• Journal of Soil and Groundwater Environment
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• v.9 no.1
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• pp.28-38
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• 2004

This study presents the result of uncertainty and sensitivity analysis of a pharmacokinetic model which describes the distribution and removal of benzene at each organ when an indivisual inhales indoor contaminated air with benzene originated from groundwater. The pharmacokinetic model simulates the distribution of benzene deposited in organs of human body through inhalation of contaminated indoor air as well as degradation-metabolism in liver. This study focused on the uncertainty problem induced from the use of the single values for blood flow, partition coefficient, degradation constant, volume, etc. of each organ which was due to a lack of knowledge about these parameters or their measurements. To solve this problem, uncertainty analysis on the pharmacokinetic model was conducted simultaneously which would help understanding the risk assessment associated with VOCs.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.2803-2815
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• 2021

This paper addresses the uncertainty quantification and sensitivity analysis of a depleted light-water fuel assembly of the Turkey Point-3 benchmark. The uncertainty of the fuel assembly decay heat and isotopic densities is quantified with respect to three different groups of diverse parameters: nuclear data, assembly design, and reactor core operation. The uncertainty propagation is conducted using a two-step analysis code system comprising the lattice code STREAM, nodal code RAST-K, and spent nuclear fuel module SNF through the random sampling of microscopic cross-sections, fuel rod sizes, number densities, reactor core total power, and temperature distributions. Overall, the statistical analysis of the calculated samples demonstrates that the decay heat uncertainty decreases with the cooling time. The nuclear data and assembly design parameters are proven to be the largest contributors to the decay heat uncertainty, whereas the reactor core power and inlet coolant temperature have a minor effect. The majority of the decay heat uncertainties are delivered by a small number of isotopes such as ²⁴¹Am, ¹³⁷Ba, ²⁴⁴Cm, ²³⁸Pu, and ⁹⁰Y.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.7 s.184
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• pp.51-58
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• 2006

This study analyzes the uncertainty of the compensation method of a sensing error of three-DOF measuring system. This compensation method utilizes a reference coordinate system using a three point by moving a position of an endpoint of a three-DOF manipulator. The coordinate transformation between the three-DOF manipulator and the measuring system is identified by the reference coordinate system. According to the concept of this compensation method, each positioning error at any position of the end-point of the manipulator is derived. Uncertainty analyses of the compensation values on the basis of sensitivity analysis and Monte Carlo simulation are used to investigate a feasibility and effectiveness of the compensation method.

• Journal of Soil and Groundwater Environment
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• v.25 no.1
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• pp.37-52
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• 2020

Sensitivity analysis of hydrodynamic and reaction parameters in conceptual model reflecting aquifer characteristics of Korea was performed to evaluate the uncertainty in the predicted concentrations. Among the hydrodynamic input parameters, both hydraulic conductivity (K_x) and hydraulic gradient (I) affected transport behaviors of contaminants, and resulted in same convergence concentrations with continuous injections of contaminant. However, longitudinal dispervisity (α_L) affected both transport behaviors and the convergence concentrations of contaminants. Compared to the hydrodynamic parameters, growth kinetic and degradation parameters (μ_m & K_c) more significantly affected both transport behaviors and the convergence concentrations of contaminants, indicating those parameters had higher sensitivity indices causing the uncertainties of model predictions. Considering that the sensitivity indices of both hydrodynamic and reaction parameters were a function of transport distance of groundwater, the parameters with higher sensitivity indices, a priori, need to be investigated using conceptual model reflecting site-specific aquifer characteristics before field investigation. After determining the parameters with higher sensitivity indices, the detail field investigations for the selected hydrodynamic and reaction parameters were warranted to reduce the uncertainties of model predictions.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1687-1707
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• 2023

This paper presents a molten salt reactor (MSR) design parameter sensitivity study using a nodal dynamic modelling methodology with explicitly modified point kinetics equation and Mann's model for heat transfer. Six parameters that can impact MSR safety are evaluated. A MATLAB-Simulink model inspired by Thorcon's 550MWth MSR is used for parameter evaluations. A safety envelope was formed to encapsulate power, maximum and minimum temperature, and temperature-induced reactivity feedback. The parameters are perturbed by ±30%. The parameters were then ranked by their subsequent impact on the considered safety envelope, which ranks acceptable parameter uncertainty. The model is openly available on GitHub.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.281-287
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• 1999

Decision class analysis (DCA) is viewed as a classification problem where a set of input data (situation-specific knowledge) and output data (a topological leveled influence diagram (ID)) is given. Situation-specific knowledge is usually given from a decision maker (DM) with the help of domain expert(s). But it is not easy for the DM to know the situation-specific knowledge of decision problem exactly. This paper presents a methodology fur sensitivity analysis of DCA under incomplete information. The purpose of sensitivity analysis in DCA is to identify the effects of incomplete situation-specific frames whose uncertainty affects the importance of each variable in the resulting model. For such a purpose, our suggested methodology consists of two procedures: generative procedure and adaptive procedure. An interactive procedure is also suggested based the sensitivity analysis to build a well-formed ID. These procedures are formally explained and illustrated with a raw material purchasing problem.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.281-287
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• 1999

Decision class analysis (DCA) is viewed as a classification problem where a set of input data (situation-specific knowledge) and output data(a topological leveled influence diagram (ID)) is given. Situation-specific knowledge is usually given from a decision maker (DM) with the help of domain expert(s). But it is not easy for the DM to know the situation-specific knowledge of decision problem exactly. This paper presents a methodology for sensitivity analysis of DCA under incomplete information. The purpose of sensitivity analysis in DCA is to identify the effects of incomplete situation-specific frames whose uncertainty affects the importance of each variable in the resulting model. For such a purpose, our suggested methodology consists of two procedures: generative procedure and adaptive procedure. An interactive procedure is also suggested based the sensitivity analysis to build a well-formed ID. These procedures are formally explained and illustrated with a raw material purchasing problem.

• Journal of Environmental Impact Assessment
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• v.9 no.3
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• pp.185-202
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• 2000

Uncertainty and variability in Life Cycle Assessment(LCA) have been significant key issues in LCA methodology with techniques in other research area such as social and political science. Variability is understood as stemming from inherent variations in the real world, while uncertainty comes from inaccurate measurements, lack of data, model assumptions, etc. Related articles in this issues were reviewed for classification, distinguish and elaboration of probabilistic/stochastic health risk analysis application in LCA. Concept of focal zone, streamlining technique, scenario modelling and Monte Carlo/Latin Hypercube risk analysis were applied to the uncertainty/variability analysis of health risk in LCA. These results show that this general framework of multi-disciplinary methodology between probabilistic health risk assessment and LCA was of benefit to decision making process by suppling information about input/output data sensitivity, health effect priority and health risk distribution. There should be further research needs for case study using this methodology.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.780-786
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• 2013

In the reliability-based design optimization of electromagnetic devices, the accurate and efficient reliability assessment method is very essential. The first-order sensitivity-assisted Monte Carlo Simulation is proposed in the former research. In order to improve its accuracy for wide application, in this paper, the second-order sensitivity analysis is presented by using the hybrid direct differentiation-adjoint variable method incorporated with the finite element method. By combining the second-order sensitivity with the Monte Carlo Simulation method, the second-order sensitivity-assisted Monte Carlo Simulation algorithm is proposed to implement reliability calculation. Through application to one superconductor magnetic energy storage system, its accuracy is validated by comparing calculation results with other methods.

• Magazine of the Korea Concrete Institute
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• v.10 no.6
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• pp.149-159
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• 1998

The reasonable prediction of time-dependent deformation of prestressed concrete(PSC) box girder bridges is very important for accurate construction as well as good serviceability. The long-term behavior is mostly influenced by the probabilistic characteristic of creep and shrinkage. This paper presents a method of statistical analysis and sensitivity analysis of creep and shrinkage effects in PSC box been taken into account - model uncertainty, parameter variation and environmental condition. The statistical and sensitivity analyses are performed by using the numerical simulation of Latin Hypercube sampling. For each sample, the time-dependent structural analysis is performed to produce response data, which are then statistically analyzed. The probabilistic prediction of the confidence limits on long-term effects of creep and shrinkage is then expressed. Three measure are examined to quantify the sensitivity of the outputs of each of the input variables. These are rank correlation coefficient(RCC), partical rank correlation coefficient(PRCC) and standardiozed rank regression coefficient(SRRC) computed on the ranks of the observations. Three creep and shrinkage models - i. e., ACI model. CEB-FIP model and the model in Korea Highway Bridge Specification - are studied. The creep model uncertainy factor and the relative humidity appear to be the most dominant factors with regard to the model output uncertainty.