• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.68-72
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• 1997

This paper presents the design and the evaluation of the 6-component force/moment calibration machine which h a s t h e maximum capacities of 500 N in forces and 50 Nm in moments. This calibration machine consists of body. fixture. force generating system, moment generating system. The expanded uncertainty of the calibration machine is evaluated by calculating the A type uncertainty. $U_A$ and B type uncertainty, $U_B$. The evaluation results. this system has the expanded uncertainty of less than $2{\times}10^[-2]$ in respective force and moment components.

• Applied Science and Convergence Technology
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• v.23 no.3
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• pp.103-112
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• 2014

The Korea Research Institute of Standards and Science (KRISS) has three major vacuum systems: an ultrasonic interferometer manometer (UIM; Section II, Figs. 1 and 2) for a low vacuum, a static expansion system (SES; Section III, Figs. 3 and 4) for a medium vacuum, and an orifice-type dynamic expansion system (DES, Section IV, Figs. 5 and 6) for high and ultra-high vacuum systems. For each system, explicit measurement model equations with multiple variables are given. According to ISO standards, all of these system variable errors were used to calculate the expanded uncertainty (U). For each system, the expanded uncertainties (k = 1, confidence level = 95%) and relative expanded uncertainty (expanded uncertainty/generated pressure) levels are summarized in Table 4. Within the uncertainty limits, our bilateral and key comparisons [CCM.P-K4 (10 Pa to 1 kPa)] are extensive and in good agreement with those of other nations (Fig. 8 and Table 5).

• Journal of the Korean Society of Industry Convergence
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• v.26 no.3
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• pp.401-409
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• 2023

Oscillating water column (OWC) type wave power generator system is a power generation system that uses wave energy, a sustainable and renewable energy source. Irregular cycles and wave heights act as factors that make it difficult to secure generation efficiency of the wave power generator system. Recently, research for improving power generation efficiency is being conducted by applying digital twin technology to OWC type wave energy converter system. However, digital twin using sensor data can predict erroneous performance due to uncertainty in the sensor data. Therefore, this study proposes an uncertainty analysis method for sensor data which is used in digital twin to secure the reliability of digital twin prediction results. Uncertainty quantification considering sensor data characteristics and future uncertainty information according to uncertainty propagation were derived mathematically, and confidence interval estimation was performed based on the proposed method.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.229-233
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• 2003

Theodolite measurement system is non-contacted 3-dimensional measurement system. The system accuracy is 0.5 mm or better for distance 0 ~ 100m. And the system is used for a product of middle and large scale. This study is performed for the measurement uncertainty of the system. We could know that the main uncertainty factors are temperature, illumination and skill. And, we perform the study for the effect according to the height difference of scale bar. And, we calculated the measurement uncertainty with those factors.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1845-1853
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• 2024

The setpoint of the reactor trip system shall be set to consider the measurement uncertainty of the instrument channel and provide a reasonable and sufficient margin between the analytical limit and the trip setpoint. A comparative analysis was conducted to find out an appropriate uncertainty combination method through an example problem. The four methods were evaluated; 1) ISA-67.04.01 method, 2) the GUM95 method, 3) the modified GUM method developed by Fotowicz, and 4) the modified IEC61888 method proposed by authors for the pressure instrument channel presented in ISA-RP67.04.02 example. The appropriateness of each method was validated by comparing it with the result of Monte Carlo simulation. As a result of the evaluation, all methods are appropriate when all measurement uncertainty elements are normally distributed as expected. But ISA-67.04 method and GUM95 method overestimated the channel uncertainty if there is a dominant input element with rectangular distribution among the uncertainty input elements. Modified GUM95 methods developed by Fotowicz and modified IEC61888 method by authors are able to produce almost the same level of channel uncertainty as the Monte Carlo method, even when there is a dominant rectangular distribution among the uncertainty components, without computer-assisted simulations.

• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.139-141
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• 2005

For the reliable evaluation of the distribution and power transformer no-load loss measurement, measurement uncertainty of the transformer measuring system, consisted of current transformer, potential transformer and power metering equipment is required. In this paper, we describe the uncertainty of transformer measuring system based on ANSI/IEEE C57.12.90.

• Structural Engineering and Mechanics
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• v.53 no.4
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• pp.819-831
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• 2015

In this paper, we propose a new method for taking into account uncertainties based on the projection on polynomial chaos. The new approach is used to determine the dynamic response of a spur gear system with uncertainty associated to gear system parameters and this uncertainty must be considered in the analysis of the dynamic behavior of this system. The simulation results are obtained by the polynomial chaos approach for dynamic analysis under uncertainty. The proposed method is an efficient probabilistic tool for uncertainty propagation. It was found to be an interesting alternative to the parametric studies. The polynomial chaos results are compared with Monte Carlo simulations.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.161-167
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• 2021

This paper presents the method to quantitatively evaluate the uncertainty of the semi-empirical Bidirectional Reflectance Distribution Function (BRDF) model for Himawari-8/AHI. The uncertainty of BRDF modeling was affected by various issues such as assumption of model and number of observations, thus, it is difficult that evaluating the performance of BRDF modeling using simple uncertainty equations. Therefore, in this paper, Monte-Carlo method, which is most dependable method to analyze dynamic complex systems through iterative simulation, was used. The 1,000 input datasets for analyzing the uncertainty of BRDF modeling were generated using the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) Radiative Transfer Model (RTM) simulation with MODerate Resolution Imaging Spectroradiometer (MODIS) BRDF product. Then, we randomly selected data according to the number of observations from 4 to 35 in the input dataset and performed BRDF modeling using them. Finally, the uncertainty was calculated by comparing reproduced surface reflectance through the BRDF model and simulated surface reflectance using 6S RTM and expressed as bias and root-mean-square-error (RMSE). The bias was negative for all observations and channels, but was very small within 0.01. RMSE showed a tendency to decrease as the number of observations increased, and showed a stable value within 0.05 in all channels. In addition, our results show that when the viewing zenith angle is 40° or more, the RMSE tends to increase slightly. This information can be utilized in the uncertainty analysis of subsequently retrieved geophysical variables.

• Journal of Power System Engineering
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• v.4 no.3
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• pp.72-80
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• 2000

In order to design a stable robust controller, nominal model, and the upper bound about the uncertainty which is the error of the model are needed. The problem to estimate the nominal model of controlled system and the upper bound of uncertainty at the same time is called robust identification. When the nominal model of controlled system and the upper bound of uncertainty in relation to robust identification are given, the evaluation of the validity of the model and the upper bound makes it possible to distinguish whether there is a model which explains observation data including disturbance among the model set. This paper suggests a method to identity the uncertainty which removes disturbance and expounds observation data by giving a probable postulation and plural data set to disturbance. It also examines the suggested method through a numerical computation simulation and validates its effectiveness.

• Journal of Korean Society for Atmospheric Environment
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• v.30 no.1
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• pp.26-36
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• 2014

The uncertainty assessment is important to improve the reliability of emission inventory data. The DARS (Data Attribute Rating System) have recommended as the uncertainty assessment technic of emission inventory by U.S. EPA (Environmental Protection Agency) EIIP (Emission Inventory Improvement Program). The DARS score is based on the perceived quality of the emission factor and activity data. Scores are assigned to four attributes; measurement/method, source specificity, spatial congruity and temporal congruity. The resulting emission factor and activity rate scores are combined to arrive at an overall confidence rating for the inventory. So DARS is believed to be a useful tool and may provide more information about inventories than the usual qualitative grading procedures (e.g. A through E). In this study, the uncertainty assessment for 2009 CAPSS (Clean Air Policy Support System) emission inventory is conducted by DARS. According to the result of this uncertainty assessment, the uncertainty for fugitive dust emission data is higher than other sources, the uncertainty of emission factor for surface coating is the highest value, and the uncertainty of activity data for motor cycle is the highest value. Also it is analysed that the improvement of uncertainty for activity data is as much important as the improvement for emission factor to upgrade the reliability of CAPSS emission inventory.