• Journal of Korea Society of Industrial Information Systems
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• v.5 no.3
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• pp.87-93
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• 2000

Recently Software Industry has tended to enhance the productivity and quality with using the software architecture in software development and administration. The research of software component technique and software development methodology are just doing and making many applications. The software architecture is considered as the essential element for analyzing and maintaining the entire structure with organizing the software into components and describing the relations with connectors. The software modeling methodology that we propose is generating Happy Work Language describing the software structure with the modeling tool as Happy Work. We can use System Context Diagram, Component Diagram, Component Sequence Diagram, and they are composed of four Elements as Users, Systems, Components, Connectors.

• Journal of Magnetics
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• v.12 no.1
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• pp.7-11
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• 2007

We confirm the validity of the analytic expression for the temperature of the Joule heated nano-wire [C.-Y. You et al. Appl. Phys. Lett. 89, 222513 (2006)] with finite element method. The temperature of the Joule heated nano-wire is essential information for the research of the current induced domain wall movement. The analytic expression includes an adjustable parameter which must be determined. Since the physical origin of the adjustable parameter is simplification of the heat source profile, the validity of the analytic expression must be examined for wide range of the nano-wire structure. By comparison with this analytic expression with the results of full numerical finite element method, the adjustable parameter has been determined. The numerically confirmed adjustable parameter values are in the range of 0.60$\sim$0.69, which is well matched with the theoretically expected one. Furthermore, it is found that the adjustable parameter is a slow varying function of the nano-wire geometry. Based on this numerical confirmation, we can apply the analytic expression for the wide range of the nano-wire geometry with proper adjustable parameters.

• Journal of the Optical Society of Korea
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• v.19 no.3
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• pp.272-276
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• 2015

The PbS quantum dot is an emerging photovoltaic material, which may provide high efficiency breakthroughs. The most crucial element for the high efficiency solar cells's development is to understand charge transport characteristics of PbS quantum dot solids, which are also important in planning strategic research. We have investigated charge transport characteristics of PbS quantum dot solids thin films using space charge limited conduction analysis and assessed thickness dependent photovoltaic performances. The extracted carrier drift mobility was $low-10^{-2}cm^2/Vs$ with the estimated diffusion length about 50 nm. These and recently reported values were compared with those from a commercial photovoltaic material, and we present an essential element in further development of PbS quantum dot solids materials.

• Molecules and Cells
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• v.44 no.7
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• pp.493-499
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• 2021

Parkinson's disease (PD) is characterized by a progressive loss of dopamine-producing neurons in the midbrain, which results in decreased dopamine levels accompanied by movement symptoms. Oral administration of l-3,4-dihydroxyphenylalanine (L-dopa), the precursor of dopamine, provides initial symptomatic relief, but abnormal involuntary movements develop later. A deeper understanding of the regulatory mechanisms underlying dopamine homeostasis is thus critically needed for the development of a successful treatment. Here, we show that p21-activated kinase 4 (PAK4) controls dopamine levels. Constitutively active PAK4 (caPAK4) stimulated transcription of tyrosine hydroxylase (TH) via the cAMP response element-binding protein (CREB) transcription factor. Moreover, caPAK4 increased the catalytic activity of TH through its phosphorylation of S⁴⁰, which is essential for TH activation. Consistent with this result, in human midbrain tissues, we observed a strong correlation between phosphorylated PAK4^S474, which represents PAK4 activity, and phosphorylated TH^S40, which reflects their enzymatic activity. Our findings suggest that targeting the PAK4 signaling pathways to restore dopamine levels may provide a new therapeutic approach in PD.

• Journal of Digital Convergence
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• v.17 no.6
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• pp.381-388
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• 2019

The purpose of this study is to first define self-confidence (self-efficacy) and evaluate importance of creativity of designers, then investigate correlation between the two values. While creativity is a crucial element of design process, for novelty is an essential element of a great design, many believe that self-confidence is one of the major sources of creativity. An experiment consisted of questionnaires and creativity tests have suggested that there is no clear relationship between the two values. Nonetheless, the two values are still driving forces of one's motivation, which could ultimately lead to a designer's success.

• Transactions of Materials Processing
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• v.27 no.6
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• pp.331-338
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• 2018

Electrohydraulic forming (EHF) process is a high speed forming process that utilizes the electric energy discharge in fluid-filled chamber to deform a sheet material. This process is completed in a very short time of less than 1ms. Therefore, finite element analysis is essential to observe the deformation mechanism of the material in detail. In addition, to perform the numerical simulation of EHF, the material properties obtained from the high-speed status, not quasi static conditions, should be applied. In this study, to obtain the parameters in the constitutive equation of Al 6061-T6 at high strain rate condition, a surrogate model using an artificial neural network (ANN) technique was employed. Using the results of the numerical simulation with free-bulging die in LS-DYNA, the surrogate model was constructed by ANN technique. By comparing the z-displacement with respect to the x-axis position in the experiment with the z-displacement in the ANN model, the parameters for the smallest error are obtained. Finally, the acquired parameters were validated by comparing the results of the finite element analysis, the ANN model and the experiment.

• Nuclear Engineering and Technology
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• v.51 no.6
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• pp.1658-1668
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• 2019

Nuclear power generates a large portion of the energy used today and plays an important role in energy development. To ensure safe nuclear power generation, it is essential to conduct an accurate analysis of reactor structural integrity. Accordingly, in this study, a methodology for obtaining accurate structural responses to the combined seismic and reactor coolant loads existing prior to the shutdown of a nuclear reactor is proposed. By applying the proposed analysis method to the reactor vessel internals, it is possible to derive the seismic responses considering the influence of the hydraulic loads present during operation for the first time. The validity of the proposed methodology is confirmed in this research by using the finite element method to conduct seismic and hydraulic load analyses of the advanced APR1400 1400 MWe power reactor, one of the commercial reactors. The structural responses to the combined applied loads are obtained using displacement-based and stress-based superposition methods. The safety of the subject nuclear reactor is then confirmed by analyzing the design margin according to the American Society for Mechanical Engineers (ASME) evaluation criteria, demonstrating the promise of the proposed analysis method.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1199-1209
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• 2021

The detection of unexpected loose parts in the primary coolant system in a nuclear power plant remains an extremely important issue. It is essential to develop a methodology for the localization and mass estimation of loose parts owing to the high prediction error of conventional methods. An effective approach is presented for the localization and mass estimation of a loose part using machine-learning and deep-learning algorithms. First, a methodology was developed to estimate both the impact location and the mass of a loose part at the same times in a real structure in which geometric changes exist. Second, an impact database was constructed through a series of impact finite-element analyses (FEAs). Then, impact parameter prediction modes were generated for localization and mass estimation of a simulated metallic loose part using machine-learning algorithms (artificial neural network, Gaussian process, and support vector machine) and a deep-learning algorithm (convolutional neural network). The usefulness of the methodology was validated through blind tests, and the noise effect of the training data was also investigated. The high performance obtained in this study shows that the proposed methodology using an FEA-based database and deep learning is useful for localization and mass estimation of loose parts on site.

• Design & Manufacturing
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• v.15 no.2
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• pp.63-69
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• 2021

Springback is an essential task to be solved in order to make high-precision products in sheet metal forming. In this study, materials with four different elastic regions were used. For the forming analysis, the change of springback caused by the frictional force generated in the flange part during hat shape forming was considered by using the AutoForm analysis program. Factors affecting frictional force were blank holder force, friction coefficient, bead R and bead height. As a result of the forming analysis, the springback increases as the material with a larger elastic region increases. In addition, as the frictional force of the flange part increased, the tensile force in the forming direction increased and the springback decreased. In particular, the blank holder force and friction coefficient had a great effect on springback in mild materials (DC04, Al6016), and the bead effectively affects all materials. Through this study, it was considered that the springback decreased as the material with a smaller elastic region and the tensile force in the forming direction increased.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.11
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• pp.100-107
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• 2021

The use of new and renewable energy is essential to solve the problem of increasing fossil fuel use due to industrial development. The paradigm of the automobile industry has changed due to the strengthening of environmental regulations in developed countries, and the development of eco-friendly cars is underway. Fuel cell electric vehicles (FCEVs), which use hydrogen as fuel, require strict standards for fuel-related components. In particular, check valves for FCEV control high-pressure hydrogen and thus, must be sufficiently strong for the challenging environment caused by high-pressure hydrogen. Therefore, this study used DEFORM 3D, a regular finite element analysis program, to check the moldability of check valves for FCEV, design the process, verify reliability through single streamline analysis, tensile tests, and ANSYS simulations, and identify suitable materials for the high-pressure hydrogen environment.