• Journal of the Korean Society of Tobacco Science
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• v.26 no.2 s.52
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• pp.168-178
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• 2004

Uncertainty of final measurement results considering main uncertainty sources being in nicotine of mainstream smoke was estimated. This study was accomplished by using the ISO 'The Guide to the Expression of Uncertainty in Measurement'. Using the two point re-calibration method, uncertainty for nicotine concentration was calculated considering the uncertainty sources of each step. The concentration and uncertainty of nicotine in mainstream smoke was estimated as $153.95{\pm}17.84\;{\mu}g/mL\;(0.77\pm0.089 mg/cig)$. The expanded uncertainty was $17.84 {\mu}g/mL(\pm0.089 mg/cig).$ The reported expanded uncertainty of the measurement is stated as the standard uncertainty of measurement multiplied by a coverage factor of 2, which for a normal distribution corresponds to a coverage probability of approximately $95\%$ The former expression indicates the conversion concentration into the sample.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.12
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• pp.1758-1765
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• 2003

Monte Carlo simulation(MC) method was used as an uncertainty assessment tool for gas flow measurement in this paper. Uncertainty sources for gas flow measurement were analyzed, and probability distribution characteristics of each source were discussed. Detailed MC methodology was described including the effect of the number of simulation. The uncertainty result was compared with that of the conventional sensitivity coefficient method, and it was revealed that the results were different from each other for this particular gas flow measurement case of which the modelling equation was nonlinear. The MC was comparatively simple, convenient and accurate as an uncertainty assessment method, especially in cases of complex, nonlinear measurement modelling equations. It was noted that the uncertainty assessment method should be selected carefully according to the mathematical characteristics of the measurement.

• 유체기계공업학회:학술대회논문집
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• 2002.12a
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• pp.378-386
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• 2002

Multi-path ultrasonic Sow measurement system uncertainty is determined by assigning an expected error of each component of flow measurement and then defining the total flow measurement uncertainty as square root of the sum of squared values of the individual error. Sources of uncertainty for flow measurement are geometry, transit time and velocity profile integration uncertainty. A theoretical uncertainty model for multi-path ultrasonic transit time flowmeter configured with parallel 5 chords, is derived from and calculated by dry calibration method.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.225-228
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• 2007

This paper presents a geostatistical methodology to model local uncertainty in spatial estimation of sediment grain size with high-resolution remote sensing imagery. Within a multi-Gaussian framework, the IKONOS imagery is used as local means both to estimate the grain size values and to model local uncertainty at unsample locations. A conditional cumulative distribution function (ccdf) at any locations is defined by mean and variance values which can be estimated by multi-Gaussian kriging with local means. Two ccdf statistics including condition variance and interquartile range are used here as measures of local uncertainty and are compared through a cross validation analysis. In addition to local uncertainty measures, the probabilities of not exceeding or exceeding any grain size value at any locations are retrieved and mapped from the local ccdf models. A case study of Baramarae beach, Korea is carried out to illustrate the potential of geostatistical uncertainty modeling.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.4
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• pp.665-672
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• 2010

This paper describes Monte Carlo Simulation(MCS) to assess the uncertainty of dynamic pressure calibrator and the expanded uncertainty results that were compared by GUM approximation and MCS. MCS uncertainties were computed using defining a domain of possible inputs, generating inputs randomly using probability distribution, performing a deterministic computation repeatedly and aggregating the results. It was revealed that the expanded uncertainty between GUM and MCS was different from each other. the expanded uncertainties were 0.5366%, 0.4856%, respectively. MCS is a suitable method for determining the uncertainty of simple and complex measurement systems. It should be more widely used and studied in measurement uncertainty calculations.

• Journal of Korean Tunnelling and Underground Space Association
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• v.5 no.4
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• pp.337-348
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• 2003

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. The blasting pressure was a function of detonation velocity, isentropic exponent, explosive density, Hugoniot parameters, and rock density. 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 the above mentioned 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. In other words, since rock property uncertainty is much larger than detonation velocity uncertainty the blasting pressure uncertainty is more influenced by the former than by the latter even though the detonation velocity is found to be the most influencing parameter on the blasting pressure.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.19 no.2
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• pp.130-139
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• 2023

This paper examines the quantification of uncertainty for welding residual stresses in dissimilar metal welds used in nuclear power plants. A mock-up of a dissimilar metal weld pipe, consisting of carbon and stainless steel pipes, was fabricated to measure the residual stress. A Round-Robin analysis was conducted by Korean institutions to assess the welding residual stress. The analysis was carried out in the second order, and the data obtained by each institution was evaluated based on the information provided. Using the Round-Robin results, the distribution of uncertainty in welding residual stresses among Korean institutions was evaluated. The quantification of uncertainty for Korean institutions was found to have a wider range compared to the distribution of welding residual stresses observed in overseas institutions. This study is considered useful in the establishment of comprehensive strategies for evaluating welding residual stress analysis methods used by domestic institutions.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.285-292
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• 2024

When calculating sonar detection probability, underwater acoustic uncertainty is assumed to be normal distributed with a standard deviation of 8 dB to 9 dB. However, due to the variability in experimental areas and ocean environmental conditions, predicting detection performance requires accounting for underwater acoustic uncertainty based on ocean experimental data. In this study, underwater acoustic uncertainty was determined using measured mid-frequency (2.3 kHz, 3 kHz) noise level and transmission loss data collected in the shallow water of the East Sea. After calculating the predictable probability of detection reflecting underwater acoustic uncertainty based on ocean experimental data, we compared it with the conventional detection probability results, as well as the predictable probability of detection results considering the uncertainty of the Rayleigh distribution and a negatively skewed distribution. As a result, we confirmed that differences in the detection area occur depending on each underwater acoustic uncertainty.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.825-833
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• 2013

An estimation of confidence intervals is essential to calculate uncertainty for greenhouse gases inventory. It is generally assumed that the population has a normal distribution for the confidence interval of parameters. However, in case data distribution is asymmetric, like nonnormal distribution or positively skewness distribution, the traditional estimation method of confidence intervals is not adequate. This study compares two estimation methods of confidence interval; parametric and non-parametric method for exponential distribution as an asymmetric distribution. In simulation study, coverage probability, confidence interval length, and relative bias for the evaluation of the computed confidence intervals. As a result, the chi-square method and the standardized t-bootstrap method are better methods in parametric methods and non-parametric methods respectively.

• Journal of Ship and Ocean Technology
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• v.9 no.1
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• pp.64-71
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• 2005

In probabilistic design, the challenge is to estimate the uncertainty propagation, since outputs of subsystems at lower levels could constitute inputs of other systems or at higher levels of the multilevel systems. Three uncertainty propagation estimation techniques are compared in this paper in terms of numerical efficiency and accuracy: root sum square (linearization), distribution-based moment approximation, and Taguchi-based integration. When applied to reliability-based design optimization (RBDO) under uncertainty, it is investigated which type of applications each method is best suitable for. Two nonlinear analytical examples and one vehicle crashworthiness for side-impact simulation example are employed to investigate the unique features of the presented techniques for uncertainty propagation. This study aims at helping potential users to identify appropriate techniques for their applications in the multilevel design.