• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.125-135
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• 2013

Analysis and evaluation of uncertainty is adopting the advanced methodology among the methods for greenhouse gas emission assessment that was defined in GPS2000 (Good practice guideline 2000) and GPG-LULUCF (GPG Land Use, Land-Use Change and Forestry). In 2006 IPCC guideline, two approaches are suggested to explain the uncertainty for each section with a national net emission and a prediction value on uncertainty as follows; 1) Spread sheet calculation based on the error propagation algorithm that was simplified with some assumptions, and 2) Monte carlo simulation that can be utilized in general purposes. There are few researches on the agricultural field including greenhouse gas emission that is generated from livestock and cultivation lands due to lack of information for statistic data, emission coefficient, and complicated emission formula. The main objective of this study is to suggest an evaluation method for the uncertainty of greenhouse gas emission in agricultural field by means of intercomparison of the prediction value on uncertainties which were estimated by spread sheet calculation and monte carlo simulation. A statistic analysis for probability density function for uncertainty of emission rate was carried out by targeting livestock intestinal fermentation, excrements treatment, and direct/indirect emission from agricultural lands and rice cultivation. It was suggested to minimize uncertainty by means of extraction of emission coefficient according to each targeting section.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.10
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• pp.60-64
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• 2015

Many people think that Electric Vehicles(EVs) is the best method to resolve the problems of running out of fossil fuels. But EVs take long time for charging. So, EVs with battery swapping systems(EVBS) are developed to resolve this problem. Nonetheless, EVBS is not spreaded widely because the method of durability test in couplers is not defined. In this study, the evaluation method of durability test in couplers is defined by some standards and the measurement uncertainty is used to increase the reliability of EV couplers.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.179-185
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• 2010

In a sensitivity analysis, an uncertainty importance measure is often used to assess how much uncertainty of an output is attributable to the uncertainty of an input, and thus, to identify those inputs whose uncertainties need to be reduced to effectively reduce the uncertainty of output. A function is called monotonic if the output is either increasing or decreasing with respect to any of the inputs. In this paper, for a monotonic function, we propose a method for evaluating the measure which assesses the expected percentage reduction in the variance of output due to ascertaining the value of input. The proposed method can be applied to the case that the output is expressed as linear and nonlinear monotonic functions of inputs, and that the input follows symmetric and asymmetric distributions. In addition, the proposed method provides a stable uncertainty importance of each input by discretizing the distribution of input to the discrete distribution. However, the proposed method is computationally demanding since it is based on Monte Carlo simulation.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.187-195
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• 2009

In a fault tree analysis, an uncertainty importance measure is often used to assess how much uncertainty of the top event probability (Q) is attributable to the uncertainty of a basic event probability ($q_i$), and thus, to identify those basic events whose uncertainties need to be reduced to effectively reduce the uncertainty of Q. For evaluating the measures suggested by many authors which assess a percentage change in the variance V of Q with respect to unit percentage change in the variance $\upsilon_i$ of $q_i$, V and ${\partial}V/{\partial}{\upsilon}_i$ need to be estimated analytically or by Monte Carlo simulation. However, it is very complicated to analytically compute V and ${\partial}V/{\partial}{\upsilon}_i$ for large-sized fault trees, and difficult to estimate them in a robust manner by Monte Carlo simulation. In this paper, we propose a method for experimentally evaluating the measure using a Taguchi orthogonal array. The proposed method is very computationally efficient compared to the method based on Monte Carlo simulation, and provides a stable uncertainty importance of each basic event.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.14 no.23
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• pp.57-64
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• 1991

The preliminary, advanced and final evaluation of R&D project is essential in order to reduce loss of resource and opportunity and to minimize uncertainty resulting from optimal selection and efficient progress of R&D project. This thesis examined characteristics of deterministic evaluation, economical evaluation, and OR-approach evaluation as theoretical methodology of evaluation of R&D project applicable to food industry in Korea by using scoring method, one of deterministic evaluations. In addition, this thesis divided the evaluation factors for preliminary evaluation of R&D project into 5 groups and 30 factors on basis of the environment of domestic companies and set up the standard of each evaluation factors and contains marking-selecting way. But, generally, the evaluation model by this thesis, as the conditions of the business company environment are different to each other, contents to be set up evaluation factors, evaluation standard and decision method conforming to each the environment of the business companies with referring to as one standard of evaluation project for selecting R&D project.

• Nuclear Engineering and Technology
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• v.41 no.4
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• pp.381-390
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• 2009

This article provides selects of outstanding problems in computational neutron transport, with some suggested approaches thereto, as follows: i) ray effect in discrete ordinates method, ii) diffusion synthetic acceleration in strongly heterogeneous problems, iii) method of characteristics extension to three-dimensional geometry, iv) fission source and $k_{eff}$ convergence in Monte Carlo, v) depletion in Monte Carlo, vi) nuclear data evaluation, and vii) uncertainty estimation, including covariance data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.4
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• pp.653-659
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• 2015

In the last few years, the regulations for efficiency grade of the three phase induction motor are internationally being discussed and upgraded for the protection of environment and energy saving. So the efficiency improvement and the reliable test result are essential to determine the premium grade three phase induction motor. While a study on developing the efficiency motor is active, there is little research about the guarantee for efficiency. So in this paper, the dispersion characteristic of the efficiency is studied using uncertainty theory for the three phase induction motor to improve the reliability of efficiency. The values such as input voltage, current, speed, torque were obtained by loss separation method to evaluate the uncertainty. From the result, it was known that the important loss factor could affect the uncertainty is the stray loss.

• Journal of Radiation Industry
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• v.17 no.4
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• pp.345-357
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• 2023

Nuclear forensics has been understood as a mendatory component in the international society for nuclear material control and non-proliferation verification. Radiochronometry of nuclear activities for nuclear forensics are decay series characteristics of nuclear materials and the Bateman equation to estimate when nuclear materials were purified and produced. Radiochronometry values have uncertainty of measurement due to the uncertainty factors in the estimation process. These uncertainties should be calculated using appropriate evaluation methods that are representative of the accuracy and reliability. The IAEA, US, and EU have been researched on radiochronometry and uncertainty of measurement, although the uncertainty calculation method using the Bateman equation is limited by the underestimation of the decay constant and the impossibility of estimating the age of more than one generation, so it is necessary to conduct uncertainty calculation research using computer simulation such as Monte Carlo method. This highlights the need for research using computational simulations, such as the Monte Carlo method, to overcome these limitations. In this study, we have analyzed mathematical models and the LHS (Latin Hypercube Sampling) methods to enhance the reliability of radiochronometry which is to develop an uncertainty algorithm for nuclear material radiochronometry using Bateman Equation. We analyzed the LHS method, which can obtain effective statistical results with a small number of samples, and applied it to algorithms that are Monte Carlo methods for uncertainty calculation by computer simulation. This was implemented through the MATLAB computational software. The uncertainty calculation model using mathematical models demonstrated characteristics based on the relationship between sensitivity coefficients and radiative equilibrium. Computational simulation random sampling showed characteristics dependent on random sampling methods, sampling iteration counts, and the probability distribution of uncertainty factors. For validation, we compared models from various international organizations, mathematical models, and the Monte Carlo method. The developed algorithm was found to perform calculations at an equivalent level of accuracy compared to overseas institutions and mathematical model-based methods. To enhance usability, future research and comparisons·validations need to incorporate more complex decay chains and non-homogeneous conditions. The results of this study can serve as foundational technology in the nuclear forensics field, providing tools for the identification of signature nuclides and aiding in the research, development, comparison, and validation of related technologies.

• Tunnel and Underground Space
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• v.12 no.3
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• pp.189-197
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• 2002

In recent years, the probabilistic analysis has been used in rock slope engineering. This is because uncertainty is pervasive in rock slope engineering and most geometric and geotechnical parameters of discontinuity and rock masses are involved with uncertainty. Whilst the traditional deterministic analysis method fails to properly deal with uncertainty, the probabilistic analysis has advantages quantifying the uncertainty in parameters. As a probabilistic analysis method, the Monte Carlo simulation has been used commonly. However, the Monte Carlo simulation requires many repeated calculations and therefore, needs much effort and time to calculate the probability of failure. In contrast, the point estimate method involves a simple calculation with moments for random variables. In this study the probability of failure in rock slope is evaluated by the point estimate method and the results are compared to the probability of failure obtained by Monte Carlo simulation method.

• Korean Journal of Optics and Photonics
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• v.20 no.2
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• pp.110-117
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• 2009

This work introduces the uncertainty evaluation formulation on color measurement of light sources and display devices, such as CIE 1931 (x, y) chromaticity, CIE 1960 (u, v) chromaticity, correlated color temperature, and distribution temperature. All the mentioned quantities are reduced from spectral data in the visible range, for which uncertainties are strongly correlated between different wavelengths. Using matrix algebra we have formulated the uncertainty propagation from the SI- traceable spectral irradiance standard to the individual color related measurement quantities taking the correlation between wavelengths into account. As a result, we have demonstrated uncertainty evaluation examples of 3 types of light sources: CIE illuminant A, LED white light, and LCD white light. This method can be applied to any other quantities based on spectral measurement such as solar irradiance, material color measurement, etc.