• 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.53 no.9
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• pp.2816-2829
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• 2021

Decay heat residuals of spent nuclear fuel (SNF), i.e., the differences between calculations and measurements, were obtained previously for various spent fuel assemblies (SFA) using the Polaris module of the SCALE code system. In this paper, we compare decay heat residuals to their uncertainties, focusing on four PWRs and four BWRs. Uncertainties in nuclear data and model inputs are propagated stochastically through calculations using the SCALE/Sampler super-sequence. Total uncertainties could not explain the residuals of two SFAs measured at GE-Morris. The combined z-scores for all SFAs measured at the Clab facility could explain the resulting deviations. Nuclear-data-related uncertainties contribute more in the high burnup SFAs. Design and operational uncertainties tend to contribute more to the total uncertainties. Assembly burnup is a relevant variable as it correlates significantly with the SNF decay heat. Additionally, burnup uncertainty is a major contributor to decay heat uncertainty, and assumptions relating to these uncertainties are crucial. Propagation of nuclear data and design and operational uncertainties shows that the analyzed assemblies respond similarly with high correlation. The calculated decay heats are highly correlated in the PWRs and BWRs, whereas lower correlations were observed between decay heats of SFAs that differ in their burnups.

• Smart Structures and Systems
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• v.29 no.2
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• pp.321-336
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• 2022

Model uncertainty is a key factor that could influence the accuracy and reliability of numerical model-based analysis. It is necessary to acquire an appropriate updating approach which could search and determine the realistic model parameter values from measurements. In this paper, the Bayesian model updating theory combined with the transitional Markov chain Monte Carlo (TMCMC) method and K-means cluster analysis is utilized in the updating of the structural model parameters. Kriging and polynomial chaos expansion (PCE) are employed to generate surrogate models to reduce the computational burden in TMCMC. The selected updating approaches are applied to three structural examples with different complexity, including a two-storey frame, a ten-storey frame, and the national stadium model. These models stand for the low-dimensional linear model, the high-dimensional linear model, and the nonlinear model, respectively. The performances of updating in these three models are assessed in terms of the prediction uncertainty, numerical efforts, and prior information. This study also investigates the updating scenarios using the analytical approach and surrogate models. The uncertainty quantification in the Bayesian approach is further discussed to verify the validity and accuracy of the surrogate models. Finally, the advantages and limitations of the surrogate model-based updating approaches are discussed for different structural complexity. The possibility of utilizing the boosting algorithm as an ensemble learning method for improving the surrogate models is also presented.

• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.231-242
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• 2023

A novel combinatorial type-2 adaptive neuro-fuzzy inference system (T2-ANFIS) and robust proportional integral derivative (PID) control framework for intelligent vibration mitigation of uncertain structural system is introduced. The fuzzy logic controllers (FLCs), are designed independently of the mathematical model of the system. The type-1 FLCs, have a limited ability to reduce the effect of uncertainty, due to their fuzzy sets with a crisp degree of membership. In real applications, the consequent part of the fuzzy rules is uncertain. The type-2 FLCs, are robust to the fuzzy rules and the process parameters due to the fuzzy degree of membership functions and footprint of uncertainty (FOU). The adaptivity of the proposed method is provided with the optimum tuning of the parameters using the neural network training algorithms. In our approach, the PID control force is obtained using the generalized type-2 neuro-fuzzy in such a way that the stability and robustness of the controller are guaranteed. The robust performance and stability of the presented framework are demonstrated in a numerical study for an eleven-story seismically-excited building structure combined with an active tuned mass damper (ATMD). The results indicate that the introduced type-2 neuro-fuzzy PID control scheme is effective to attenuate plant states in the presence of the structured and unstructured uncertainties, compared to the conventional, type-1 FLC, type-2 FLC, and type-1 neuro-fuzzy PID controllers.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.7
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• pp.647-656
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• 2014

To supplement the ISO-GUM method for the evaluation of measurement uncertainty, a simulation program using the Monte Carlo method (MCM) was developed, and the MCM and GUM methods were compared. The results are as follows: (1) Even under a non-normal probability distribution of the measurand, MCM provides an accurate coverage interval; (2) Even if a probability distribution that emerged from combining a few non-normal distributions looks as normal, there are cases in which the actual distribution is not normal and the non-normality can be determined by the probability distribution of the combined variance; and (3) If type-A standard uncertainties are involved in the evaluation of measurement uncertainty, GUM generally offers an under-valued coverage interval. However, this problem can be solved by the Bayesian evaluation of type-A standard uncertainty. In this case, the effective degree of freedom for the combined variance is not required in the evaluation of expanded uncertainty, and the appropriate coverage factor for 95% level of confidence was determined to be 1.96.

• Korean Journal of Ecology and Environment
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• v.40 no.2
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• pp.193-200
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• 2007

The objective of this study was to estimate uncertainty of online TOC analyzer in water quality monitoring system. A procedure for the estimation of measurement uncertainty of total organic compounds (TOC) based on the ISO approach is presented. It is based on a mathematical model that involves 4 input parameters (standardization, sensitivity, solute effect and representativeness). In this study, a major problem in estimating the uncertainty of online TOC analyzer was the solute effect. It was strongly depends on organic materials. So homogeneity of the sample is the most important consideration. Modified concentration and combined standard uncertainty was $4.71{\pm}0.36$ mg $L^{-1}$ by model modified in this study.

• Journal of Korea Water Resources Association
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• v.42 no.10
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• pp.773-783
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• 2009

The effects of rainfall input uncertainty on predictions of stream flow are studied based extended GLUE (Generalized Likelihood Uncertainty Estimation) approach. The uncertainty in the rainfall data is implemented by systematic/non-systematic rainfall measurement analysis in Weida catchment, Germany. PDM (Probability Distribution Model) rainfall runoff model is selected for hydrological representation of the catchment. Using general correction procedure and DUE(Data Uncertainty Engine), feasible rainfall time series are generated. These series are applied to PDM in MC(Monte Carlo) and GLUE method; Posterior distributions of the model parameters are examined and behavioural model parameters are selected for simplified GLUE prediction of stream flow. All predictions are combined to develop ensemble prediction and 90 percentile of ensemble prediction, which are used to show the effects of uncertainty sources of input data and model parameters. The results show acceptable performances in all flow regime, except underestimation of the peak flows. These results are not definite proof of the effects of rainfall uncertainty on parameter estimation; however, extended GLUE approach in this study is a potential method which can include major uncertainty in the rainfall-runoff modelling.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.10 no.1
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• pp.126-146
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• 2000

To develop and evaluate formaldehyde measurement method using 2,4-dinitro-phenylhydrazine (2,4-DNPH) coated sampler and gas chromatography, laboratory test and field test were conducted. Results of this study are as follows. Limit of detection(LOD) of measurement methods, HPLC-UVD, GC-NPD and GC-FID, is $0.008{\mu}g/m{\ell}$ $0.060{\mu}g/m{\ell}$, $0.472{\mu}g/m{\ell}$ respectively. Coefficiency of measurement methods, HPLC-UVD, GC-NPD and GC-FID, is 0.008, 0.009, 0.020 respectively. Desorption efficiency of sep-pak xposure aldehyde sampler and sorbent sample tube is 1.05(range : 0.99 - 1.12), 1.02(range : 0.99 - 1.06) respectively. Samples of sorbent sample tube and sep-pak xposure aldehyde sampler turned out to be stored at refrigerator, according to storage test results. Measurement methods of HPLC-UVD, GC-NPD, GC-FID, according to results of precision for the combined sampling and analytical procedure, became acceptable to OSHA evaluation standard. Field test using exposure chamber met the NIOSH overall uncertainty recommendation(less than 25%). Overall uncertainty of Sepak-HPLC(UVD), Tube-GC(NPD), Tube-GC(FID) is 11.0% - 17.0%. Consequently gas chromatography(GC-NPD, GC-FID) and high performance liquid chromatography(EPA TO-11) using 2,4-DNPH coated sampler for formaldehyde measurement turned out to be suitable to measure personal formaldehyde exposure at workplaces.

• Journal of Soil and Groundwater Environment
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• v.18 no.5
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• pp.15-25
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• 2013

In this study, two kinds of soil-based proficiency testing materials (PTMs), NICE-012L and NICE-012R were prepared and certified for Benzen, Toluene, Etylbenzene and Xylene with evaluation of uncertainties. In order to analyse BTEX (Benzen Toluene Etylbenzene Xylene) for the candidate materials, GC/MS was used after pretreatment according to methods of soil analysis by Ministry of Environment. For the homogeneity test among bottles in terms of candidate materials, ISO 13528 and IUPAC Protocol were used and according to the result, both candidate materials showed sufficient homogeneity. Also, the stability test over the candidate materials was accessed according to the ISO Guide 35 by classifying short-term and long-term stability and the result showed that both candidate materials showed decent stability. The reference values of the two candidate materials depending on BTEX components were derived from the average of the 11 samples that were used for verification of the samples' homogeneity. Uncertainty of measurement was combined by uchar that was caused by a characteristic value, $u_{bb}$ that was caused by between-bottle homogeneity, and $u_{stab}$ that was caused by stability, and then combined uncertainty ($u_{PTM}$) was multiplied to the coverage factor (k) derived from the effective degree of freedom from each factor that leads to expanded uncertainty (U) in about 95% of confidence level. The proficiency testing materials developed through this study were supplied to National Institute of Environmental Research (NIER) and utilized as an external proficiency testing materials for evaluating analysis capacity of soil agencies with specialty in terms of soil analysis approved by Minister of Environment.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.1
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• pp.88-99
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• 2004

The purpose of this study is to observe the significance and symbolic meaning of fashion design which is combined with machines, and to develop excellent designs in aesthetic aspects. The method of this study analyzed the related documents and journal, fashion magazines. The results is as follows. The cyborg discourse and virtual human body in virtual world predict the existence of new human. In present times, up-to-date equipments such as wearable computer have begun to be built-in clothing based on technology, and these dress and ornaments influence on human's life gradually in practicality and ability. These equipments are divided as military affairs, medical treatment equipment, leisure, information access and communication, guard, and business assistance. And according to the kind of item, they are divided by headwear, clothing and accessory. The significance of clothing combined with machine is practical viewpoint, economical viewpoint and aesthetic viewpoint. And the symbolic meaning of these fashion combined machine with technology is dis-identity in digital society, dis-borderness between human and machine and the uncertainty of human being. Like this, the clothing which is combined with high-technology shapes its own unique and individual system. But, this must escape from the limit of medium system itself that is technology to become a future clothing for human, suggest new agenda about human and society, and confirm the human being's existence and identity continually.