• Proceedings of the Korea Concrete Institute Conference
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• 1998.10b
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• pp.656-661
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• 1998

This paper presents a method of statistical analysis and sensitivity analysis of creep and shrinkage effects in PSC box girder bridges. The statistical and sensitivity analyses are performed by using the numerical simulation of Latin Hypercube sampling. For each sample, the time-dependent structural analysis is performed to produce response data, which are then statistically analyzed. The probabilistic prediction of the confidence limits on long-term effects of creep and shrinkage is then expressed. Three measures are examined to quantify the sensitivity of the outputs to each of the input variables. These are rank correlation coefficient(RCC), partial rank correlation coefficient(PRCC) and standardized rank regression coefficient(SRRC) computed on the ranks of the observations. Probability band widens with time, which indicates an increase of prediction uncertainty with time. The creep model uncertainty factor and the relative humidity appear as the most dominant factors with regard to the model output uncertainty.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1067-1078
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• 2018

Water resources projection typically consists of several stages including emission scenarios, global circulation models (GCMs), downscaling techniques, and hydrological models, and each stage is a source of total uncertainty in water resources projection. Several studies proposed methods to quantify the relative contribution of each stage to total uncertainty, and we call such analysis uncertainty decomposition. Uncertainty decomposition enables us to investigate the stages yielding large uncertainties and to establish the uncertainty reduction plan that reflects them. Interactions between stages is one of the important issues to be considered in uncertainty decomposition. This study suggests a new uncertainty decomposition method considering interaction effect. The proposed method has an advantage of decomposing the total uncertainty to the uncertainty from each stage considering both the main and interactions effects. We apply the proposed method to streamflow projection for Chungju Dam basin. The results show that the uncertainties from the main effects are larger than the uncertainties from interaction effects in both summer and winter. Using the proposed uncertainty decomposition method, we show that the GCM stage is the largest source of the total uncertainty in summer and the downscaling technique stage is the one in winter among the following four stages: emission scenarios, GCMs, downscaling techniques, and hydrological models.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.2
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• pp.331-341
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• 2018

Hazardous air pollutants(HAPs) in the atmosphere are regulated as major air pollutants in Korea by the Air Pollution Control Act. In order to manage and control HAPs, accurate standards, which are traceable to the International System of Units(SI), are required. In this study, primary standard gas mixtures(PSMs) of volatile organic compounds(VOCs) which are specified as HAPs were developed at $1{\mu}mol/mol$ levels. The selected fourteen VOCs include Benzene, Toluene, Ethylbenzene, m-Xylene, Styrene, o-Xylene, Chloroform, 1,1,2-Trichloroethane, Trichloroethylene, Tetrachloroethylene, 1,1-Dichloroethane, Carbon tetrachloride, 1,3-Butadiene, and Dichloromethane. The HAPs PSMs were gravimetrically prepared in aluminum cylinders and their consistency was verified within the relative expanded uncertainty of 0.71% (k=2). Potential adsorption loss onto the internal surface of cylinders was estimated by cylinder-to-cylinder division method. No adsorption loss was observed within the uncerainty of 0.53%. The long-term stability of the HAPs PSMs was evaluated comparing with freshly prepared HAPs PSMs. The HAPs PSMs were stable for one year within the uncertainty of 0.38%. The final uncertainty of the PSMs was determined by combining the preparation uncertainty, verification uncertainty, and stability uncertainty. Finally, traceable and stable HAPs PSMs at $1{\mu}mol/mol$ levels were developed with the uncertainty of less than 0.76% in high-pressure aluminum cylinders.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.3
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• pp.198-206
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• 2009

This paper presents the reduction of the positional uncertainty of an ultrasonic sensor ring with overlapped beam pattern for the efficient obstacle detection of a mobile robot. Basically, it is assumed that a relatively small number of inexpensive low directivity ultrasonic sensors are installed at regular spacings along the side of a circular mobile robot with their beams overlapped. First, for both single and double obstacles, we show that the positional uncertainty inherent to an ultrasonic sensor can be reduced using the overlapped beam pattern, and also quantify the relative improvement in positional uncertainty. Second, given measured distance data from one or two ultrasonic sensors, we devise the geometric method to determine the position of an obstacle with respect to the center of a mobile robot. Third, we examine and compare existing ultrasonic sensor models, including Gaussian distribution, parabolic distribution, uniform distribution, and impulse, and then build the sensor model of overlapped ultrasonic sensors, adequate for obstacle detection in terms of positional uncertainty and computational requirement. Finally, through experiments using our prototype ultrasonic sensor ring, the validity of overlapped beam pattern for reduced positional uncertainty and efficient obstacle detection is demonstrated.

• Journal of the Korean Society for information Management
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• v.36 no.2
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• pp.175-199
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• 2019

Uncertainty means incomplete stages of knowledge of propositions due to the lack of consensus of information and existing knowledge. As the amount of academic literature increases exponentially over time, new knowledge is discovered as research develops. Although the flow of time may be an important factor to identify patterns of uncertainty in scientific knowledge, existing studies have only identified the nature of uncertainty based on the frequency in a particular discipline, and they did not take into consideration of the flow of time. Therefore, in this study, we identify and analyze the uncertainty words that indicate uncertainty in the scientific literature and investigate the stream of knowledge. We examine the pattern of biomedical knowledge such as representative entity pairs, predicate types, and entities over time. We also perform the significance testing using linear regression analysis. Seven pairs out of 17 entity pairs show the significant decrease pattern statistically and all 10 representative predicates decrease significantly over time. We analyze the relative importance of representative entities by year and identify entities that display a significant rising and falling pattern.

• Journal of the Korean Magnetic Resonance Society
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• v.24 no.2
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• pp.53-58
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• 2020

Free radicals including reactive oxygen species (ROS) are important chemicals in the research area of biology, pharmaceutical, medical, and environmental science as well as human health risk assessment as they are highly involved in diverse metabolism and toxicity mechanisms through chemical reactions with various components of living bodies. Electron spin resonance (ESR) spectroscopy is a powerful tool for detecting and quantifying those radicals in biological environments. In this work we observed the ESR signal of 2,2,6,6-Tetra-methyl piperidine 1-oxyl (TEMPO) in aqueous solution at various concentrations to estimate the uncertainty factors arising from the experimental conditions and signal treatment methods. As the sample position highly influences the signal intensity, dual ESR tube geometry (consists of a detachable sample tube and a position fixed external tube) was adopted. This type of measurement geometry allowed to get the relative uncertainty of signal intensity lower than 1% when triple measurements are averaged. Linear dependence of signal intensity on the TEMPO concentration, which is required for the quantification of unknown sample, could be obtained over a concentration range of ~10³ by optimizing the signal treatment method depending on the concentration range.

• Journal of the Korean Solar Energy Society
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• v.30 no.4
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• pp.79-85
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• 2010

The uncertainty in WindCube LIDAR measurements, which are specific to wind profiling at less than 200m above ground levelin wind resource assessments, was analyzed focusing on the error caused by its volume sampling principle. A two-month SODAR measurement campaign conducted in an urban environment was adopted as the reference wind profile assuming that various atmospheric boundary layer shapes had been captured. The measurement error of LIDAR at a height z was defined as the difference in the wind speeds between the SODAR reference data, which was assumed to be a virtually true value, and the numerically averaged wind speed for a sampling volume height interval of $z{\pm}12.5m$. The pattern of uncertainty in the measurement was found to have a maximum in the lower part of the atmospheric boundary layer and decreased with increasing height. It was also found that the relative standard deviations of the wind speed error ratios were 6.98, 2.70 and 1.12% at the heights of 50, 100 and 150m above ground level, respectively.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.10 s.103
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• pp.1148-1159
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• 2005

In this paper, the various uncertainties generated in an optical disk drive (ODD) and the robust servo designs considering the uncertainties are studied. First, the brief introduction an ODD and the servo error tolerance of it are discussed. Then, the classifications of uncertainty and the concept of relative stability are introduced. Considering the uncertainty of an ODD, two robust control approaches are applied: (i) mixed sensitivity approach in H$\infty$ control theory for unstructured uncertainty, (ii) QFT for structured uncertainty Finally, the designed controllers are realized by DSP, and these controllers are applied to a commercial DVD-ROM drive. From these experiments, we prove that the designed robust controllers have more good disturbance rejection performance and robustness when it is compared to the conventional lead-lag controller.

• The KSFM Journal of Fluid Machinery
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• v.17 no.4
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• pp.5-10
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• 2014

It is possible for the nation's largest flowmeter calibration system in K-water to calibrate flow rate up to $2,700m^3/h$ and diameter 800mm. However, the calibration and measurement capability of K-water's system is not satisfied in comparison with other developed countries. In this study, we find the dominant factors related to the uncertainty of weight and time measurement for gravimetric flowmeter calibration system. As a results of improving the system, the combined standard uncertainty has been improved $1.099{\times}10^{-3}$ to $2.332{\times}10^{-4}$. So calibration and measurement capability got 0.08 percent of the relative expanded uncertainty for maximum flow rate using the coverage factor(k=2).

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4534-4550
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• 2022

Integrated severe accident codes should be capable of simulating not only specific physical phenomena but also entire plant behaviors, and in a sufficiently fast time. However, significant uncertainty may exist owing to the numerous parametric models and interactions among the various phenomena. The primary objectives of this study are to present best-practice uncertainty and sensitivity analysis results regarding the evolutions of severe accidents (SAs) and fission product source terms and to determine the effects of mitigation measures on them, as expected during a short-term station blackout (STSBO) of a reference pressurized water reactor (optimized power reactor (OPR)1000). Three reference scenarios related to the STSBO accident are considered: one base and two mitigation scenarios, and the impacts of dedicated severe accident mitigation (SAM) actions on the results of interest are analyzed (such as flammable gas generation). The uncertainties are quantified based on a random set of Monte Carlo samples per case scenario. The relative importance values of the uncertain input parameters to the results of interest are quantitatively evaluated through a relevant sensitivity/importance analysis.