• Proceedings of the KSR Conference
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• 2003.10c
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• pp.301-306
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• 2003

Recently, uncertainty of measurement became a major concern for the people working on the laboratory evaluation and accreditation. 'uncertainty of measurement is a parameter associated with the result of a measurement that characteristics the dispersion of the value that could reasonably be attributed to the measured.' This study analysed how to estimate uncertainty of measurement in mechanical characteristic exam for Plastic material. its uncertainty was estimated according to International Organization for Standardization(ISO), they were named to A type uncertainty, B type uncertainty, combined standard uncertainty, and expanded uncertainty. We obtained that the combined standard uncertainty was 0.96697 MPa and the expanded uncertainty was 2.291MPa.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.687-690
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• 1991

In deterministic design of feedback controllers for uncertain dynamical systems, the bound on the uncertainty is an important clue to guarantee the asymptotic stability or uniform ultimate boundedness of the closed-loop system. In this paper, using only the measurable output we propose an adaptation law for the estimation of the bound of the uncertainty. And based on this adaptation law an adaptive control which renders the uncertain dynamical systems uniformly ultimately bounded is constructed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.826-829
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• 2008

In a field measurement, measurement errors are produced by measuring environments and systematic errors in the measurement procedure. Measurement errors can be expressed as a measurement uncertainty. In this study, the measurement uncertainty and various measuring factors are investigated in heavy-weight impact sounds. According to KS 2810-2, the model functions, which is the estimation of the maximum SPL measurement in each octave band frequency, are determined. From this estimation model, 3.53dB is shown in 63Hz. This level is caused by the sound field of the receiving room, which does not meet the diffusing field.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.481-487
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• 2013

This paper presents an FIR (Finite Impulse Response) fixed-interval smoothing filter for fast and exact estimating state variables of a discrete nonlinear system with modeling uncertainty. Conventional IIR (Infinite Impulse Response) filter and smoothing filter can estimate state variables of a system with an exact model when the system is observable. When there is an uncertainty in the system model, however, conventional IIR filter and smoothing filter may cause large errors because the filters cannot estimate the state variables corresponding to the uncertain model exactly. To solve this problem, FIR filters that have fast estimation properties and have robustness to the modeling uncertainty have been developed. However, there is time-delay estimation phenomenon in the FIR filter. The FIR smoothing filter proposed in this paper makes up for the drawbacks of the IIR filter, IIR smoothing filter, and FIR filter. Therefore, the FIR smoothing filter has good estimation performance irrespective of modeling uncertainty. The proposed FIR smoothing filter is applied to the integrated navigation system composed of a magnetic compass based DR (Dead Reckoning) and a GPS (Global Positioning System) receiver. Even when the magnetic compass error that changes largely as the surrounding magnetic field is modeled as a random constant, it is shown that the FIR smoothing filter can estimate the varying magnetic compass error fast and exactly with simulation results.

• Journal of Aerospace System Engineering
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• v.12 no.3
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• pp.53-57
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• 2018

The Monte Carlo simulation (MCS) method and the Guide to the Expression of Uncertainty in Measurement (GUM) are the most widely used approaches for uncertainty estimation. In this paper, MCS and GUM were used to estimate the confidence of MOI measurement equipment developed in-house. According to the results, the GUM estimated uncertainty was slightly underestimated compared to the MCS method. This difference is due to the approximation used by GUM. MOI uncertainties estimated by both methods were less than 1% of the estimate, which shows the high measurement reliability of the developed MOI measurement system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.1
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• pp.73-78
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• 2010

Estimation of tensile properties measurement uncertainty of material was carried out. Sources of uncertainty affecting the measurement of tensile properties were classified and analyzed. The models for uncertainty evaluation of measurands to be determined from tensile test, such as elastic modulus, yield strength and tensile strength, were suggested and derived from the mathematical relations, corresponding to the respective measurands, and the measuring quantities by calculating each sensitivity coefficient of the quantities. Based on these models, the uncertainty of the tensile properties was evaluated from the experimental data of SUS316LN determined according to ISO 6892.

• International journal of steel structures
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• v.18 no.5
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• pp.1508-1524
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• 2018

Hysteretic energy dissipating devices (HEDDs) have been increasingly applied to building construction to improve the seismic performance. The seismic responses of such damped structures are significantly affected by HEDD's structural properties. An accurate investigation on the propagation of HEDD's structural properties is required for reasonable evaluation of the seismic performance of a structure. This study aims to develop simplified methods that can estimate the collective uncertainty-propagation to the seismic response of damped structures employing HEDDs. To achieve this, three- and six-story steel moment-resisting frames were selected and the propagations of the individual HEDD's property-uncertainties were evaluated when they are subjected to various levels of seismic demand. Based on the result of individual uncertainty-propagations, a simplified method is proposed to evaluate the variation of seismic response collectively propagated by HEDD's property-uncertainties and is verified by comparing with the exact collective uncertainty-propagation calculated using the Monte Carlo simulation method. The proposed method, called as a modified SRSS method in this study, is established from a conventional square root of the sum of the squares (SRSS) method with the relative contributions of the individual HEDD's property-uncertainty propagations. This study shows that the modified SRSS method provides a better estimation than the conventional SRSS method and can significantly reduce computational time with reasonable accuracy compared with the Monte Carlo simulation method.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1630-1643
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• 2023

The correct situation awareness (SA) of operators is important for managing nuclear power plants (NPPs), particularly in accident-related situations. Among the three levels of SA suggested by Ensley, Level 3 SA (i.e., projection of the future status of the situation) is challenging because of the complexity of NPPs as well as the uncertainty of accidents. Hence, several prediction methods using artificial intelligence techniques have been proposed to assist operators in accident prediction. However, these methods only predict short-term plant status (e.g., the status after a few minutes) and do not provide information regarding the uncertainty associated with the prediction. This paper proposes an algorithm that can predict the multivariate and long-term behavior of plant parameters for 2 h with 120 steps and provide the uncertainty of the prediction. The algorithm applies bidirectional long short-term memory and an attention mechanism, which enable the algorithm to predict the precise long-term trends of the parameters with high prediction accuracy. A conditional variational autoencoder was used to provide uncertainty information about the network prediction. The algorithm was trained, optimized, and validated using a compact nuclear simulator for a Westinghouse 900 MWe NPP.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.493-494
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• 2012

• Journal of Korean Society of Rural Planning
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• v.23 no.4
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• pp.153-168
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• 2017

The main objective of this study was to assess reference evapotranspiration based on multiple GCMs (General Circulation Models) and estimation methods. In this study, 10 GCMs based on the RCP (Representative Concentration Pathway) 4.5 scenario were used to estimate reference evapotranspiration. 54 ASOS (Automated Synoptic Observing System) data were constructed by statistical downscaling techniques. The meteorological variables of precipitation, maximum temperature and minimum temperature, relative humidity, wind speed, and solar radiation were produced using GCMs. For the past and future periods, we estimated reference evapotranspiration by GCMs and analyzed the statistical characteristics and analyzed its uncertainty. Five methods (BC: Blaney-Criddle, HS: Hargreaves-Samani, MK: Makkink, MS: Matt-Shuttleworth, and PM: Penman-Monteith) were selected to analyze the uncertainty by reference evapotranspiration estimation methods. We compared the uncertainty of reference evapotranspiration method by the variable expansion and analyzed which variables greatly influence reference evapotranspiration estimation. The posterior probabilities of five methods were estimated as BC: 0.1792, HS: 0.1775, MK: 0.2361, MS: 0.2054, and PM: 0.2018. The posterior probability indicated how well reference evapotranspiration estimated with 10 GCMs for five methods reflected the estimated reference evapotranspiration using the observed data. Through this study, we analyzed the overall characteristics of reference evapotranspiration according to GCMs and reference evapotranspiration estimation methods The results of this study might be used as a basic data for preparing the standard method of reference evapotranspiration to derive the water management method under climate change.