• Proceedings of the Korea Water Resources Association Conference
• /
• 2006.05a
• /
• pp.149-153
• /
• 2006

Precipitation is the most important component and critical to the study of water and energy cycle. This study investigates the propagation of precipitation retrieval uncertainty in the simulation of hydrologic variables for varying spatial resolution on two different vegetation cover. We explore two remotely sensed rain retrievals (space-borne IR-only and radar rainfall) and three spatial grid resolutions. An offline Community Land Model (CLM) was forced with in situ meteorological data In turn, radar rainfall is replaced by the satellite rain estimates at coarser resolution $(0.25^{\circ},\;0.5^{\circ}\;and\;1^{\circ})$ to determine their probable impact on model predictions. Results show how uncertainty of precipitation measurement affects the spatial variability of model output in various modelling scales. The study provides some intuition on the uncertainty of hydrologic prediction via interaction between the land surface and near atmosphere fluxes in the modelling approach.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.25 no.8
• /
• pp.802-807
• /
• 2014

In this paper, an accurate method to estimate the measurement uncertainty of a power amplifier was proposed. Because power amplifiers incorporate mismatch at the drain for the optimal performance, the general method is not enough to produce precise measurement uncertainty of the output power. In order to supplement this method, We suggest comprehensive power measurement uncertainty which is utilized by a complex reflection coefficient and measurement uncertainty of S-parameter which contain the mismatch at the drain on the power amplifier. After that, we compared it with real measurement results of the 10 watt power amplifier which operates on 3.7 GHz. As a result, suggested measurement uncertainty could obtain the uncertainty of output power near 10 times accurate in comparison with existing uncertainty calculation method.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2004.03b
• /
• pp.391-398
• /
• 2004

The propagation mechanism of a detonation pressure with fully coupled charge is clarified and the blasting pressure propagated in rock mass is derived from the application of shock wave theory. Probabilistic distribution is obtained by using explosion tests on emulsion and rock property tests on granite in Seoul and then the probabilistic distribution of the blasting pressure is derived from their properties. The probabilistic distributions of explosive properties and rock properties show a normal distribution so that the blasting pressure propagated in rock can be also regarded as a normal distribution. Parametric analysis was performed to pinpoint the most influential parameter that affects the blasting pressure and it was found that the detonation velocity is the most sensitive parameter. Moreover, uncertainty analysis was performed to figure out the effect of each parameter uncertainty on the uncertainty of blasting pressure. Its result showed that uncertainty of natural rock properties constitutes the main portion of blasting pressure uncertainty rather than that of explosive properties.

• Earthquakes and Structures
• /
• v.8 no.4
• /
• pp.915-934
• /
• 2015

Within the context of Structural Health Monitoring (SHM), it is often the case that structural systems are described by uncertainty, both with respect to their parameters and the characteristics of the input loads. For the purposes of system identification, efficient modeling procedures are of the essence for a fast and reliable computation of structural response while taking these uncertainties into account. In this work, a reduced order metamodeling framework is introduced for the challenging case of nonlinear structural systems subjected to earthquake excitation. The introduced metamodeling method is based on Nonlinear AutoRegressive models with eXogenous input (NARX), able to describe nonlinear dynamics, which are moreover characterized by random parameters utilized for the description of the uncertainty propagation. These random parameters, which include characteristics of the input excitation, are expanded onto a suitably defined finite-dimensional Polynomial Chaos (PC) basis and thus the resulting representation is fully described through a small number of deterministic coefficients of projection. The effectiveness of the proposed PC-NARX method is illustrated through its implementation on the metamodeling of a five-storey shear frame model paradigm for response in the region of plasticity, i.e., outside the commonly addressed linear elastic region. The added contribution of the introduced scheme is the ability of the proposed methodology to incorporate uncertainty into the simulation. The results demonstrate the efficiency of the proposed methodology for accurate prediction and simulation of the numerical model dynamics with a vast reduction of the required computational toll.

• Proceedings of the SAREK Conference
• /
• 2006.06a
• /
• pp.369-374
• /
• 2006

Quantification of infiltration rate is an important issue in HVAC system design. The infiltration in buildings depends on many uncertain parameters that vary with significant magnitude and hence, the results from standard deterministic simulation approach can be unreliable. The authors utilize uncertainty analysis In predicting the airflow rates. The paper presents relevant uncertain parameters such as meteorological data, building parameters (leakage areas of windows, doors, etc.), etc. Uncertainties of the aforementioned parameters are quantified based on available data from literature. Then, the Latin Hypercube Sampling (LHS) method was used for the uncertainty propagation. The LHS is one of the Monte Carlo simulation techniques that is suited for our needs. The CONTAMW was chosen to simulate infiltration phenomena in a residential apartment that is typical of residential buildings in Korea. It will be shown that the uncertainty propagating through this process is not negligible and may significantly influence the prediction of the airflow rates.

• Journal of the Korean Society of Visualization
• /
• v.17 no.2
• /
• pp.48-57
• /
• 2019

A straightforward strategy for particle image velocimetry (PIV) interrogation and post-processing has been proposed, aiming at reducing errors and clarifying vortex structures. The interrogation window size should be kept small to reduce bias error and improve spatial resolution. A spatial filter is then applied to the velocity field to reduce random error and clarify flow structure. The performance of three popular spatial filters were assessed: box filter, median filter, and local quadratic polynomial regression filter. In order to quantify random uncertainty, the image matching (IM) method is applied to an experimental dataset of homogeneous and isotropic turbulence (HIT) obtained by 2D-PIV. We statistically analyze the uncertainty propagation through the spatial filters, and verify the reduction in random uncertainty. Moreover, we illustrate that the spatial filters help clarify vortex structures using vortex identification criteria. As a result, PIV random uncertainty was reduced and the vortex structures became clearer by spatial filtering.

• Nuclear Engineering and Technology
• /
• v.44 no.2
• /
• pp.161-176
• /
• 2012

McCARD is a Monte Carlo (MC) neutron-photon transport simulation code. It has been developed exclusively for the neutronics design of nuclear reactors and fuel systems. It is capable of performing the whole-core neutronics calculations, the reactor fuel burnup analysis, the few group diffusion theory constant generation, sensitivity and uncertainty (S/U) analysis, and uncertainty propagation analysis. It has some special features such as the anterior convergence diagnostics, real variance estimation, neutronics analysis with temperature feedback, $B_1$ theory-augmented few group constants generation, kinetics parameter generation and MC S/U analysis based on the use of adjoint flux. This paper describes the theoretical basis of these features and validation calculations for both neutronics benchmark problems and commercial PWR reactors in operation.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2003.05a
• /
• pp.175-180
• /
• 2003

Ultrasonic pulse velocity method is applied many times for measuring surface crack depth of concrete in case of diagnosis of concrete structures. By the way, this method has an error accompanying measured surface crack depth of concrete because there are many uncertainty factors. So, it is necessary to study for an error of this method affected by these uncertainty factors. Two error factors(uncertainty factors) are tested and analyzed in this study. One is for an error according to measuring the propagation time of ultrasonic wave and the arrangement distance of transducers. Another is for an error according to positioning the transducer as a distance to surface crack from the transducer.

• Proceedings of the Korean Nuclear Society Conference
• /
• 1995.05a
• /
• pp.509-516
• /
• 1995

The uncertainty analysis for the in-vessel steam explosion during severe accidents at a nuclear power plant is performed using a probabilistic approach. This approach consists of four steps; 1) screening, 2) quantification of uncertainty 3) propagation of uncertainty, and 4) output analysis. And the specific methods which satisfy the sub-objectives of each step are prepared and presented. Compared with existing ones, the unique feature of this approach is the improved estimation of uncertainties through quantification, which ensures the defensibility of the resultant failure probability distributions. Using the approach, the containment failure probability due to in-vessel steam explosion is calculated. The results of analysis show that 1) pour diameter is the most dominant factor and slug condensed phase fraction is the least and 2) fraction of core molten is the second most dominant factor, which is identified as distinct feature of this study as compared with previous studies.

• Journal of Institute of Control, Robotics and Systems
• /
• v.3 no.3
• /
• pp.252-258
• /
• 1997

This paper presents neural networks for hybrid position/force control which is a type of position and force control for robot manipulators. The performance of conventional hybrid position/force control is excellent in the case of the exactly-known dynamic model of the robot, but degrades seriously as the uncertainty of the model increases. Hence, the neural network control scheme is presented here to overcome such shortcoming. The introduced neural term is designed to learn the uncertainty of the robot, and to control the robot through uncertainty compensation. Further more, the learning rule of the neural network is derived and is shown to be effective in the sense that it requires neither desired output of the network nor error back propagation through the plant. The proposed scheme is verified through the simulation of hybrid position/force control of a 6-dof robot manipulator.