• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.5-7
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• 2006

In this paper, we analyzed the elements of measurement uncertainty on electrical performance test which are the most important things in photovoltaic module performance test. Repeating the performance test by 6 men, the measurement uncertainty could be calculated. In this experiment, Solar Simulator (A-Class pulse type) used for domestic certificate test of PV module is Pasan IIIb (Balval, Switzerland). The possible elements of the measurement uncertain that could effect electrical performance test of PV module are reference cell, spectrum correction, error from measurement repetition, test condition, stability and uniformity of artificial solar simulator. To find the measurement uncertainty, 6 men repeated the test by 10 times. And the results were that numerical average value was 124.44W and measurement uncertainty was $124.44W{\pm}0.75W$ with 95% confidence level for 125W PV module.

• Journal of Power Electronics
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• v.13 no.5
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• pp.814-828
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• 2013

The LCL resonant inductive power transfer (IPT) system is increasingly used because of its harmonic filtering capabilities, high efficiency at light load, and unity power factor feature. However, the modeling and controller design of this system become extremely difficult because of parameter uncertainty, high-order property, and switching nonlinear property. This paper proposes a frequency and load uncertainty modeling method for the LCL resonant IPT system. By using the linear fractional transformation method, we detach the uncertain part from the system model. A robust control structure with weighting functions is introduced, and a control method using structured singular values is used to enhance the system performance of perturbation rejection and reference tracking. Analysis of the controller performance is provided. The simulation and experimental results verify the robust control method and analysis results. The control method not only guarantees system stability but also improves performance under perturbation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.2
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• pp.81-86
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• 2005

In this paper we consider an optimal configuration problem for redundant inertial sensors which have uncertainty such as misalignment, scale factor error. The optimal configuration problem is treated from the viewpoint of navigation accuracy. We propose a necessary and sufficient condition for the optimal configuration of redundant sensors with no uncertainty, and a sufficient condition for the optimal configuration of redundant sensors with uncertainty. Finally we propose a condition for the optimal configuration based both navigation performance and FDI(fault detection and isolation).

• Journal of the Korea Safety Management & Science
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• v.13 no.2
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• pp.267-273
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• 2011

Since 'The Act on Private Investment of The Infrastructure' was established in 1994, private investment as well as government's investment in transport infrastructure has been active. However investment in transport infrastructure has more risks than others' due to uncertainty both in traffic volume and in construction cost. In the current appraisal procedure of deciding transportation infrastructure investment, instead of risk management, the sensitivity analysis considering only the changes of benefit, cost and social discount rate which are main factor affecting economic feasibility is carried out. Therefore the uncertainty of various factors affecting demand, cost and benefit are not considered in feasibility study. In this study the problems in current investment appraisal system were reviewed. Using Delphi technique the major factors which have high uncertainty in feasibility study were surveyed and then improvement plan was suggested in the respective of classic 4 step demand forecasting method. The range estimation technique was also mentioned to deal with the uncertainty of the future.

• Journal of the Korean Physical Society
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• v.73 no.9
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• pp.1247-1254
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• 2018

We study the uncertainty stemming from different theoretical models in the spectroscopic factors extracted from experiments. We use three theoretical approaches, the distorted wave Born approximation (DWBA), the adiabatic distorted wave approximation (ADWA) and the continuum discretized coupled-channels method (CDCC), and analyze the $^{12}C(d,p)^{13}C$, $^{14}C(d,p)^{15}C$ reactions. We find that the uncertainty associated with the adopted theoretical models is less than 20%. We also investigate the contribution from the remnant term and observe that it gives less than 10% uncertainty. We finally make an attempt to explain the discrepancy in the spectroscopic factors of $^{17}C(\frac{3}{2}^+)$ between the ones extracted from experiments and from shell model calculations by analyzing the $^{16}C(d,p)^{17}C$ reaction.

• 유체기계공업학회:학술대회논문집
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• 2005.12a
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• pp.287-294
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• 2005

Flow rate measurement uncertainties of the ultrasonic flow meter are generally influenced by many different factors, such as Reynolds number, flow distortion, turbulence intensity, wall surface roughness, velocity integration method along the acoustic paths, and transducer installation method, etc. Of these influencing factors, one of the most important uncertainties comes from the velocity integration method. In the present study, a optimization weighting factor method for 5-chord, which is given by a function of the chord locations of acoustic paths, is employed to obtain the mean velocity in the flow through a pipe. The power law profile is assumed to model the axi-symmetric pipe flow and its results are compared with the present weighting factor concept. For an asymmetric pipe flow, the Salami flow model is applied to obtain the velocity profiles. These theoretical methods are also compared with the previous Gaussian, Chebyshev, and Tailor methods. The results obtained show that for the fully developed turbulent pipe flows with surface roughness effects, the present weighting factor method is much less sensitive than Chebyshev and Tailor methods, leading to a better reliability in flow rate measurement using the ultrasonic flow meters.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2019.05a
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• pp.157-158
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• 2019

• Korean Journal of Environmental Agriculture
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• v.39 no.3
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• pp.228-236
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• 2020

BACKGROUND: The closed chamber method is the most commonly used for measuring greenhouse gas emissions from rice fields. This method has the advantages of being simple, easily available and economical. However, a measurement result using the chamber method is an estimated value and is complete when the uncertainty is estimated. The methane emissions from a rice paddy account for the largest portion of the greenhouse gas emissions in the agriculture sectors. Although assessment of uncertainty components affecting methane emission from a rice paddy is necessary to take account of dispersion characteristics, research on these uncertainty components is very rare to date. The goal of this study was to elucidate influencing factors on measurement uncertainty of methane concentrations measured by a closed automated chamber system from a rice paddy. METHODS AND RESULTS: The methane sampling system is located in the rice paddy in Gyeonggi-do Agricultural Research and Extension Services (37°13'15"N, 127°02'22"E). The primary measurement uncertainty components influencing methane concentrations (influencing factors) investigated in this research were repeatability, reproducibility and calibration in the aspects of methane sampling and analytical instrumentation. The magnitudes of the relative standard uncertainty of each influencing factor were quantified and compared. CONCLUSION: Results of this study showed what influencing factors were more important in determination of methane concentrations measured using the chamber system and analytical instrumentation located in the monitoring site. Quantifying the measurement uncertainty of the methane concentrations in this study would contribute to improving measurement quality of methane fluxes.

• Korean Journal of Environmental Agriculture
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• v.39 no.3
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• pp.237-245
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• 2020

BACKGROUND: The closed chamber method is the most commonly used for measuring greenhouse gas emissions from upland fields. This method has the advantages of being simple, easily available and economical. However, uncertainty estimation is essential for accurate assessment of greenhouse gas emissions and verification of emission reductions. The nitrous oxide emissions from upland field is very important for the nitrogen budget in the agriculture sectors. Although assessment of uncertainty components affecting nitrous oxide emission from upland field is necessary to take account of dispersion characteristics, research on these uncertainty components is very rare to date. This study aims at elucidation of influencing factors on measurement uncertainty of nitrous oxide concentrations measured by an automated open closed chamber method from upland field. METHODS AND RESULTS: The nitrous oxide sampling system is located in the upland field in Gyeonggi-do Agricultural Research and Extension Services (37°13'22"N, 127°02'22"E). The primary measurement uncertainty components influencing nitrous oxide concentrations (influencing factors) investigated in this research are repeatability, reproducibility and calibration in the aspects of nitrous oxide sampling and analytical instrumentation. The magnitudes of the relative standard uncertainty of each influencing factor are quantified and compared. CONCLUSION: Results of this study show what influencing factors are more important in determination of nitrous oxide concentrations measured using the automated open closed chambers located in the monitoring site. Quantifying the measurement uncertainty of the nitrous oxide concentrations in this study would contribute to improving measurement quality of nitrous oxide fluxes.

• Journal of Korean Society of Forest Science
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• v.102 no.4
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• pp.477-483
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• 2013

The purpose of this study was to calculate uncertainty of emission factor collected data and to evaluate the applicability of Monte Carlo simulation technique. To estimate the distribution of emission factors (Such as Basic wood density, Biomass expansion factor, and Root-to-shoot ratio), four probability density functions (Normal, Lognormal, Gamma, and Weibull) were used. The two sample Kolmogorov-Smirnov test and cumulative density figure were used to compare the optimal probability density function. It was observed that the basic wood density showed the gamma distribution, the biomass expansion factor results the log-normal distribution, and root-shoot ratio showd the normal distribution for Pinus densiflora in the Gangwon region; the basic wood density was the normal distribution, the biomass expansion factor was the gamma distribution, and root-shoot ratio was the gamma distribution for Pinus densiflora in the central region, respectively. The uncertainty assessment of emission factor were upper 62.1%, lower -52.6% for Pinus densiflora in the Gangwon region and upper 43.9%, lower -34.5% for Pinus densiflora in the central region, respectively.