• Journal of the Korean Society for Railway
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• v.13 no.6
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• pp.565-569
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• 2010

Sleepers perform bearing rails and are underneath rails. Therefore, the current and voltage of rails are related to the resistance of sleepers. In case that the resistance of sleepers are low, operation problems of relays in tr ack circuits are occur because of flowing leakage current through sleepers. So the condition that the track circuit is always occupied by a train is kept. Currently, the creosote has been used in wood sleepers due to prevention against putrefaction. After a long time, the material is changeable to the chemistry material bases on carbon dioxide or carbon. So, the insulation resistance of wood sleepers is lower than the initial insulation resistance. In case of effecting wood sleepers as conductors, amplitude of the current and voltage on rails is decreased. This phenomenon causes that a train does not receive signals. In this paper, four-network model on the track circuit including the insulation resistance of sleepers is suggested. Also, the standard value of the resistance in straight section is proposed in the wood sleeper.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.11
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• pp.1161-1167
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• 2015

A slender guideway is essential in improving aesthetically and reducing its construction cost which accounts for about 70% of overall investment for maglev system. As the slender guideway, however, may increase its deformation, its effect on levitation stability and guidance performance needs to be analyzed. The purpose of this study is to analyze the effect on guidance characteristics of maglev due to the lateral deformation of the guideway girder and lateral irregularity of guiderail. For doing this, 3D model considering lateral deformation of girder and irregularity of rail of the guideway is developed. Using the dynamic interaction model integrated with the proposed guideway and maglev vehicle including electromagnetics and its controller, guidance characteristics of maglev are analyzed. It is analyzed that the effect on lateral deformation of girder is relatively small compared to deformation on the lateral irregularities of guiderail.

• Journal of the Korean Society for Railway
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• v.11 no.6
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• pp.536-542
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• 2008

In concrete slab track, the signal current using wayside transmitter of ATP (Automatic Train Protection) system is influenced by reinforcing bars. The magnetic coupling between reinforcing bars and wayside transmitter of ATP system as a filter makes an input current distorted. So, it makes an alternating current signal with a desirable size not transmit to on-board system of a train. Way to decrease the distortion of an input current signal frequency is to avoid maximum induction current frequency. And the induction phenomenon between reinforcing bars insulated and wayside transmitter of ATP system does not occur. In this paper, we represent the model about wayside transmitter of ATP system and reinforcing bars on the concrete slab tracks, and calculated the parameters demanded for the model. Also, we demonstrated it through the Maxwell program. Furthermore, we calculated impedance on wayside transmitter used in KVB system and ERTMS/ETCS system which are a kind of ATP system, frequency response of induction current, using Matlab, and demonstrated the validity of it, using PSpice program.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.11
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• pp.909-917
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• 2021

In this work, a one-dimensional combustor solver was constructed for the scramjet control m odel. The governing equations for fluid flow, Arrhenius based combustion kinetics, and the inje ction model were implemented into the solver. In order to validate the solver, the zero-dimensi onal ignition delay problem and one-dimensional scramjet combustion problem were considered and showed that the solver successfully reproduced the results from the literature. Subsequentl y, a ramjet analysis algorithm under subsonic speed conditions was constructed, and a study o n the inlet Mach number of the combustor was carried out through the thermal choking locatio ns at ram conditions. In such conditions, a model for precombustion shock train analysis was i mplemented, and the algorithm for transition section analysis was introduced. In addition, in or der to determine the appropriateness of the ram mode analysis in the code, the occurrence of a n unstart was studied through the length of the pseudo-shock in the isolator. A performance a nalysis study was carried out according to the geometry of the combustor.

• Wind and Structures
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• v.35 no.4
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• pp.269-285
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• 2022

The pressure-mitigating effects of a high-speed train passing through a tunnel with a partially reduced cross-section are investigated via the numerical approach. A compressible, three-dimensional RNG k-ε turbulence model and a hybrid mesh strategy are adopted to reproduce that event, which is validated by the moving model test. Three step-like tunnel forms and two additional transitions at the tunnel junction are proposed and their aerodynamic performance is compared and scrutinized with a constant cross-sectional tunnel as the benchmark. The results show that the tunnel step is unrelated to the pressure mitigation effects since the case of a double-step tunnel has no advantage in comparison to a single-step tunnel, but the excavated volume is an essential matter. The pressure peaks are reduced at different levels along with the increase of the excavated earth volume and the peaks are either fitted with power or logarithmic function relationships. In addition, the Arc and Oblique-transitions have very limited gaps, and their pressure curves are identical to each other, whereas the Rec-transition leads to relatively lower pressure peaks in C_Pmax, C_Pmin, and ΔC_P, with 5.2%, 4.0%, and 4.1% relieved compared with Oblique-transition. This study could provide guidance for the design of the novel railway tunnel.

• Journal of Information Technology Services
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• v.19 no.5
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• pp.83-91
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• 2020

Language Models such as BERT has been an important factor of deep learning-based natural language processing. Pre-training the transformer-based language models would be computationally expensive since they are consist of deep and broad architecture and layers using an attention mechanism and also require huge amount of data to train. Hence, it became mandatory to do fine-tuning large pre-trained language models which are trained by Google or some companies can afford the resources and cost. There are various techniques for fine tuning the language models and this paper examines three techniques, which are data augmentation, tuning the hyper paramters and partly re-constructing the neural networks. For data augmentation, we use no-answer augmentation and back-translation method. Also, some useful combinations of hyper parameters are observed by conducting a number of experiments. Finally, we have GRU, LSTM networks to boost our model performance with adding those networks to BERT pre-trained model. We do fine-tuning the pre-trained korean-based language model through the methods mentioned above and push the F1 score from baseline up to 89.66. Moreover, some failure attempts give us important lessons and tell us the further direction in a good way.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.589-594
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• 2004

In design of suspension system for KHST, it was applied the approximated optimization method using meta-models which called Response Surface Model and Neural Network Model for 29 design variables and 46 performance index. These models was coded using correlation between design variables and performance indices that is made by the 66 times iterative execution through the design of experimental table consisted orthogonal array L32 and D-Optimal design table. The results show that the optimization process is very efficient and simply applicable for complex mechanical system such as railway vehicle system. Also it was compared with the sensitivity of some design variables in order to know the characteristics of two models. This paper describes the general method for dynamic analysis and design process of railway vehicle system applied to KHST development, and proposed the efficient methods for vibration mode analysis process dealing with test data and the function based approximation method using meta-model applicable for a complex mechanical system. This method will be able to apply to the other railway vehicle system in oder to systematize and generalize the design process of railway vehicle dynamic system.

• Steel and Composite Structures
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• v.24 no.5
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• pp.635-641
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• 2017

Safety service improvement and development of efficient maintenance strategies for corroded steel structures are undeniably essential. Therefore, understanding the influence of damage caused by corrosion on the remaining load-carrying capacities such as tensile strength is required. In this study, artificial neural network (ANN) approach is proposed in order to produce a simple, accurate, and inexpensive method developed by using tensile test results, material properties and finite element method (FEM) results to train the ANN model. Initially in reproducing corroded model process, FEM was used to obtain tensile strength of artificial corroded plates, for which surface is developed by a spatial autocorrelation model. By using the corroded surface data and material properties as input data, with tensile strength as the output data, the ANN model could be trained. The accuracy of the ANN result was then verified by using leave-one-out cross-validation (LOOCV). As a result, it was confirmed that the accuracy of the ANN approach and the final output equation was developed for predicting tensile strength without tensile test results and FEM in further work. Though previous studies have been conducted, the accuracy results are still lower than the proposed ANN approach. Hence, the proposed ANN model now enables us to have a simple, rapid, and inexpensive method to predict residual tensile strength more accurately due to corrosion in steel structures.

• Nuclear Engineering and Technology
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• v.31 no.4
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• pp.375-384
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• 1999

The credibility of CHECWORKS FAC model analysis was evaluated for plant application in a model plant chosen for demonstration. The operation condition at each pipe component was defined before the wear rate analysis by plant data base, water chemistry analysis, and network flow analysis. The predicted wear was compared with the measured wear for 57 sample components selected from 43 susceptible line groups analysed. The inspected 57 locations represent components of highest predicted wear in each line group. Both absolute value and relative ranking comparisons indicated reasonable correlations between the predicted and the measured values. Four components showed much higher measured wear rates than the predicted ones in the feed water train from main feed water pump discharge to steam generator, probably due to high hydrazine concentration operation the effect of which had not been incorporated into the CHECWORKS model. The measured wear was higher than the predicted one consistently for components with least susceptibility to FAC. It is believed that the conservatism maintained during UT data analysis dominated the measurement accuracy. A great deal of enhancement is anticipated over the current plant pipe management program when a comprehensive plant pipe management program is implemented based on the model analysis.

• Transactions of Materials Processing
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• v.29 no.5
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• pp.282-289
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• 2020

Flexible roll forming is an advanced sheet-metal-forming process that allows the production of parts with various cross-sections. During the flexible process, material is subjected to three-dimensional deformation such as transverse bending, inhomogeneous elongations, or contraction. Because of the effects of process variables on the quality of the roll-formed products, the approaches used to investigate the roll-forming process have been largely dependent on experience and trial- and-error methods. Web-warping is one of the major shape defects encountered in flexible roll forming. In this study, an SVR model was developed to predict the web-warping during the flexible roll forming process. In the development of the SVR model, three process parameters, namely the forming-roll speed condition, leveling-roll height, and bend angle were considered as the model inputs, and the web-warping height was used as the response variable for three blank shapes; rectangular, concave, and convex shape. MATLAB software was used to train the SVR model and optimize three hyperparameters (λ, ε, and γ). To evaluate the SVR model performance, the statistical analysis was carried out based on the three indicators: the root-mean-square error, mean absolute error, and relative root-mean-square error.