• Current Photovoltaic Research
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• v.8 no.2
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• pp.54-59
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• 2020

Within the IEA (International Energy Agency) PVPS (Photovoltaic Power System) Programme Task 15, 'Enabling Framework for the Acceleration of BIPV,' a round-robin action focusing on the performance of vertical BIPV elements as a facade in different climatic environments was performed. The performance of identical (both, in construction and bill of materials (BOM)) glass-to-glass c-Si BIPV elements was monitored at seven outdoor test sites in 6 different countries in Europe and Asia. In this work, the comprehensive results of the electrical and corresponding meteorological data will be presented and discussed. The monitored data were merged, processed, and filtered for further analysis. The analysis includes the chracteristics of the module temperatures and the in-plane irradiation at the outdoor test locations, mean daily PR per test module, time series of mean daily performance ratio coefficients, and monthly yield.

• Nuclear Engineering and Technology
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• v.48 no.5
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• pp.1120-1125
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• 2016

The neutron decay constant, ${\alpha}$, and effective delayed neutron fraction, ${\beta}_{eff}$, are important parameters for the control of the dynamic behavior of nuclear reactors. For the heavy water zero power reactor (HWZPR), this document describes the measurements of the neutron decay constant by noise analysis methods, including variance to mean (VTM) ratio and endogenous pulse source (EPS) methods. The measured ${\alpha}$ is successively used to determine the experimental value of the effective delayed neutron fraction as well. According to the experimental results, ${\beta}_{eff}$ of the HWZPR reactor under study is equal to 7.84e-3. This value is finally used to validate the calculation of the effective delayed neutron fraction by the Monte Carlo methods that are discussed in the document. Using the Monte Carlo N-Particle (MCNP)-4C code, a ${\beta}_{eff}$ value of 7.58e-3 was obtained for the reactor under study. Thus, the relative difference between the ${\beta}_{eff}$ values determined experimentally and by Monte Carlo methods was estimated to be < 4%.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.12
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• pp.2368-2375
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• 1992

The transition of turbulent kinetic energy(TKE) balance along the centerline of the flow unit, which is composed of straight-duct, contraction and free-jet, has been investigated by the hot-wire anemometry. It is found that the mean turbulent kinetic energy is balanced by the dissipation in the internal flow region ; by the production and the dissipation, through contraction ; and by the dissipation, in initial region(X〈8D) of free-jet. But in the developing region (8D〈X〈20D) it is balanced by all of the three(ie, diffusion, production and dissipation). Finally, in the downstream of free-jet, the mean TKE is balanced again by dissipation like as the beginning. The decay-laws along the centerline are checked in the region of free jet as well as in the straightduct. After the developing region of free-jet also exist the decay-laws, the exponent of the axial turbulence being bigger than of the radial.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.05a
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• pp.281-284
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• 2004

Mean energy of electrons in $SF_6-Ar$ Mixtures Gas used by MCS-BEq algorithm has been analysed over the E/N range $30{\sim}300[Td]$ by a two term Boltzmann equation and by a Monte Carlo Simulation using a set of electron cross sections determined by other authors, experimentally the electron swarm parameters for 0.2[%] and 0.5[%] $SF_6-Ar$, 0.1[%] and 5.0[%], $SF_6-Ar$ mixtures were measured by time-of-flight(TOF) method. The transport Coefficients for electrons in (100[%])$SF_6$. (100[%])Ar, (0.2[%])$SF_6-Ar$ and (0.5[%]) $SF_6-Ar$, (5.0[%]) $SF_6-Ar$, (0.1[%])$SF_6-Ar$ mixtures were measured by time-of-flight method, and the electron energy distribution function and the parameters of the velocity and the diffusion were determined by the variation of the collision cross-sections with energy. The results obtained from Boltzmann equation method and Monte Carlo simulation have been compared with present and previously obtained data and respective set of electron collision cross sections of the molecules.

• The Korean Journal of Food And Nutrition
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• v.17 no.4
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• pp.356-367
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• 2004

This study was performed to evaluate the effectiveness of a nutritional education program conducted by public health center in Jinju city for obese women. The subjects of this study consisted of 27 obese women(BMI $\geq$ 25) aged 35∼55 years in Jinju area, and the educational period was 6 weeks. We evaluated the anthropometric parameters and biochemical indices, dietary habits, dietary behaviors, nutritional attitude of obese women before and after the nutritional education. And also daily intake during the educational period were measured. Weight, obesity index, BMT, waist circumferences and hip circumferences of obese women were significantly decreased(p<0.001) after nutritional education, but changes of WHR, systolic blood pressure and diastolic blood pressure were not significant. There were no significant difference in total cholesterol, HDL-cholesterol, LDL-cholesterol, triglyceride, LDH and blood glucose level in serum before and after the nutritional education, but the indices tend to decrease after the nutritional education. There was significantly different change of dietary behaviors in 3 items among the dietary behavior after the nutritional education. Their dietary habit, dietary behavior and nutritional attitude scores were significantly improved after the nutritional education. Mean daily energy intakes was low compared with the RDA as 78.88%. The average carbohydrates, protein, fat ratio on the energy intakes was 63 : 17 : 20. The proportion of energy intake from snacks the was 12.91${\pm}$6.15%.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2844-2853
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• 2023

A sophisticated Bayesian multilevel model for estimating group bias was developed to improve the utility of the ASTM E900-15 embrittlement trend curve (ETC) to assess the conditions of nuclear power plants (NPPs). For multilevel model development, the Baseline 22 surveillance dataset was basically classified into groups based on the NPP name, product form, and notch orientation. By including the notch direction in the grouping criteria, the developed model could account for TTS differences among NPP groups with different notch orientations, which have not been considered in previous ETCs. The parameters of the multilevel model and biases of the NPP groups were calculated using the Markov Chain Monte Carlo method. As the number of data points within a group increased, the group bias approached the mean residual, resulting in reduced credible intervals of the mean, and vice versa. Even when the number of surveillance test data points was less than three, the multilevel model could estimate appropriate biases without overfitting. The model also allowed for a quantitative estimate of the changes in the bias and prediction interval that occurred as a result of adding more surveillance test data. The biases estimated through the multilevel model significantly improved the performance of E900-15.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.1
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• pp.1-12
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• 1992

Generally, laser machines with high generated power can be developed by means of enhancing their mean power, since the enhancement of mean power exerts an influence on peripheral parameters and machining performance. In this research, we evaluate the various machining properties by the use of two machines which bear different mean power each other, so that we may study various effects of the enhancement of mean power. As a result, when the mean power comes to be enhanced to 75%, we obtain the increase of output energy up to 69% and of peak power more than 95%, and also obtain almost twice of the cutting speed. Moreover we find the fact that if the test pieces have enough thickness in contrast with output energy, the pulse frequency moves toward the frequency bandwidth which takes proportion to the cutting speed mas well as to the amount of material removal per unit time. In addition it is finally obtained that the laser machine with high output power yields small taper degrees at kerf parts, while it has large cutting widiths and dross lengths.

• Nutritional Sciences
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• v.2 no.2
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• pp.88-92
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• 1999

The purpose of this study was to study the intake of heavy metals such af arsenic, lead and cobalt and the relationship of dietary heavy metals with serum iron, topper, and zinc, which play important roles in hematopoiesis, in healthy college women living in Choongnam Korea, where we have detected heavy metals (As, Pb, Co) in some marine products in previous studies. The nutritional status of the subjects (35 women) was evaluated by anthropometric measurements, 24-hr dietary recall for 3 days. And 3-day diets (by weighing method) and blood were collected to analyze As, Pb, Co, Fe, Cu, Zn, Hb, Hct, and MCHC. The mean age, height, weight, and BMI were 20 years, 158 cm, 55 kg and 22.42 kg/$m^2$, respectively. The mean daily energy intake was 85.85% of RDA for Koreans. The ratio of energy from carbohydrate, protein, and fat was 60 : 24 : 16. The mean daily intake of heavy metals (As, Pb, Co) was 1.77 mg/day, 75.21 $\mu$g/day and 21.12 $\mu$g/day. And the mean daily intake of iron, copper, and Zinc concentrations were 97, 68, and 92% of normal values. The mean serum heavy metals (As, Pb, Co) were 16.14 $\mu$g/dl, 4.32 $\mu\textrm{g}$/dl and 0.02 $\mu$g/dr, respectively Mean blood levels of Fe, Cu, Zn, Hb, Hct, and MCHC were at normal levels. Dietary heavy metals except Co were not significantly different from serum Fe, Cu, Zn and Hb, Hct, and MCHC. However, there was a tendency toward lower serum concentration of Fe, Hb, Hct, and MCHC in the subjects with higher heavy metals (As) intake. Among heavy metals, only dietary Co showed a significant negative correlation with Hb (p< 0.001) and Hct (p < 0.001).

• Tunnel and Underground Space
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• v.31 no.6
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• pp.508-519
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• 2021

In this study, a model was developed to predict the peak particle velocity (PPV) that affects people and the surrounding environment during blasting. Four machine learning models using the k-nearest neighbors (kNN), classification and regression tree (CART), support vector regression (SVR), and particle swarm optimization (PSO)-SVR algorithms were developed and compared with each other to predict the PPV. Mt. Yogmang located in Changwon-si, Gyeongsangnam-do was selected as a study area, and 1048 blasting data were acquired to train the machine learning models. The blasting data consisted of hole length, burden, spacing, maximum charge per delay, powder factor, number of holes, ratio of emulsion, monitoring distance and PPV. To evaluate the performance of the trained models, the mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE) were used. The PSO-SVR model showed superior performance with MAE, MSE and RMSE of 0.0348, 0.0021 and 0.0458, respectively. Finally, a method was proposed to predict the degree of influence on the surrounding environment using the developed machine learning models.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.136.2-136.2
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• 2011

In this work, we analyzed correlations between life-cycle greenhouse gas (GHG) emissions and life-cycle cost of energy resources. Energy resources studied in this paper include coal, natural gas, nuclear power, hydropower, geothermal energy, wind power, solar thermal energy, and solar photovoltaic energy, and all of them are used to generate electricity. We calculated the mean values, ranges of maximum minus minimum values, and ranges of 90% confidence interval of life-cycle GHG emissions and life-cycle cost of each energy resource. Based on the values, we plotted them in two dimensional graphs to analyze a relationship and characteristics between GHG emissions and cost. Besides, to analyze the technical maturity, the GHG emissions and the range of minimum and maximum values were compared to each other. For the electric generation, energy resources are largely inverse proportional to the GHG emission and the corresponding cost.