• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.23-32
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• 1999

Reliability and maintainability allocation in the analysis of the system's design, with the objective of planning and installing the individual components in such a way that the system performance is achieved. This paper has been made to solve an important task in reliability management of manufacturing systems within the general objective being to increase productivity while maintaining costs low. Thus, the purpose of this paper is to provide an analytical approach to determine an optimal reliability and maintainability allocation, trading off among system performance and parts investment costs. Two important considerations will be addressed in this regard : (ⅰ) determine the reliability and maintainability allocation of parts which maximizes a given production index, having fixed the total cost of investments ; and (ⅱ) determine the reliability and maintainability allocation which minimizes the total cost of investments, having fixed a minimum acceptable level of productivity. The procedure proposed in this paper is able to provide to managers and designers useful indications on the reliability and maintainability characteristics of parts in series -parallel systems. And this heuristic model is a decision support tool for contractors who are involved in large scale design projects such as ship and aircraft design. Numerical examples prove that an approximate expression of the average throughput rate is sufficiently accurate to be used in a numerical optimization method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.4 s.304
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• pp.25-34
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• 2005

We had research to conduct interrelationships between sensors using postprocessing analysis with the Fuzzy-Kalman Filtering Auto-Correlation about Real Time Simulator data of the NaroSC LCS in case of a fully blind situation scenario. The conducted interrelations are same harmony with relations in scenario. We had analyzed signals of sensors reverse-using a optimization character of Fuzzy-Kalman Filter. As our research conclusion, We had recognized possibilities of signal processing about the KSLV-1, on-board payloads, general equipments of ground support which apply to multi sensor systems.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.6
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• pp.498-508
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• 2015

In the simulation of photovoltaic (PV) power conditioning systems, PSIM is a widely accepted circuit simulation platform because of its fast speed and C-code support. PSIM provides two kinds of generic PV panel models: functional model and physical model. Whereas the functional model simulates PV in the standard test condition (STC) only, the physical model can emulate changing PV characteristics under varying temperatures and irradiation conditions and is thus more suitable for system simulation. However, the physical model requires complicated parameters from users, and thus it is prone to errors and is difficult to use. In this study, a new PSIM model for PV is presented to solve these problems. The proposed model utilizes manufacturers' datasheet values specified under STC only and excludes user-defined information from input parameters. To achieve good accuracy even in varying environmental conditions, single-diode model parameters are successively tuned to a time-varying virtual datasheet. Comparison with a conventional physical model shows that the proposed model provides more accurate simulation according to error analysis based on the EN50530 standard.

• KIEAE Journal
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• v.10 no.6
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• pp.139-144
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• 2010

The demands are increasing for the efficient heating and cooling system and thermal comfort environment because of changes in climate and environment, and deterioration of buildings and facilities can cause education budget to increase. So the study to apply heating and cooling system to university is urgently needed to improve an optimum energy saving system, educational environment and convenience of maintenance. For this reason, we selected a university campus in Seoul then came to understand the current situation and found some problems. We drew alternatives from comparative analysis of them. It selects representative building and carries out economic analysis to evaluate characteristics of energy consumption and economics on each type of heating and cooling system. As a result we drew the optimum system from those processes as previously stated. We studied 3 available systems, absorption chiller, EHP(Electric Heat Pump) and GHP(Gas Engine Heat Pump). According to LCC analysis suppose that the value of EHP is 1, it came out that the value of absorption chiller is 1.5 and the value of GHP is 2.2. This study, suggesting the optimum heating and cooling system, will support educational and research activities furthermore effect to maximize energy efficiency. Ultimately it is expected that it will contribute to make eco-friendly Green Campus.

• Journal of Communications and Networks
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• v.11 no.4
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• pp.368-374
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• 2009

This paper focuses on a distributed multiple spectrum pricing scheme to maximize system capacity in next generation multiaccess systems, where multimode user equipments (MUEs) can connect simultaneously to multiple base stations (BSs) with multiple radio access technologies (RATs). The multi-price based scheme provides a distributed decision making for an optimal solution where radio resource allocations are determined by each MUE, unlike most centralized mechanisms where BS controls the whole radio resource. By the proposed optimal solution, MUEs can decide their share of spectrum bands and power allocation according to the spectrum price of each RAT, and at the same time the multiaccess system can achieve maximized total throughput. Numerical analysis shows that the proposed scheme achieves the maximal capacity by distributed resource allocation for the multiaccess system.

• Bulletin of the Korean Chemical Society
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• v.30 no.7
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• pp.1573-1578
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• 2009

A computational study of the reactions between Zn-containing species, the products of the thermal decomposition of diethylzinc (DEZn) and water was investigated. The Zn-containing species – $C_2H_5)_2,\;HZnC_2H_5,\;and\;(ZnC_2H_5)_2$ – were assumed to react with water during ZnO metal organic chemical vapor deposition (MOCVD). Density functional theory (DFT) calculations at the level of B3LYP/6-311G(d) were employed for the geometry optimization and thermodynamic property evaluation. As a result dihydroxozinc, $Zn(OH)_2$, was the most probable reaction product common for all three Zn-containing species. A further clustering of $Zn(OH)_2$ was investigated to understand the initial stage of ZnO film deposition. In experiments, the reactions of DEZn and water were examined by in-situ Raman scattering in a specially designed MOCVD reactor. Although direct evidence of $Zn(OH)_2$ was not observed, some relevant reaction intermediates were successfully detected to support the validity of the gas phase reaction pathways proposed in the computational study.

• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2262-2273
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• 2020

Digital twin technology can provide significant value for the prognostics and health management (PHM) of critical plant components by improving insight into system design and operating conditions. Digital twinning of systems can be utilized for anomaly detection, diagnosis and the estimation of the system's remaining useful life in order to optimize operations and maintenance processes in a nuclear plant. In this regard, a conceptual framework for the application of digital twin technology for the prognosis of Control Element Drive Mechanism (CEDM), and a data-driven approach to anomaly detection using coil current profile are presented in this study. Health management of plant components can capitalize on the data and signals that are already recorded as part of the monitored parameters of the plant's instrumentation and control systems. This work is focused on the development of machine learning algorithm and workflow for the analysis of the CEDM using the recorded coil current data. The workflow involves features extraction from the coil-current profile and consequently performing both clustering and classification algorithms. This approach provides an opportunity for health monitoring in support of condition-based predictive maintenance optimization and in the development of the CEDM digital twin model for improved plant safety and availability.

• Steel and Composite Structures
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• v.17 no.2
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• pp.173-184
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• 2014

This study aimed to theoretical calculate the thermal residual stress in continuous SiC fiber reinforced titanium matrix composites. The analytical solution of residual stress field distribution was obtained by using coaxial cylinder model, and the numerical solution was obtained by using finite element model (FEM). Both of the above models were compared and the thermal residual stress was analyzed in the axial, hoop, radial direction. The results indicated that both the two models were feasible to theoretical calculate the thermal residual stress in continuous SiC fiber reinforced titanium matrix composites, because the deviations between the theoretical calculation results and the test results were less than 8%. In the titanium matrix composites, along with the increment of the SiC fiber volume fraction, the longitudinal property was improved, while the equivalent residual stress was not significantly changed, keeping the intensity around 600 MPa. There was a pronounced reduction of the radial residual stress in the titanium matrix composites when there was carbon coating on the surface of the SiC fiber, because carbon coating could effectively reduce the coefficient of thermal expansion mismatch between the fiber and the titanium matrix, meanwhile, the consumption of carbon coating could protect SiC fibers effectively, so as to ensure the high-performance of the composites. The support of design and optimization of composites was provided though theoretical calculation and analysis of residual stress.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8B
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• pp.691-698
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• 2003

Throughput response characteristics depending on the network bandwidth allocation need to be modeled to devise adaptive control mechanism to support QoS of the network. Thus, two models are proposed in this study. The first one is a dynamic system model and the other one is a stochastic model. The dynamic system model is developed to represent dynamic characteristics of the network and the stochastic model is developed to represent distribution of measured throughput data. An optimization technique is used for decision of proposed model's factor. The result confirms that the characteristics of proposed models are similar with actual network's characteristics.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.621-652
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• 2012

Software Estimations provide an inclusive set of directives for software project developers, project managers, and the management in order to produce more realistic estimates based on deficient, uncertain, and noisy data. A range of estimation models are being explored in the industry, as well as in academia, for research purposes but choosing the best model is quite intricate. Estimation by Analogy (EbA) is a form of case based reasoning, which uses fuzzy logic, grey system theory or machine-learning techniques, etc. for optimization. This research compares the estimation accuracy of some conventional data mining models with a hybrid model. Different data mining models are under consideration, including linear regression models like the ordinary least square and ridge regression, and nonlinear models like neural networks, support vector machines, and multivariate adaptive regression splines, etc. A precise and comprehensible predictive model based on the integration of GRA and regression has been introduced and compared. Empirical results have shown that regression when used with GRA gives outstanding results; indicating that the methodology has great potential and can be used as a candidate approach for software effort estimation.