• Corrosion Science and Technology
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• v.8 no.5
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• pp.193-196
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• 2009

For the estimation of uncertainty in potentiodynamic polarization resistance measurement, the type A uncertainty was measured using type 316 stainless steel in an acidified NaCl solution. Sensitivity coefficients were determined for measurand such as scan rate of potential, temperature of solution, concentration of NaCl, concentration of HCl, surface roughness of specimen and flow rate of purging gas. Sensitivity coefficients were large for the measurand such as the scan rate of potential, temperature of solution and roughness of specimen. However, the sensitivity coefficients were not the major factors influencing the combined standard uncertainty of polarization resistance due to the low values of uncertainty in measurements of the measurands. A major influencing factor was the concentration of NaCl. The value of type A uncertainty was 1.1 times the value of type B uncertainty, and the combined standard uncertainty was 10.5 % of the average value of polarization resistance.

• Journal of the Korean Society of Tobacco Science
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• v.27 no.2
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• pp.226-234
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• 2005

The uncertainty of measurement in nitrate from burley leaf tobacco by continuous-flow analysis method was evaluated following internationally accepted guidelines. The sources of uncertainty associated with the analysis of nitrate were weight of standard and sample, purity of standard, dilution of standard solution, calibration curve, water content, etc. The calculation of uncertainty based on the GUM(Guide to the Expression of Uncertainty in Measurement) and EURACHEM/CITAC Guide. An expanded uncertainty was obtained by multiplying the combined standard uncertainty with a coverage factor (k) calculated from the effective degree of freedom. The concentration of nitrate from burley leaf tobacco was $2.09\%$ and the expanded uncertainty by multiplying by the coverage factor(k, 2.20) was $0.13\%\;at\;a\;95\%$ confidence level.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.860-865
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• 2021

A data-based model, such as an AAKR model is widely used for monitoring the drifts of sensors in nuclear power plants. However, since a training dataset and a test dataset for a data-based model cannot be constructed with the data from all the possible states, the model uncertainty cannot be good enough to represent the uncertainty of estimations. In fact, the errors of estimation grow much bigger if the incoming data come from inexperienced states. To overcome this limitation of the model uncertainty, a new measure of uncertainty for a data-based model is developed and the predicted uncertainty is introduced. The predicted uncertainty is defined in every estimation according to the incoming data. In this paper, the AAKR model is used as a data-based model. The predicted uncertainty is similar in magnitude to the model uncertainty when the estimation is made for the incoming data from the experienced states but it goes bigger otherwise. The characteristics of the predicted model uncertainty are studied and the usefulness is demonstrated with the pressure signals measured in the flow-loop system. It is expected that the predicted uncertainty can quite reduce the false alarm by using the variable threshold instead of the fixed threshold.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.321-344
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• 2017

Smart homes are the new generation of homes where pervasive computing is employed to make the lives of the residents more convenient. Human activity recognition (HAR) is a fundamental task in these environments. Since critical decisions will be made based on HAR results, accurate recognition of human activities with low uncertainty is of crucial importance. In this paper, a novel HAR method based on a difference of convex programming (DCP) problem is represented, which manages to handle uncertainty. For this purpose, given an input sensor data stream, a primary belief in each activity is calculated for the sensor events. Since the primary beliefs are calculated based on some abstractions, they naturally bear an amount of uncertainty. To mitigate the effect of the uncertainty, a DCP problem is defined and solved to yield secondary beliefs. In this procedure, the uncertainty stemming from a sensor event is alleviated by its neighboring sensor events in the input stream. The final activity inference is based on the secondary beliefs. The proposed method is evaluated using a well-known and publicly available dataset. It is compared to four HAR schemes, which are based on temporal probabilistic graphical models, and a convex optimization-based HAR procedure, as benchmarks. The proposed method outperforms the benchmarks, having an acceptable accuracy of 82.61%, and an average F-measure of 82.3%.

• Nuclear Engineering and Technology
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• v.37 no.3
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• pp.245-258
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• 2005

This paper addresses two types of uncertainty: stochastic uncertainty and subjective uncertainty in probabilistic accident consequence assessments. The off-site consequence assessment code OSCAAR has been applied to uncertainty and sensitivity analyses on the individual risks of early fatality and latent cancer fatality in the population outside the plant boundary due to a severe accident. A new stratified meteorological sampling scheme was successfully implemented into the trajectory model for atmospheric dispersion and the statistical variability of the probability distributions of the consequence was examined. A total of 65 uncertain input parameters was considered and 128 runs of OSCAAR with 144 meteorological sequences were performed in the parameter uncertainty analysis. The study provided the range of uncertainty for the expected values of individual risks of early and latent cancer fatality close to the site. In the sensitivity analyses, the correlation/regression measures were useful for identifying those input parameters whose uncertainty makes an important contribution to the overall uncertainty for the consequence. This could provide valuable insights into areas for further research aiming at reducing the uncertainties.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.790-802
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• 2022

Large-scale reactor simulation often requires the use of Monte Carlo calculation techniques to estimate important reactor parameters. One drawback of these Monte Carlo calculation techniques is they inevitably result in some uncertainty in calculated quantities. The present study includes parametric uncertainty quantification (UQ) and sensitivity analysis (SA) on the Advanced Test Reactor Critical (ATRC) facility housed at Idaho National Laboratory (INL) and addresses some complications due to Monte Carlo uncertainty when performing these analyses. This approach for UQ/SA includes consideration of Monte Carlo code uncertainty in computed sensitivities, consideration of uncertainty from directly measured parameters and a comparison of results obtained from brute-force Monte Carlo UQ versus UQ obtained from a surrogate model. These methodologies are applied to the uncertainty and sensitivity of k_eff for two sets of uncertain parameters involving fuel plate geometry and fuel plate composition. Results indicate that the less computationally-expensive method for uncertainty quantification involving a linear surrogate model provides accurate estimations for k_eff uncertainty and the Monte Carlo uncertainty in calculated k_eff values can have a large effect on computed linear model parameters for parameters with low influence on k_eff.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1791-1801
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• 2023

The multi-physics coupled methodologies that have been widely used to analyze the complex process occurring in nuclear reactors have also been used to the R&D of numerical reactors. The advancement in the field of computer technology has helped in the development of these methodologies. Herein, we report the integration of ADPRES code and RELAP5 code into the SALOME-ICoCo framework to form a multi-physics coupling platform. The platform exploits the supervisor architecture, serial mode, mesh one-to-one correspondence and explicit coupling methods during analysis, and the uncertainty analysis tool URANIE was used. The correctness of the platform was verified through the NEACRP-L-335 benchmark. The results obtained were in accordance with the reference values. The platform could be used to accurately determine the power peak. In addition, design margins could be gained post uncertainty analysis. The initial power, inlet coolant temperature and the mass flow of assembly property significantly influence reactor safety during the rod ejections accident (REA).

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.3
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• pp.19-25
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• 2004

Pitch measurements of 150 nm one-dimensional grating standards were carried out using a contact mode atomic force microscopy with a high resolution three-axis laser interferometer. This measurement technique was named as the 'nano-metrological AFM'. In the nano-metrological AFM, three laser interferometers were aligned precisely to the end of an AFM tip. Laser sources of the three-axis laser interferometer in the nano-metrological AFM were calibrated with an I$_2$ stabilized He-Ne laser at a wavelength of 633 nm. Therefore, the Abbe error was minimized and the result of the pitch measurement using the nano-metrological AFM could be used to directly measure the length standard. The uncertainty in the pitch measurement was estimated in accordance with the Guide to the Expression of Uncertainty in Measurement (GUM). The primary source of uncertainty in the pitch-measurements was derived from the repeatability of the pitch-measurements, and its value was about 0.186 nm. The average pitch value was 146.65 nm and the combined standard uncertainty was less than 0.262 nm. It is suggested that the metrological AFM is a useful tool for the nano-metrological standard calibration.

• Journal of Astronomy and Space Sciences
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• v.23 no.4
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• pp.405-414
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• 2006

Satellite formation flying has become a critical issue in the aerospace engineering because it is considered as an enabling technology for many space missions. Thus, many nonlinear control theories have been developed for the tracking problem of satellite formation flying, which include full-nonlinear dynamics, external disturbances and parameter uncertainty. In this study, nonlinear adaptive control law is developed using an adaptive backstepping technique to solve the relative position tracking problem of the satellite formation flying in the presence of mass uncertainty and the bounded external disturbance. Simulation studies are included to demonstrate the proposed controller performance. The proposed controller is shown to guarantee the system stability against the external bounded disturbances in the presence of mass uncertainty.

• Coupled systems mechanics
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• v.6 no.4
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• pp.487-499
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• 2017

This paper investigates the approximate solution bounds of radon diffusion equation in soil pore matrix coupled with uncertainty. These problems have been modeled by few researchers by considering the parameters as crisp, which may not give the correct essence of the uncertainty. Here, the interval uncertainties are handled by parametric form and solution of the relevant uncertain diffusion equation is found by using Galerkin's Method. The shape functions are taken as the linear combination of orthogonal polynomials which are generated based on the parametric form of the interval uncertainty. Uncertain bounds are computed and results are compared in special cases viz. with the crisp solution.