• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.154-154
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• 2018

To interpret the climate projections for the future as well as present, recognition of the consequences of the climate internal variability and quantification its uncertainty play a vital role. The Korean Peninsula belongs to the Far East Asian Monsoon region and its rainfall characteristics are very complex from time and space perspective. Its internal variability is expected to be large, but this variability has not been completely investigated to date especially using models of high temporal resolutions. Due to coarse spatial and temporal resolutions of General Circulation Models (GCM) projections, several studies adopted dynamic and statistical downscaling approaches to infer meterological forcing from climate change projections at local spatial scales and fine temporal resolutions. In this study, stochastic downscaling methodology was adopted to downscale daily GCM resolutions to hourly time scale using an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). After extracting factors of change from the GCM realizations, these were applied to the climatic statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series which can be considered to be representative of future climate conditions. Further, 30 ensemble members of hourly precipitation were generated for each selected station to quantify uncertainty. Spatial map was generated to visualize as separated zones formed through K-means cluster algorithm which region is more inconsistent as compared to the climatological norm or in which region the probability of occurrence of the extremes event is high. The results showed that the stations located near the coastal regions are more uncertain as compared to inland regions. Such information will be ultimately helpful for planning future adaptation and mitigation measures against extreme events.

• Journal of Environmental Science International
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• v.20 no.3
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• pp.329-340
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• 2011

The probability concepts mainly used for rainfall or flood frequency analysis in water resources planning are the frequentist viewpoint that defines the probability as the limit of relative frequency, and the unknown parameters in probability model are considered as fixed constant numbers. Thus the probability is objective and the parameters have fixed values so that it is very difficult to specify probabilistically the uncertianty of these parameters. This study constructs the uncertainty evaluation model using Bayesian MCMC and Metropolis -Hastings algorithm for the uncertainty quantification of parameters of probability distribution in rainfall frequency analysis, and then from the application of Bayesian MCMC and Metropolis- Hastings algorithm, the statistical properties and uncertainty intervals of parameters of probability distribution can be quantified in the estimation of probability rainfall so that the basis for the framework configuration can be provided that can specify the uncertainty and risk in flood risk assessment and decision-making process.

• YAKHAK HOEJI
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• v.51 no.3
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• pp.206-213
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• 2007

Recently estimating the uncertainty of an analytical result has become an essential part of quantitative analysis. This study describes the uncertainty of the measurement for the determination of methamphetamine and its major metabolite amphetamine in human hair, The method consists of washing, drying, weighing, incubation and extraction with methanolic HCI solution, clean-up, trifluoroacetyl derivatization, and qualification/quantification of residues by gas chromatography/mass spectrometry (GC/MS). Traceability of measurement was established through traceable standards and calibrated volumetric equipment and measuring instruments. Measurement uncertainty associated with each analyte in real samples was estimated using quality control (QC) data. The main source of combined standard uncertainty comprised two components, which are uncertainties associated with calibration linearity and variations in QC, while those associated with preparation of analytical standards and sample weighing were not so important considering the degree of contribution. Relative combined standard uncertainties associated with the described method ranged for individual analytes from 4.99 to5.03%.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.2084-2093
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• 2022

Probabilistic safety assessment is widely used to quantify the risks of nuclear power plants and their uncertainties. When the lognormal distribution describes the uncertainties of basic events, the uncertainty of the top event in a fault tree is approximated with the sum of lognormal random variables after minimal cutsets are obtained, and rare-event approximation is applied. As handling complicated analytic expressions for the sum of lognormal random variables is challenging, several approximation methods, especially Monte Carlo simulation, are widely used in practice for uncertainty analysis. In this study, a theoretical approach for analyzing the sum of lognormal random variables using an efficient numerical integration method is proposed for uncertainty analysis in probability safety assessments. The change of variables from correlated random variables with a complicated region of integration to independent random variables with a unit hypercube region of integration is applied to obtain an efficient numerical integration. The theoretical advantages of the proposed method over other approximation methods are shown through a benchmark problem. The proposed method provides an accurate and efficient approach to calculate the uncertainty of the top event in probabilistic safety assessment when the uncertainties of basic events are described with lognormal random variables.

• Proceedings of the Korean Nuclear Society Conference
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• 2003.10a
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• pp.131-131
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• 2003

• Korean Journal of Radiology
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• v.25 no.4
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• pp.328-330
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• 2024

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1804-1812
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• 2022

The aim of this paper is to assess the reliability and accuracy of the PSI standard method, used in many previous works, for the quantification of ND uncertainties in the SPERT-III RIA transient, by quantifying the discrepancy between the actual inserted reactivity and the original static reactivity worth and their associated uncertainties. The assessment has shown that the inherent S3K neutron source renormalization scheme, introduced before starting the transient, alters the original static reactivity worth of the transient CR and reduces the associated uncertainty due to the ND perturbation. In order to overcome these limitations, two additional methods have been developed based on CR adjustment. The comparative study performed between the three methods has showed clearly the high sensitivity of the obtained results to the selected approach and pointed out the importance of using the right procedure in order to simulate correctly the effect of ND uncertainties on the overall parameters in a RIA transient. This study has proven that the approach that allows matching the original static reactivity worth and starting the transient from criticality is the most reliable method since it conservatively preserves the effect of the ND uncertainties on the inserted reactivity during a RIA transient.

• Steel and Composite Structures
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• v.44 no.5
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• pp.651-676
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• 2022

Most of the experimental, theoretical, and numerical studies on the stability of functionally graded composites are deterministic, while there are full of complex interactions of variables with an inherently probabilistic nature, this paper presents a non-intrusive framework to investigate the stochastic nonlinear buckling behaviors of porous functionally graded cylindrical shells exposed to inevitable source-uncertainties. Euler-Lagrange equations are theoretically derived based on the three variable refined shear deformation theory. Closed-form solutions for the shell buckling loads are achieved by solving the deterministic eigenvalue problems. The analytical results are verified with numerical results obtained from finite element analyses that are conducted in the commercial software ABAQUS. The non-intrusive framework is completed by integrating the Monte Carlo simulation with the verified closed-form solutions. The convergence studies are performed to determine the effective pseudorandom draws of the simulation. The accuracy and efficiency of the framework are verified with statistical results that are obtained from the first and second-order perturbation techniques. Eleven cases of individual and compound uncertainties are investigated. Sensitivity analyses are conducted to figure out the five cases that have profound perturbative effects on the shell buckling loads. Complete probability distributions of the first three critical buckling loads are completely presented for each profound uncertainty case. The effects of the shell thickness, volume fraction index, and stochasticity degree on the shell buckling load under compound uncertainties are studied. There is a high probability that the shell has non-unique buckling modes in stochastic environments, which should be known for reliable analysis and design of engineering structures.

• Journal of Soil and Groundwater Environment
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• v.18 no.1
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• pp.94-101
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• 2013

It is well known that uncertainty associated with soil sampling is bigger than that with analysis. In this research, uncertainties for soil sampling when assessing TPH and BTEX concentration in soils were quantified based on actual field data. It is almost impossible to assess exact contamination of the site regardless how carefully devised for sampling. Uncertainties associated with sample reduction for further chemical analysis were quantified approximately 10 times larger than those associated with core sampling on site. Bigger uncertainties occur when contamination level is low, sample quantity is small, and soil particle is coarse. To minimize the uncertainties on field, homogenization of soil sample is necessary and its procedures are proposed in this research as well.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.4
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• pp.610-615
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• 2018

A filter-based optical technique is one of the representative ways for the measurement and quantification of black carbon (BC). Since the filter-based technique adopts a simple principle, it is easy to put into practical use and instrumental products have already been commercialized. In this study, however, the absorption coefficients of BC after the correction process was estimated to be approximately 3 times lower than those before the correction process. In addition, the difference between before and after corrections was also evident for the trend of increasing and decreasing absorption coefficient. When BC concentration is low, uncertainty may increase regardless of corrections due to the artifacts of filter. In this sense, techniques without using a filter are required, and uncertainties will be minimized if these techniques are used to further complement the filter-based black carbon measurements. Finally, this study is believed to help understand the uncertainty and correction of filter-based black carbon measurements.