• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.594-600
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• 2021

Curved beam structures are generally used as components in structures such as railroad bridges and vehicles. The stability analysis of curved beams has been studied by a large number of researchers. Due to the complexities of structural components, it is difficult to obtain an analytical solution for any boundary conditions. In order to overcome these difficulties, the differential quadrature method (DQM) has been applied for a large number of cases. In this study, DQM was used to solve the complicated partial differential equations for buckling analysis of curved beams. The governing differential equation was deduced and solved for beams subjected to uniformly distributed radial loads. Critical loads were calculated with various opening angles, boundary conditions, and parameters. The results of the DQM were compared with exact solutions for available cases, and the DQM gave outstanding accuracy even when only a small number of grid points was used. Critical loads were also calculated for the in-plane inextensional buckling of the asymmetric curved beams, and two theories were compared. The study of a beam with extensibility of the arch axis shows that the effects on the critical loads are significant.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.541-549
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• 2018

This paper deals with the braking dynamic behavior of diesel electric locomotive pulling domestic cargo and passenger vehicles. Friction coefficient, pneumatic pressure, and running resistance affecting the braking system were tested. For the friction coefficient, the Dynamo test was performed with reference to UIC 541-4. The results are analyzed by multivariate regression and the relationship between braking force and ititial velocity is presented. The pneumatic pressure were classified into service braking and emergency braking. In order to reflect the characteristics of the brake valve and piping, the pressure rising over time was measured in the vehicle. In order to reflect the external force acting on the vehicle, we carried out the test of EN 14067-4 and presented the second order polynomial formula on a running resistance. The running resistance test results were compared with other countries. The dynamic behavior of a diesel electric locomotive running on a straight flat track based on vehicle resources, friction coefficient, braking pressure, and running resistance is simulated using the time integration presented in EN 14531-1. The simulation results were compared and verified with the vehicle braking test results. The results of this study can be used to analyze the dynamic braking behavior of a train. Also, it is expected that various parameters affecting braking in vehicle design can be analyzed and used as basic data for braking performance improvement.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.75-82
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• 2021

Low-temperature combustion (LTC) strategies, such as HCCI (Homogeneous Charge Compression Ignition), PCCI (Premixed Charge Compression Ignition), and RCCI (Reactivity Controlled Compression Ignition), have been developed to effectively reduce NOx and PM while increasing the thermal efficiency of diesel engines. Through numerical analysis, this study examined the effects of the injection timing and two-stage injection ratio of diesel fuel, a highly reactive fuel, on the performance and exhaust gas of RCCI engines using gasoline as the low reactive fuel and diesel as the highly reactive fuel. In the case of two-stage injection, combustion slows down if the first injection timing is too advanced. The combustion temperature decreases, resulting in lower combustion performance and an increase in HC and CO. The injection timing of approximately -60°ATDC is considered the optimal injection timing considering the combustion performance, exhaust gas, and maximum pressure rise rate. When the second injection timing was changed during the two-stage injection, considering the combustion performance, exhaust gas, and the maximum pressure increase rate, it was judged to be optimal around -30°ATDC. In the case of two-stage injection, the optimal result was obtained when the first injection amount was set to approximately 60%. Finally, a two-stage injection rather than a single injection was considered more effective on the combustion performance and exhaust gas.

• Journal of Korean Society of Forest Science
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• v.111 no.2
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• pp.287-301
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• 2022

This study aims to propose a crane-tip control method to intuitively control the end-effector vertically or horizontally for improving the crane work efficiency and to confirm the control performance. To verify the control performance based on experimental variables, a laboratory-scale crane was manufactured using an electric cylinder. Through a forward and reverse kinematics analysis, the crane was configured to output the position coordinates of the current crane-tip and the joint angle at each target point. Furthermore, a method of generating waypoints was used, and a dead band using lateral boundary offset (LBO) was set. Appropriate parameters were selected using bang-bang control, which confirmed that the number of waypoints and LBO radius were associated with positioning error, and the cylinder speed was related to the lead time. With increased number of waypoints and decreased LBO radius, the positioning error and the lead time also decreased as the cylinder speed decreased. Using the proportional control, when the cylinder velocity was changed at every control cycle, the lead time was greatly reduced; however, the actual control pattern was controlled by repeating over and undershoot in a large range. Therefore, proportional control was performed by additionally applying velocity gain that can relatively change the speed of each cylinder. Since the control performed with in a range of 10 mm, it was verified th at th e crane-tip control can be ach ieved with only th e proportional control to which the velocity gain was applied in a control cycle of 20 ms.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.991-1005
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• 2022

Satellite imaging is an effective supplementary data source for detecting and verifying nuclear activity. It is also highly beneficial in regions with limited access and information, such as nuclear installations. Time series analysis, in particular, can identify the process of preparing for the conduction of a nuclear experiment, such as relocating equipment or changing facilities. Differences in the semantic segmentation findings of time series photos were employed in this work to detect changes in meaningful items connected to nuclear activity. Building, road, and small object datasets made of KOMPSAT 3/3A photos given by AIHub were used to train deep learning models such as U-Net, PSPNet, and Attention U-Net. To pick relevant models for targets, many model parameters were adjusted. The final change detection was carried out by including object information into the first change detection, which was obtained as the difference in semantic segmentation findings. The experiment findings demonstrated that the suggested approach could effectively identify altered pixels. Although the suggested approach is dependent on the accuracy of semantic segmentation findings, it is envisaged that as the dataset for the region of interest grows in the future, so will the relevant scope of the proposed method.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.543-552
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• 2022

When frost occurs, crops are directly damaged. When crops come into contact with low temperatures, tissues freeze, which hardens and destroys the cell membranes or chloroplasts, or dry cells to death. In July 2020, a sudden sub-zero weather and frost hit the Minas Gerais state of Brazil, the world's largest coffee producer, damaging about 30% of local coffee trees. As a result, coffee prices have risen significantly due to the damage, and farmers with severe damage can produce coffee only after three years for crops to recover, which is expected to cause long-term damage. In this paper, we tried to predict frost using frost generation data and weather observation data provided by the Korea Meteorological Administration to prevent severe frost. A model was constructed by reflecting weather factors such as wind speed, temperature, humidity, precipitation, and cloudiness. Using XGB(eXtreme Gradient Boosting), SVM(Support Vector Machine), Random Forest, and MLP(Multi Layer perceptron) models, various hyper parameters were applied as training data to select the best model for each model. Finally, the results were evaluated as accuracy(acc) and CSI(Critical Success Index) in test data. XGB was the best model compared to other models with 90.4% ac and 64.4% CSI, followed by SVM with 89.7% ac and 61.2% CSI. Random Forest and MLP showed similar performance with about 89% ac and about 60% CSI.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.211-218
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• 2021

This paper addressed the problems of controlling the coupled pitch-roll motions in a marine vessel exposed to the regular waves in the longitudinal and transversal directions. Stabilization of the pitch and roll motions can be regarded as the essential task to ensure the safety of a ship's navigation. One of the important features in the pitch-roll motions is the resonance phenomena, which result in unexpected large responses in terms of pitch and roll modes in some specific conditions. Besides, owing to its inherent characteristics of coupled combination and nonlinearity of restoring terms, the vessel shows various dynamical behaviors according to the system parameters, especially in the pitch responses. Above all, it can be seen that suppression of pitch rate remains the most significant challenge to overcome for ship maneuvering safety studies. To secure the stable upright condition, a quasi-sliding mode control scheme is employed to reduce the undesirable pitch and roll responses as well as chattering elimination. The Lyapunov theory is adopted to guarantee the closed stability of the pitch-roll system. Numerical simulations demonstrate the effectiveness of the control scheme. Finally, the control goals of state convergences and chattering reduction are effectively realized through the proposed control synthesis.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.3
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• pp.92-102
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• 2022

Various numerical analysis models can be used to evaluate the behavior characteristics of tunnel facilities which are representative underground structures. In general, the Mohr-Coulomb model, which is most often used for numerical analysis, is an elastic-perfect plastic behavior model. And the deformation characteristics are the same during the load increase-load reduction phase. So there is a problem that the displacement may appear different from the field situation in the case of excavation analysis. In contrast, the HS-small strain stability model has a wide range of applications for each ground. And it is known that soil deformation characteristics can be analyzed according to field conditions by enabling input of initial elastic modulus and nonlinear curve parameter and so on. However, civil engineers are having difficulty using nonlinear models that can apply material nonlinear properties due to difficulties in estimating ground property coefficients. In this study, the necessity of rational model selection was reviewed by comparing the results of seismic performance evaluation using the Mohr-Coulomb model, which civil engineers generally apply for numerical analysis of tunnels, and the HS Small strain Stiffness model, which can consider ground nonlinearity.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.77-89
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• 2022

It has been proven through many previous researches that the pretrained language model with a large corpus helps improve performance in various natural language processing tasks. However, there is a limit to building a large-capacity corpus for training in a language environment where resources are scarce. Using the Cross-lingual Post-Training (XPT) method, we analyze the method's efficiency in Korean, which is a low resource language. XPT selectively reuses the English pretrained language model parameters, which is a high resource and uses an adaptation layer to learn the relationship between the two languages. This confirmed that only a small amount of the target language dataset in the relationship extraction shows better performance than the target pretrained language model. In addition, we analyze the characteristics of each model on the Korean language model and the Korean multilingual model disclosed by domestic and foreign researchers and companies.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.33-41
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• 2023

As carbon-free has been getting interest, renewable energy sources have been increasing. However, renewable energy is intermittent and variable so it is difficult to predict the produced electrical energy from a renewable energy source. In this study, digital-twin concept is applied to solve difficulties in predicting electrical energy from a renewable energy source. Considering that rotation of wind turbine has high correlation with produced electrical energy, a model which simulates rotation in the drivetrain of a wind turbine is developed. The base of a drivetrain simulation model is set with well-known state equation in mechanical engineering, which simulates the rotating system. Simulation based machine learning is conducted to get unknown parameters which are not provided by manufacturer. The simulation is repeated and parameters in simulation model are corrected after each simulation by optimization algorithm. The trained simulation model is validated with 27 real wind turbine operation data set. The simulation model shows 4.41% error in average compared to real wind turbine operation data set. Finally, it is assessed that the drivetrain simulation model represents the real wind turbine drivetrain system well. It is expected that wind-energy-prediction accuracy would be improved as wind turbine digital twin including the developed drivetrain simulation model is applied.