• Tunnel and Underground Space
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• v.13 no.6
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• pp.434-443
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• 2003

In this study, it was purposed to develop the new method for the prediction of pollutant concentration in road tunnels. The new method was the use of artificial neural network with the back-propagation algorithm which can model the non-linear system of tunnel environment. This network system was separated into two parts as the visibility and the CO concentration. For this study, data was collected from two highway road tunnels on Yeongdong Expressway. The tunnels have two lanes with one-way direction and adopt the longitudinal ventilation system. The actually measured data from the tunnels was used to develop the neural network system for the prediction of pollutant concentration. The output results from the newly developed neural network system were analysed and compared with the calculated values by PIARC method. Results showed that the prediction accuracy by the neural network system was approximately five times better than the one by PIARC method. In addition, the system predicted much more accurately at the situation where the drivers have to be stayed for a while in tunnels caused by the low velocity of vehicles.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.123-131
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• 2012

As the price of traditional fuels soar, the alternatives are becoming more viable. And manufacturers are promoting the growing viability of electric and biofuel-powered vehicles through longer warranties. Now, these longer green environment (emission)warranties, sometimes called extended warranties or "super warranties," have been adapted. The main result of this paper is to present a new method to approximate a bivariate warranty function by using Radial Basis Function Network with application of Radon Transform and its inverse which is used to reduce the dimension of the warranty space. This method consist of the following stages: First, by using the Radon Transform, the bivariate warranty function can be reduced to one dimensional function. Second, each of the one dimensional functions is approximated by using neural network technique into neural sub-networks. Third, these neural sub-networks are combined together to form the final approximation neural network. Four, by using the inverse of radon transform to this final approximation neural network we get the approximation to the given function. Also, we apply the above method to some green warranty data of automotive vehicle company.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.127-135
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• 2017

Recently, the most brand new vehicles contain a lot of ECU for comfortable and safety driving environments. For efficient communication network among ECUs, almost car manufactures use CAN protocol which enables to decrease the number of communication lines dramatically and ensures higher data transmission reliability. However, CAN dose not ensure authentication of CAN data frame. So it is vulnerable to replay-attack on CAN data frame. This paper proposes the practical message authentication technique for In-vehicle CAN. To transmit data and MAC together, it is very useful to use the short length of MAC after considering limited space of CAN data frame. However to ensure safety of MAC, additional technique is required. We suggested a message authentication technique that can be usefully applied to build a safety network inside the vehicle because it considers limited data payload of CAN.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.2
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• pp.225-230
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• 2017

To generate mechanical movements in one-shot devices such as missiles and space launch vehicles, pyrotechnic mechanical device(PMD) such as pin pullers using pyrotechnic charge has been widely used. Reliability prediction of pin pullers is crucial to successfully execute target missions for the one-shot devices. Because the pin pullers require destructive tests to evaluate their reliability, one would need about 3,000 samples of success to guarantee a reliability of 99.9 % with a confidence level of 95 %. This paper suggests the application of a probit model using the charge amount as a functional parameter for estimation of functional reliability of pin puller. To guarantee target reliability, we propose estimation methods of the lower bound of functional reliability by applying the probit model. Given lower bound of functional reliability, we quantitatively show that the optimum amount of charge increases as the number of samples decreases. Along with a variety of simulations the validity of our new model via real test results is confirmed.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.11a
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• pp.252-255
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• 2007

Recently military industrial company, utilizing company funded R&D and goverment and industry contracts, has developed ACTS/DACS technology. This technology can be utilized to rapidly steer "smart" bullets, "smart" rounds, tactical missile, cruise missile and kill vehicles for both endo- and exoatmospheric applications. The ACTS/DACS typically consists of a Smart Bus Controller(SCB), a proprietary network firing bus, Smart Pyrotechnic Devices(SPD), rocket motors, and a structure. The SCB communicates with the SPDs over the propretary network firing bus. Each rocket motor contains an SPD which provides rocket motor ignition. Firing energy is stored locally in the SPD so surge currents do not occur in the system as rocket motors are fired. This approach allows multiple, truly simultaneous firings without the need for large, dedicated batteries. Each SPD also functions as a network tranceiver and high reliability fir set all in the space of a single-sided 10 millimeter diameter circuit. The present work develops a new means for igniting explosive materials. The volume of semiconductor bridge (SCB) is over 30 times smaller than a conventional hot wire. We believe that the present work has a potential for development of a new igniter such as smart pyrotechnic device.

• Journal of the Korean Society for Railway
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• v.13 no.4
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• pp.382-388
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• 2010

This paper describes the standardized finite element model for carbody structures of railway vehicle made of sandwich composites. Recently, sandwich composites were widely used to railway vehicle due to the improvement of energy efficiency, high specific stiffness and strength, weight reduction and space saving in korea. Therefore, structural integrity should be verified using finite element analysis prior to the manufacture of composite railway vehicle. The standardized finite element model for composite carbody structures was introduced through comparing the results of real structural test under vertical, compressive, twisting load and natural frequency test of various railway vehicles in this study. The results show that the quadratic shell element is suitable to model the reinforced metal frame used to improve the flexural stiffness of sandwich panel compared to beam element, and layered shell and solid element are recommended to model the skin and honeycomb core of sandwich panel compared to sandwich shell element. Also, the proposed standard finite element model has the merit of being applied to crashworthiness problem without modifications of finite element model.

• Journal of the Korean Society for Precision Engineering
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• v.34 no.1
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• pp.41-46
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• 2017

Magnetically levitated (Maglev) vehicles maintain a constant air gap between guideway and car bogie, and thereby achieves non-contact riding. Since the straightness and the flatness of the guideway directly affect the stability of levitation as well as the ride comfort, it is necessary to monitor the status of the guideway and to alert the train operators to any abnormal conditions. In order to develop a signal processing algorithm that extracts guideway irregularities from sensor data, virtual testing using a simulation model would be convenient for analyzing the exact effects of any input as long as the model describes the actual system accurately. Simulation model can also be used as an estimation model. In this paper, we develop a state-space dynamic model of a maglev vehicle system, running on the guideway that contains jumps. This model contains not only the dynamics of the vehicle, but also the descriptions of the power amplifier, the anti-aliasing filter and the sampling delay. A test rig is built for the validation of the model. The test rig consists of a small-scale maglev vehicle, tracks with artificial jumps, and various sensors measuring displacements, accelerations, and coil currents. The experimental data matches well with those from the simulation model, indicating the validity of the model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.618-622
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• 2004

The vibration test system of SITC(Satellite Integration and Test Center) at KARI(Korea Aerospace Research Institute) has been used successfully for the environmental tests of a majority of korean space programs, such as KOMPSAT, Koreasat KITSAT, STSAT and KSR program since 1996. To meet the recent needs of large size test facility available for the vibrational tests of the huge launch vehicles and tole-communication satellites which will be developed in the near future, KARI undertook to construct the large size multi-electromagnetic shaking system with 3 $\times$ 3m head expander system. The new system will consist of three electromagnetic shakers which has 160 kN thrust force individually, and be able te sustain up to 8 tons test load and 300 kNm overturing moment. And to avoid the tremendous cost and effort to furnish the seismic block with large size and weight, it will adopt a Lin-E-Air type configuration with which the seismic block is less severe than a Solid-Truninon type. In addition, to fulfill the strong requirement of high overturning moment the additional guidance system including a central bearing system on a central support and several pad bearings around the head expander body is now considered. This paper describes the configuration and the design parameters of the multi-shaking system which is under development by KARI's engineers.

• Journal of Ocean Engineering and Technology
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• v.19 no.2 s.63
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• pp.67-73
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• 2005

This paper describes depth, heading and speed control of an underwater vehicle that has four stern thrusters of which forces are coupled in the diving and, steering motion, as well as the speed of the vehicle. The optimal linear quadratic controller is designed based on a linearized- state space model, developed by combining the dynamic equations of speed, steering and diving motion. The designed controller gives provides an optimal thrust distribution, minimizing the given performance index to control speed, depth and heading simultaneously. To validate the performance of the controller, a simulation and tank-test are carried out with DUSAUV (Dual Use Semi-Autonomous Underwater Vehicle), developed by KORDI as a test-bed for testing new underwater technologies. Optimal gains of the controller are tuned, using a computer simulation environment with a nonlinear 6-DOF numerical DUSAUV model, developed by PMM (Planner Motion Mechanism) test. To verify the performance of the presented controller in experiment, a tank-test with DUSAUV is carried out in the ocean engineering basin in KORDI. The experimental results are also compared with the simulation results to investigate the accordance of the numerical and the real mode.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.1029-1035
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• 2013

This paper proposes a real time lane detection algorithm using LRF (Laser Range Finder) for autonomous navigation of a mobile robot. There are many technologies for safety of the vehicles such as airbags, ABS, EPS etc. The real time lane detection is a fundamental requirement for an automobile system that utilizes outside information of automobiles. Representative methods of lane recognition are vision-based and LRF-based systems. By the vision-based system, recognition of environment for three dimensional space becomes excellent only in good conditions for capturing images. However there are so many unexpected barriers such as bad illumination, occlusions, and vibrations that the vision cannot be used for satisfying the fundamental requirement. In this paper, we introduce a three dimensional lane detection algorithm using LRF, which is very robust against the illumination. For the three dimensional lane detections, the laser reflection difference between the asphalt and lane according to the color and distance has been utilized with the extraction of feature points. Also a stable tracking algorithm is introduced empirically in this research. The performance of the proposed algorithm of lane detection and tracking has been verified through the real experiments.