual vehicle data collected through the Gwangju Metropolitan City C-ITS demonstration project. The analysis of the effectiveness was largely divided into driving behavior impact analysis and environmental analysis. Compliance analysis and driving safety evaluation were performed for the driving impact analysis. In addition, to supplement the inadequate collection of Probe Vehicle Data (PVD) collected during the C-ITS demonstration project, Digital Tacho Graph ( DTG ) data was additionally collected and used for effect analysis. The results of the compliance analysis showed that drivers displayed reduced driving behavior in response to warning information based on a sufficient number of valid samples. Also, the results of calculating and analyzing driving safety indicators, such as jerk and acceleration noise, revealed that driving safety was improved due to the provision of warning information.

• Korean Journal of Adult Nursing
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• v.27 no.1
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• pp.83-93
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• 2015

Purpose: This study was to investigate the relationship among the symptom recognition, health behavior compliance, and the hospital arrival time to identify factors influencing the hospital arrival time in patient with acute myocardial infarction (AMI). Methods: The subjects of this study were 200 patients with AMI in C hospital in D city. Data were analyzed using descriptive statistics, independent t-test, One way ANOVA, Pearson's correlation coefficients, and stepwise multiple liner regression tests. Results: Level of symptom recognition and health behavior compliance was low. The median value of hospital arrival time was 4.48 hours (ST-segment Elevation Ml was 2.43 hours and Non ST-segment Elevation MI was 7.83 hours). Among the studied factors, only symptom recognition had a statistically significant positive correlation with health behavior compliance (r=0.38, p<.001). Factors influencing the hospital arrival time were MI classification, diabetes mellitus (DM) and transport vehicle to the 1st hospital, and they accounted for 13% of the variance for hospital arrival time in AMI patients. Conclusion: To prevent the delay of hospital arrival time in MI patients, a more robust nursing strategic intervention according to MI classification and DM is necessary; further education on the importance of transportation utilization is also mandated.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.7-16
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• 2008

There are unique aspects of truck vehicle movements compared with the personal travel in trip chaining. This paper reports an analysis on the truck vehicle trip chaining which intercity/metropolitan/intraregional trips are classified. Data collected from the travel dairy survey is used the truck trip-chaining analysis. The pattern of trip chaining classes is classified by the GIS mapping based on orgin-destination trip information. The physical index and efficiency index for each trip diary is used to the truck vehicle activity. Truck trips lengths and time differs from its truck type, service type and travel patterns. It is shown that the efficiency of the truck trip chaining depends on vehicle types and its delivery patterns. There are many other topics for research on trip chaining modeling such as the classification of trip chain, time use and mode choice by trip chaining.