• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.1079-1084
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• 2002

Systems engineering technology development program for Korea next-generation high-speed railway(KNHR) system in progress is a national large-scale system development program that is not only a large-size and complex but also multi-disciplinary in nature. Using the RDD-IOO, a systems engineering tool, the KNHR program can establish requirements traceability and development process management in the course of development. This paper presents the results from a computer-aided systems engineering application to KNHR system technology development project over the three years of activities. The traceability among the system design database in the vertical direction of SE process, as the results of the first year and the second year research was accomplished. The database in both the requirement management domain and the project management domain was developed and set up the traceability between them in the horizontal direction of the SE process in the V model as the results of the third year research. Therefore, KNHR design database was built to support the life-cycle management of the system as well as to reuse the knowledge in future programs. In the following development phase, this database will be utilized to accomplish the test and integration activities providing a baseline database. The outcome of the study contributes to the establishment of the model-based systems engineering approach as a best practice in the accumulation and advancement of systems engineering technology for railway system development.

• Journal of the Society of Naval Architects of Korea
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• v.36 no.4
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• pp.64-76
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• 1999

In this paper hydroelastic experimental techniques of very large floating offshore structures are suggested based on the model test carried out in the UOU Ocean Engineering Wide Tank. The prototype is a box-shaped floating structure with length of 300m, breadth of 60m, depth of 2m and draft of 0.5m and longitudinal bending rigidity as $4.87{\times}10^{10}kgm^2$. The scale ratio is 1/42.857. The model is realized by aluminum square pipes with the section dimension of $20mm{\times}20mm$. The numbers of longitudinal and transverse pipes are 7 and 35 respectively. Heave motions at selected points are measured with potentiometers and bending moments with strain gages.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.4
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• pp.323-330
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• 2012

This study deals with the experiments of liquid dampers with multi cells whose vertical tubes are divided into several square columns for easily changing natural frequencies. Shaking table test is performed to verify control effectiveness of the dampers which are installed on a building structure. To design liquid dampers, a 64-story building structure is reduced to a SDOF structure with 1/20 of similitude laws based on acceleration. The structure model is made up to adjust its mass and stiffness easily, with separate mass and drive parts. Mass parts indicate real structure's weights and drive parts indicate real structure's stiffness with springs and LM guides. Manufactured liquid damper has 18 cells and its natural frequency ranges are 0.65Hz to 0.81Hz. Shaking table test is carried out with one way excitation to compare with only accelerations of a large-scale structure and a structure installed with liquid dampers. Control performance of the liquid damper is expressed by the transfer function from shaking table accelerations to the large-scale structure ones. Testing results show that the liquid damper reduced a large-scale structure's response by tuned natural frequencies.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.214-222
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• 2022

Convolutional Neural networks (CNNs) are a category of deep learning networks that have proven very effective in computer vision tasks such as image classification. Notwithstanding, not much has been seen in its use for remote sensing image classification in developing countries. This is majorly due to the scarcity of training data. Recently, transfer learning technique has successfully been used to develop state-of-the art models for remote sensing (RS) image classification tasks using training and testing data from well-known RS data repositories. However, the ability of such model to classify RS test data from a different dataset has not been sufficiently investigated. In this paper, we propose a deep CNN model that can classify RS test data from a dataset different from the training dataset. To achieve our objective, we first, re-trained a ResNet-50 model using EuroSAT, a large-scale RS dataset to develop a base model then we integrated Augmentation and Ensemble learning to improve its generalization ability. We further experimented on the ability of this model to classify a novel dataset (Nig_Images). The final classification results shows that our model achieves a 96% and 80% accuracy on EuroSAT and Nig_Images test data respectively. Adequate knowledge and usage of this framework is expected to encourage research and the usage of deep CNNs for land cover mapping in cases of lack of training data as obtainable in developing countries.

• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3361-3379
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• 2022

A nuclear power plant (NPP) piping is designed against low-frequency earthquakes. However, earthquakes that can occur at NPP sites in the eastern part of the United States, northern Europe, and Korea are high-frequency earthquakes. Therefore, this study conducts bi-directional shaking table tests on actual-scale NPP piping and studies the response characteristics of low- and high-frequency earthquake motions. Such response characteristics are analyzed by comparing several responses that occur in the piping. Also, based on the test results, a piping numerical analysis model is developed and validated. The piping seismic performance under high-frequency earthquakes is derived. Consequently, the high-frequency excitation caused a large amplification in the measured peak acceleration responses compared to the low-frequency excitation. Conversely, concerning relative displacements, strains, and normal stresses, low-frequency excitation responses were larger than high-frequency excitation responses. Main peak relative displacements and peak normal stresses were 60%-69% and 24%-49% smaller in the high-frequency earthquake response than the low-frequency earthquake response. This phenomenon was noticeable when the earthquake motion intensity was large. The piping numerical model simulated the main natural frequencies and relative displacement responses well. Finally, for the stress limit state, the seismic performance for high-frequency earthquakes was about 2.7 times greater than for low-frequency earthquakes.

• International Journal of Control, Automation, and Systems
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• v.2 no.2
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• pp.256-262
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• 2004

Conventionally, profile non-uniformity has been characterized by relying on approximated profile with angle or anisotropy. In this study, a new non-uniformity model for etch profile is presented by applying a discrete wavelet to the image obtained from a scanning electron microscopy (SEM). Prediction models for wavelet-transformed data are then constructed using a back-propagation neural network. The proposed method was applied to the data collected from the etching of tungsten material. Additionally, 7 experiments were conducted to obtain test data. Model performance was evaluated in terms of the average prediction accuracy (APA) and the best prediction accuracy (BPA). To take into account randomness in initial weights, two hundred models were generated for a given set of training factors. Behaviors of the APA and BPA were investigated as a function of training factors, including training tolerance, hidden neuron, initial weight distribution, and two slopes for bipolar sig-moid and linear function. For all variations in training factors, the APA was not consistent with the BPA. The prediction accuracy was optimized using three approaches, the best model based approach, the average model based approach and the combined model based approach. Despite the largest APA of the first approach, its BPA was smallest compared to the other two approaches.

• Nuclear Engineering and Technology
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• v.51 no.2
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• pp.600-606
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• 2019

Studies on the application of the lead rubber bearing (LRB) isolation system to nuclear power plants are being carried out as one of the measures to improve seismic performance. Nuclear power plants with isolation systems require seismic probabilistic safety assessments, for which the seismic fragility of the structures, systems, and components needs be calculated, including for beyond design basis earthquakes. To this end, seismic response analyses are required, where it can be seen that the behaviors of the isolation system components govern the overall seismic response of an isolated plant. The numerical model of the LRB used in these seismic response analyses plays an important role, but in most cases, the extreme performance of the LRB has not been well studied. The current work therefore develops an extreme nonlinear numerical model that can express the seismic response of the LRB for beyond design basis earthquakes. A full-scale LRB was fabricated and dynamically tested with various input conditions, and test results confirmed that the developed numerical model better represents the behavior of the LRB over previous models. Subsequent seismic response analyses of isolated nuclear power plants using the model developed here are expected to provide more accurate results for seismic probabilistic safety assessments.

• Journal of Ocean Engineering and Technology
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• v.20 no.6 s.73
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• pp.88-92
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• 2006

Large-scale model tests of welded topside joints were carried out to observe the fatigue behavior of API 2W Gr.50 steel produced by POSCO. The fatigue crack behaviors for various loading conditions were measured and investigated around the critical joint sections. The experimental results have been verified with numerical approaches and also compared with the AWS D1.1 and DnV RP-C203 design curves. The large-scale experiment models were fabricated, based on the actual operating east area fixed platform. The dimensions of the models were slightly modified to accommodate the test facilities and capacities. The fatigue test was carried out having ${\Delta}Q$ of T1=705.6kN, T2=749.7kN and T3=793.8kN. The three specimens were statically loaded 20 times, with various loadings of about 50kN intervalsbetween the maximum and minimum loads required in the fatigue tests. This loading removed the residual stress in the specimen before the fatigue tests. The topside joint crack was initiated from the brace heel, where the maximum tensile stress occurred. The API 2W Gr.50 steel satisfied the AWS D1.1 detail category C and DnV RP-C203 detail category F ${\Delta}S-N$ curve.

• Journal of the Korean GEO-environmental Society
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• v.9 no.5
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• pp.53-59
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• 2008

The purpose of the study was to evaluate how much gastropod shell effected its properties better than crushed stone as coarse grained materials by comparing friction properties of a contact surface between coarse grained materials and geosynthetics with the large-scale direct shear test. To achieve the purpose, the study compared and analyzed friction coefficient and friction angle by making crushed stone or gastropod shell into model ground and by installing and shearing non-woven fabric or geostrip geosynthetics. As the results of the analysis, crushed stone had the internal friction angle of $33.8^{\circ}$ when its unit weight was $13.7kN/m^3$ and gastropod shell had the internal friction angle of $35.4^{\circ}$ when its unit weight was $5.4kN/m^3$. Also, the friction angle of a contact surface between geosynthetics and crushed stone was larger than the friction angle of a contact surface between geosynthetics and gastropod shell.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.2
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• pp.135-145
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• 2023

Developing high-fidelity Computational Fluid Dynamics (CFD) simulation methods used to evaluate the airwake characteristics along a flight deck of a large ship, the various kind of data such as actual ship measurement and wind tunnel results are required to verify the accuracy of CFD simulation. Inflow velocity profile at the bow, local unsteady flow field data around the flight deck, and highly reliable wind tunnel data which were measured after reviewing Atmospheric Boundary Layer (ABL) simulation and Reynolds Number effects were also used to determine the key parameters such as turbulence model, time resolution and accuracy, grid resolution and type, inflow condition, domain size, simulation length, and so on in STAR CCM⁺. Velocity ratio and turbulent intensity difference between Full-scale CFD and actual ship measurement at the measurement points show less than 2% and 1.7% respectively. And differences in velocity ratio and turbulence intensity between wind tunnel test and small-scale CFD are both less than 2.2%. Based upon this fact, the selected parameters in CFD simulation are highly reliable for a specific wind condition.