Pressure waves are generated and propagate in tunnel when train enters a tunnel with high speed. Compression wave due to the entry of train head propagates along the tunnel and is reflected at tunnel exit as expansion wave. While expansion wave due to the entry of train tail propagates along the tunnel and is reflected at tunnel exit as compression wave. These pressure waves are repeatedly propagated and reflected at tunnel entrance and exit. Severe pressure change per second causes ear-discomfort for passengers in cabin and micro pressure wave around tunnel exit. It is necessary to analyze the transient pressure phenomena in tunnel qualitatively and quantitatively, because pressure change rate is considered as one of major design parameters for an optimal tunnel cross sectional area and the repeated fatigue force on car body. In this study, we developed the characteristics method analysis based on fixed mesh system and compared with the results of real train test. The results of simulation agreed with that of experiment.
Park, Byoung-Jik;Shin, Hyun-Jun;Yoo, Yong-Ho;Park, Jin-Ouk;Kim, Hwi-Seong
Journal of Korean Tunnelling and Underground Space Association
/
v.18
no.5
/
pp.413-418
/
2016
Recently, a mega project such as Korea-China or Korea-Japan undersea tunnel project has been emerged for detail discussion and the interest in undersea tunnel is on the rise. More severe damage by train fire is expected in undersea tunnel comparing to ground tunnel and thus the study on more efficient fire extinguishing system, besides existing disaster prevention design is underway. To that end, a full-scale fire tests using CAF fire extinguishing system which has been developed by modifying traditional foam fire extinguishing system for fire suppression at rescue station in timely manner were conducted over 7 times. The test was conducted after setting the rescue station in virtual tunnel with a car of KTX. As a result of using compressed air foam directly to the fire source, 30 liter of Heptane combustibles was extinguished within 1 minutes. Applicability of compressed air foam to train fire at rescue station in undersea tunnel was has been proven and further study is considered required while changing the nozzle angle and location so as to achieve quick and easy extinguishing goal, making use of the advantage of CAF, as well as to reduce the fire water and chemicals required.
Journal of the Korea Academia-Industrial cooperation Society
/
v.19
no.1
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pp.75-84
/
2018
Increasing the operation rate of components and stabilizing the operation through timely management of the core parts are crucial for improving the efficiency of the railroad maintenance industry. The demand for diagnosis technology to assess the condition of rolling stock components, which employs history management and automated big data analysis, has increased to satisfy both aspects of increasing reliability and reducing the maintenance cost of the core components to cope with the trend of rapid maintenance. This study developed a big data platform-based system to manage the rolling stock component condition to acquire, process, and analyze the big data generated at onboard and wayside devices of railroad cars in real time. The system can monitor the conditions of the railroad car component and system resources in real time. The study also proposed a machine learning technique that enabled the distributed and parallel processing of the acquired big data and automatic component fault diagnosis. The test, which used the virtual instance generation system of the Amazon Web Service, proved that the algorithm applying the distributed and parallel technology decreased the runtime and confirmed the fault diagnosis model utilizing the random forest machine learning for predicting the condition of the bearing and wheel parts with 83% accuracy.
KIPS Transactions on Computer and Communication Systems
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v.6
no.6
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pp.271-280
/
2017
In this paper, we propose a new safety system composed of wearable devices, driver's seat belt, and integrating controllers. The wearable device and driver's seat belt capture driver's biological information, while the integrating controller analyzes captured signal to alarm the driver or directly control the car appropriately according to the status of the driver. Previous studies regarding driver's safety from driver's seat, steering wheel, or facial camera to capture driver's physiological signal and facial information had difficulties in gathering accurate and continuous signals because the sensors required the upright posture of the driver. Utilizing wearable sensors, however, our proposed system can obtain continuous and highly accurate signals compared to the previous researches. Our advanced wearable apparatus features a sensor that measures the heart rate, skin conductivity, and skin temperature and applies filters to eliminate the noise generated by the automobile. Moreover, the acceleration sensor and the gyro sensor in our wearable device enable the reduction of the measurement errors. Based on the collected bio-signals, the criteria for identifying the driver's condition were presented. The accredited certification body has verified that the devices has the accuracy of the level of medical care. The laboratory test and the real automobile test demonstrate that our proposed system is good for the measurement of the driver's condition.
Kim In-Tae;Oh Seung-Hwan;Han Seung-Hwan;Cho Yoon-Ho
International Journal of Highway Engineering
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v.8
no.3
s.29
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pp.89-103
/
2006
This study develops the tire/pavement noise measuring trailer that can minimize the effect of various environmental noise and evaluate road noise characteristics without regard to time and spots. As literature reviews, it is examined into road noise characteristics and case studies of various CPX Trailer, and made a development plan of device. Based on these, HEART CPX Trailer is developed and conduct experiments for verification of the semi-anechoic chamber suitability, precision and field application of device. In the result of the experiment for verification of semi-anechoic chamber suitability, we can make sure that it is suitable and reliable among frequency bands. In the test of repetition measurement, we can verify excellent measurement accuracy among speeds and microphone's locations. In case of field tests using HEART CPX Trailer, it is founded that the result is similar to CPB test result carried out by Chung-Ang university in 2003. It can be concluded caused that the effect of environmental noise in and around the road including mechanical noise of a tow car was excluded. This paper confirmed and suggested that HEART CPX Trailer is suitable for evaluation of real road noise characteristics.
Zoz, H.;Benz, H.U.;Huettebraeucker, K.;Furken, L.;Ren, H.;Reichardt, R.
Proceedings of the Korean Powder Metallurgy Institute Conference
/
2000.04a
/
pp.9-10
/
2000
An important business-field of world-wide steel-industry is the coating of thin metal-sheets with zinc, zinc-aluminum and aluminum based materials. These products mostly go into automotive industry. in particular for the car-body. into building and construction industry as well as household appliances. Due to mass-production, the processing is done in large continuously operating plants where the mostly cold-rolled metal-strip as the substrate is handled in coils up to 40 tons unwind before and rolled up again after passing the processing plant which includes cleaning, annealing, hot-dip galvanizing / aluminizing and chemical treatment. In the liquid Zn, Zn-AI, AI-Zn and AI-Si bathes a combined action of corrosion and wear under high temperature and high stress onto the transfer components (rolls) accounts for major economic losses. Most critical here are the bearing systems of these rolls operating in the liquid system. Rolls in liquid system can not be avoided as they are needed to transfer the steel-strip into and out of the crucible. Since several years, ceramic roller bearings are tested here [1.2], however, in particular due to uncontrollable Slag-impurities within the hot bath [3], slide bearings are still expected to be of a higher potential [4]. The today's state of the art is the application of slide bearings based on Stellite\ulcorneragainst Stellite which is in general a 50-60 wt% Co-matrix with incorporated Cr- and W-carbides and other composites. Indeed Stellite is used as the bearing-material as of it's chemical properties (does not go into solution), the physical properties in particular with poor lubricating properties are not satisfying at all. To increase the Sliding behavior in the bearing system, about 0.15-0.2 wt% of lead has been added into the hot-bath in the past. Due to environmental regulations. this had to be reduced dramatically_ This together with the heavily increasing production rates expressed by increased velocity of the substrate-steel-band up to 200 m/min and increased tractate power up to 10 tons in modern plants. leads to life times of the bearings of a few up to several days only. To improve this situation. the Mechanical Alloying (MA) TeChnique [5.6.7.8] is used to prOduce advanced Stellite-based bearing materials. A lubricating phase is introduced into Stellite-powder-material by MA, the composite-powder-particles are coated by High Energy Milling (HEM) in order to produce bearing-bushes of approximately 12 kg by Sintering, Liquid Phase Sintering (LPS) and Hot Isostatic Pressing (HIP). The chemical and physical behavior of samples as well as the bearing systems in the hot galvanizing / aluminizing plant are discussed. DependenCies like lubricant material and composite, LPS-binder and composite, particle shape and PM-route with respect to achievable density. (temperature--) shock-reSistibility and corrosive-wear behavior will be described. The materials are characterized by particle size analysis (laser diffraction), scanning electron microscopy and X-ray diffraction. corrosive-wear behavior is determined using a special cylinder-in-bush apparatus (CIBA) as well as field-test in real production condition. Part I of this work describes the initial testing phase where different sample materials are produced, characterized, consolidated and tested in the CIBA under a common AI-Zn-system. The results are discussed and the material-system for the large components to be produced for the field test in real production condition is decided. Outlook: Part II of this work will describe the field test in a hot-dip-galvanizing/aluminizing plant of the mechanically alloyed bearing bushes under aluminum-rich liquid metal. Alter testing, the bushes will be characterized and obtained results with respect to wear. expected lifetime, surface roughness and infiltration will be discussed. Part III of this project will describe a second initial testing phase where the won results of part 1+11 will be transferred to the AI-Si system. Part IV of this project will describe the field test in a hot-dip-aluminizing plant of the mechanically alloyed bearing bushes under aluminum liquid metal. After testing. the bushes will be characterized and obtained results with respect to wear. expected lifetime, surface roughness and infiltration will be discussed.
In these days, 3D dynamic simulation is closely related to many industries. In the past, physically-based 3D simulation was used mainly in the car crash or construction related fields, but it also plays an important role in movies or games today. Many mathematical computations are needed to represent the 3D object realistically, but it is difficult to process a large amount of calculations for simulation of application based on CPU in real-time. Recently, with the advanced graphic hardware and improved architecture, GPU can be utilized for the general purposes of computation function as well as graphic computation. Many approaches using GPU have been applied for various research fields. In this paper, we analyze the performance variation of two cloth simulation algorithms based on GPU according to the change of execution properties of GPU shaders in oder to optimize the performance of GPU-based cloth simulation. Cloth simulation is implemented by the spring centric algorithm and node centric algorithm with GPU parallel computing using compute shader of GLSL 4.3. We compare the performance of between these algorithms according to the change of the size and dimension of work group. The experiment is repeated to 10 times during 5,000 frames for each test and experimental results are provided by averaging of FPS. The experimental result shows that the node centric algorithm is executed in higher speed than the spring centric algorithm.
Recently, lip-reading has been studied actively as an auxiliary method of automatic speech recognition(ASR) in noisy environments. However, almost of research results were obtained based on the database constructed in indoor condition. So, we dont know how developed lip-reading algorithms are robust to dynamic variation of image. Currently we have developed a lip-reading system based on image-transform based algorithm. This system recognize 22 words and this word recognizer achieves word recognition of up to 53.54%. In this paper we present how stable the lip-reading system is in environmental variance and what the main variant factors are about dropping off in word-recognition performance. For studying lip-reading robustness we consider spatial valiance (translation, rotation, scaling) and illumination variance. Two kinds of test data are used. One Is the simulated lip image database and the other is real dynamic database captured in car environment. As a result of our experiment, we show that the spatial variance is one of degradations factors of lip reading performance. But the most important factor of degradation is not the spatial variance. The illumination variances make severe reduction of recognition rates as much as 70%. In conclusion, robust lip reading algorithms against illumination variances should be developed for using lip reading as a complementary method of ASR.
Kim, Dong-Hyun;Lee, Sang-Bum;Kim, Kyung-Hoon;Yoon, Dong-Jin;Bae, Dong-Myung
Journal of the Korean Society for Nondestructive Testing
/
v.34
no.2
/
pp.176-183
/
2014
Acoustic emission testing (AET) of cylinders is advantageous in that it can be directly conducted on cylinders installed in a car, without needing to dissemble them on a real-time basis. Therefore, users prefer AET over other nondestructive testing methods. Owing to these advantages of AET, it has been approved by the Department of Transportation of the U.S. as a safety evaluation method for pressure containers or as an alternative to the hydroproof testing method. This paper presents a study of the quantitative evaluation criteria for a container having ultrasonic testing defects and also for Type 1 and Type 2 gas cylinders, which are defective seamless pressure containers provided by NK, a manufacturer of pressure containers. For the Type 1 cylinder, the process from crack growth to leak was observed in a repetitive fatigue test using a 113 L container according to ASTM E 1419-02. Further, for the Type 2 cylinder, integrity was evaluated using a 119 L sound container and a container damaged by hydraulic pressure, by the slow-fill method according to ASTM E 2191-02. Based on the AET results of the Type 1 and Type 2 cylinders, quantitative evaluation criteria were established for a defective and non-defective container.
A lot of license plate data is required for car number recognition. License plate data needs to be balanced from past license plates to the latest license plates. However, it is difficult to obtain data from the actual past license plate to the latest ones. In order to solve this problem, a license plate recognition study through deep learning is being conducted by creating a synthetic license plates. Since the synthetic data have differences from real data, and various data augmentation techniques are used to solve these problems. Existing data augmentation simply used methods such as brightness, rotation, affine transformation, blur, and noise. In this paper, we apply a style transformation method that transforms synthetic data into real-world data styles with data augmentation methods. In addition, real license plate data are noisy when it is captured from a distance and under the dark environment. If we simply recognize characters with input data, chances of misrecognition are high. To improve character recognition, in this paper, we applied the DeblurGANv2 method as a quality improvement method for character recognition, increasing the accuracy of license plate recognition. The method of deep learning for license plate detection and license plate number recognition used YOLO-V5. To determine the performance of the synthetic license plate data, we construct a test set by collecting our own secured license plates. License plate detection without style conversion recorded 0.614 mAP. As a result of applying the style transformation, we confirm that the license plate detection performance was improved by recording 0.679mAP. In addition, the successul detection rate without image enhancement was 0.872, and the detection rate was 0.915 after image enhancement, confirming that the performance improved.
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