• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.657-664
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• 1999

This paper introduced the basic theory of LRCS(Linear Reservoir and Channel System) rainfall runoff model proposed by Korean researchers(Lee and Lee, 1995), and discussed the change of model output according to objective functions in sensitivity analysis and calibration process of model. It proposed "hat" matrix and affluence measures for affluence analysis of parameters in calibration, and investigated relationship between change of model output according to error propagation in parameter estimation, and sensitivity of model output according to variance of model output and change of parameters. Accuracy of parameter estimates was known by analysis of sensitivity coefficient, diagonal element $h_i$ and $D_i$._i$.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2004.06a
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• pp.52-57
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• 2004

In order to analyze key parameters of important radionuclides in dose evaluation model of decommissioning site, a sensitivity analysis was performed. This analysis assumed a resident farmer for an exposure scenario and 0.037Bq/g for the concentration of radionuclides. As a result of sensitivity analysis, the key parameters of radionuclides considered were the area of contaminated zone, external gamma shielding factor and indoor time fraction for Cs-137 and Co-60. The key parameters for C-14 were the environmental parameters and hydrological parameters of unsaturated zone. Also, the key parameter for Sr-90 was the density of contaminated zone.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.7
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• pp.873-879
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• 2010

It is common to predict structural dynamic design parameters due to the change of design parameter, but to predict the amount of changed design parameter where the mass and stiffness are being modified are rarely found in previous literature. In this study, the changed design parameter in a proportional damping system is predicted by using sensitivity coefficients and an iterative method. The sensitivity coefficients are determined from the changes in eigenvectors; these changes are due to modification. This method is applied to a three-story shear structure. To validate the prediction of the changed design parameter, the results are compared to the reanalysis results; both results are in good agreement.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.1
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• pp.44-51
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• 2018

The purpose of RAM analysis in weapon systems is to reduce life cycle costs, along with improving combat readiness by meeting RAM target value. We analyzed the sensitivity of the RAM analysis parameters to the use of the operating system by using the Markov Process based model (MPS, Markov Process Simulation) developed for RAM analysis. A Markov process-based RAM analysis model was developed to analyze the sensitivity of parameters (MTBF, MTTR and ALDT) to the utility of the 81mm mortar. The time required for the application to reach the steady state is about 15,000H, which is about 2 years, and the sensitivity of the parameter is highest for ALDT. In order to improve combat readiness, there is a need for continuous improvement in ALDT.

• Journal of Power System Engineering
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• v.16 no.2
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• pp.11-16
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• 2012

In this paper, the authors formulate the sensitivity analysis algorithm for the natural frequency of a torsional shafting by expanding the transfer stiffness coefficient method. The basic concept of the present algorithm is based on the transfer of sensitivity stiffness coefficient, which is the derivative of stiffness coefficient with respect to design parameter, at every node from the first node to the last node in analytical model. The effectiveness of the present algorithm is confirmed by comparing the results of the sensitivity analysis and those of the reanalysis for the natural frequencies of a torsional shafting with a constant cross section. In numerical calculation, the design parameter is the diameter of the shaft element of the torsional shafting.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.180.2-180.2
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• 2010

The purpose of this research is to analyze the sensitivity of WindSIM in complex terrain. As the flat areas for wind turbine installation become scarce globally, it becomes inevitable to install wind turbines in complex terrain. In order to predict annual energy production (AEP) in a more precise manner in complex terrain, it is of great importance to conduct such research. Three parameters: reference velocity, roughness and resolution have been chosen to see to which parameter WindSIM was the most sensitive in terms of annual energy production in complex terrain. By fixing two parameters and setting one parameter as a variable, it could be easily found that how annual energy production was effected by the change in each parameter.

• Journal of the Korean Society of Safety
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• v.31 no.4
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• pp.143-149
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• 2016

In this study, a series of numerical simulation of dam break flow was conducted using EFDC model, and input conditions including cell size, time step, and turbulent eddy viscosity were considered to analyze parameter sensitivity. In case of coarse mesh layout, the propagated length of the shock wave front was ${\Delta}_x$ longer than that of other mesh layouts, and the velocity results showed jagged edge, which can be cured by applying fine grid mesh. Turbulent eddy viscosity influenced magnitude of the maximum velocity passing through gate up to 20% and the cell Peclet number less than 2.0 ensured no numerical oscillations.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.453-457
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• 2006

This study predicts the modified structure of eigenvectors and eigenvalues due to the changes in the mass and the stiffness of the structure. The sensitivity method of natural frequency using partial differential are derived with respect to the physical parameter to calculate the structure modification. The method are applied to the 3 degree of freedom???slumped mass model by modeling the mass and stiffness, and then applies the method to a real crankshaft system. The position, direction of parameter change and modified value were predicted for modification. Finally the predicted value is used to investigate the magnitude of vibration and we found that the effect of modification results to reduce the level of magnitude vibration is satisfactory.

• Coupled systems mechanics
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• v.11 no.2
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• pp.133-149
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• 2022

The accurate prediction of elastoplasticity under prescribed workloads is essential in the optimization of engineering structures. Mechanical experiments are carried out with the goal of obtaining reliable sets of material parameters for a chosen constitutive law via inverse identification. In this work, two sample geometries made of high strength steel plates were evaluated to determine the optimal configuration for the identification of Ludwik's nonlinear isotropic hardening law. Finite element model updating(FEMU) was used to calibrate the material parameters. FEMU computes the parameter changes based on the Hessian matrix, and the sensitivity fields that report changes of computed fields with respect to material parameter changes. A sensitivity analysis was performed to determine the influence of the sample geometry on parameter identifiability. It was concluded that the sample with thinned gauge region with a large curvature radius provided more reliable material parameters.

• 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.