In this study, data on indication errors within the range of 0 to 10 mm were measured using a dial gauge, which is widely used as a comparative measuring instrument in the field. Using Minitab, a statistical program, measurement conditions were determined during calibration of measuring instruments. Since the P value of the test statistic for the indication error is 0.000 to 0.003, the alternative hypothesis (H1) that no significant difference occurs due to a change in the measurement point at the significance level of 0.05 was adopted.

Bellows expansion joints enhance the displacement performance of piping systems owing to their unique geometrical features. However, structural uncertainties such as wall thinning in convolutions, a byproduct of the manufacturing process, can impair their structural integrity. This study addresses such issues by conducting a global sensitivity analysis to assess the impact of these uncertainties on the performance of bellows expansion joints under monotonic loading. Global sensitivity analysis, which examines main and nth order interaction effects, is computationally expensive. To mitigate this, we employed a surrogate model-based approach using an artificial neural network. This model demonstrated robust prediction capabilities, as evidenced by metrics such as the coefficient of determination. The sensitivity indices of the main effect for the 2-ply and 3-ply bellows at the sixth convolution were 0.3340 and 0.3233, respectively. The sensitivity index of the sixth convolution was larger than that of other convolutions because the maximum deformation of the bellows expansion joint under monotonic bending load occurs around it. Interestingly, the sensitivity index for the interaction effect was negligible (0.01%) compared to the main effect, suggesting minimal activity between uncertainty factors across convolutions. Notably, bellows expansion joints under repetitive loading exhibit more complex behaviors, with the initial leakage typically occurring at the convolution. Therefore, future studies should focus on the structural uncertainties of bellows expansion joints under cyclic loading and employ a surrogate model for comprehensive global sensitivity analysis.

This study was evaluated based on the items of KS B 6389. The study on the calculation of angular error and measurement uncertainty of HRc hardness measurement using statistical techniques using Rockwell measurement specimens with different hardness values ​​was analyzed, and the results were derived according to the change in the angle of the indenter part of the hardness tester and the specimen. As a result of the experiment, the test statistic P values ​​for angle changes such as 0°, 1°, and 2° were all 0.000 using the HRc 30 and 40 measurement specimens, so it was confirmed through the experiment that a significant difference occurred between them. In addition, the extended uncertainty value was calculated as 0.612 at the 95.45% confidence level, and the fact that the hardness test value came out smaller than the existing test value as the inclination angle increased was verified through experiments.

This paper reports an uncertainty analysis of quantitative visualization methodology for slug bubble dynamics in downward-facing nucleate boiling condition. Measurement of dynamics of slug bubble, i.e. departing speed, frequency, and diameter, is very important to predict safety margin of thermal systems in moving vehicle. By employing high speed visualization and post-processing, we quantitatively measured the volume and location of slug bubble, so that vapor generation rate and departing speed data were derived from their time differentiation. As a visualization methodology, its reliability was evaluated via uncertainty analysis. For 95% confidence interval, uncertainty of vapor generation rate and departing speed were 3% and 2%, respectively, and which were one order lower than standard deviation of those data.

콘크리트충전강관(Concrete Filled Steel Tube, CFST) 기둥 설계 시, 강관의 국부좌굴을 방지하기 위하여 강관두께 t에 대한 기둥외경 D의 크기를 제한하고 있다. 각각의 설계시방서에서 각기 다른 최대 D/t 값을 제안하고 있으며, 강재의 항복응력 fy, 또는 fy와 강재의 탄성계수 E의 식으로 표현된다. fy와 E의 불확실성을 고려할 경우, 최대 D/t 계산식을 포함한 한계 상태함수(limit state function)를 구성하여 CFST 단면의 국부좌굴에 대한 신뢰성지수(reliability index) β를 산정할 수 있다. 결정된 β는 사용된 최대 D/t 계산식에 따라 달라질 것이다. 이러한 신뢰성해석(reliability analysis) 결과의 가변성(variability)은 한계상태함수에 포함되는 전산모델 선택의 모호함(ambiguity)에서 기인한 것으로 모델링불확실성(modelling uncertainty)이라 한다. 모델링불확실성은 정보적불확실성(epistemic uncertainty)의 하나로 알려진 불명확성(non-specificity)으로 고려할 수 있으며, 불명확성은 가능성분포함수(possibility distribution function)를 사용하여 모델링할 수 있다. 본 연구에서는 다른 3개의 최대 D/t 계산식을 사용하여 주어진 CFST 단면의 국부좌굴에 대한 신뢰성해석을 수행하고 각각의 신뢰성지수를 계산할 것이다. 불명확한 신뢰성지수들은 가능성분포함수를 사용하여 모델링되고, 이로부터 확신정도(degree of confirmation)를 측정할 것이다. 확신정도는 신뢰성지수가 감소하면 증가한다. 결과적으로, 확신정도에 따라 재구성된 신뢰성지수들을 얻을 수 있으며, 허용 확신정도와 함께 CFST 단면의 국부좌굴에 대한 신뢰성지수의 결정이 가능하게 된다.

An isocratic high performance liquid chromatography (HPLC) method for routine analysis of deoxynivalenol in noodles was validated and estimated the measurement uncertainty. Noodles (dried noodle and ramyeon) were analyzed by HPLC-ultraviolet detection using immunoaffinity column for clean-up. The limits of detection (LOD) and quantification (LOQ) were 7.5 μg/kg and 18.8 μg/kg, respectively. The calibration curve showed a good linearity, with correlation coefficients r² of 0.9999 in the concentration range from 20 to 500 μg/kg. Recoveries and Repeatabilities expressed as coefficients of variation (CV) spiked with 200 and 500 μg/kg were 82 ± 2.7% and 87 ± 1.3% in dried noodle, and 97 ± 1.6% and 91 ± 12.0% in ramyeon, respectively. The uncertainty sources in measurement process were identified as sample weight, final volume, and sample concentration in extraction volume as well as components such as standard stock solution, working standard solution, 5 standard solutions, calibration curve,matrix, and instrument. Deoxynivalenol concentration and expanded uncertainty in two matrixes spiked with 200 μg/kg and 500 μg/kg were estimated to be 163.8 ± 52.1 and 435.2 ± 91.6 μg/kg for dried noodle, and 194.3 ± 33.0 and 453.2 ± 91.1 μg/kg for ramyeon using a coverage factor of two which gives a level of statistical confidence with approximately 95%. The most influential component among uncertainty sources was the recovery of matrix, followed by calibration curve.

Carbon contamination from the binder resin is an inherent problem with the metal powder injection molding process. Residual carbon in the W-Cu compacts has a strong impact on the thermal and electric properties. In this study, uncertainty was quantified to evaluate determination of carbon in a W-15%Cu MIM body by the combustition method. For a valid generalization about this evaluation, uncertainty scheme applied even to the repeatability as well as the uncertainty sources of each analyse step and quality appraisal sources. As a result, the concentration of carbon in the W-Cu part were measured as 0.062% with expanded uncertainty of 0.003% at 95% level. This evaluation example may be useful to uncertainty evaluation for other MIM products.

무딘 모양 물체의 대표적 형상인 정사각주의 후류에서의 와류 형성 분석을 위한 스트롤수 측정 실험에서 실험 방법 및 결과의 신뢰성 확보를 위하여 실험계획법과 불확실성 해석을 수행하였다. 스트롤수는 정사각주와 지면과의 간극을 변화시키면서 열선유속계를 사용하여 측정하였다. 정사각주가 지면과 충분히 떨어져 있다면, 후류의 어느 곳에서 스트롤수를 측정하더라도 신뢰할 수 있다. 그러나 정사각주가 지면과 가까워지면 와류가 부분적으로 약하게 형성되기 때문에 스트롤수는 후류의 일정한 영역에서만 측정할 수 있으며, 신뢰할 수 있는 값을 얻기가 쉽지 않다. 이에 요인배치법과 분산분석을 이용하여 5% 유의수준에서 신뢰할 수 있는 스트롤수 측정 구역을 확보하였다. 마지막으로 불확실성 해석을 실시하여 실험 환경 및 계측 장비로부터의 오차 요인을 분석하였으며 스트롤수에 대한 95% 신뢰구간을 구하였다.

The paper presents a new approach for analyzing mold growth risk in buildings, based on a mixed simulation approach with consideration of uncertainties in relevant building parameters. The approach is capable to predict and explain unexpected mold growth occurrences that would typically not show up in standard deterministic simulation. This study simulates the local environmental conditions at material surfaces in buildings by using a mix of standard simulation tools. By introducing uncertainties in relevant input parameters, this approach generates a statistical distribution of time aggregated mold growth conditions at a number of "trouble spots"in a specific building case. This distribution is then translated into an overall mold risk indicator. In addition, our method identifies those parameters whose uncertainty range has a dominant effect on an increase in mold risk. By thus identifying the critical influence of building components, building operation and maintenance factors on the increase in risk, appropriate actions during the building design and procurement process can be set up to address these risks.

Uncertainty evaluation was performed for the measurement of Volatile Organic Compounds(VOC) in indoor air. The analytical procedure and result were validated by evaluating every uncertainty source related to the measurement method. An easy approach for uncertainty evaluation for indoor VOC measurement was tested using relative standard uncertainty method which is simple in the evaluation of a measurement uncertainty in case of indoor VOC measurement. The measurement uncertainties of toluene, ethylbenzene, m+p-xylene, styrene and o-xylene in indoor air are obtained as less than or close to 10%, and those results were validated by using Gum-workbench uncertainty evaluation program. Based on the evaluation, uncertainties were found to come largely from two major sources, uncertainty related to the concentration of standard Tenax tube which was used for calibration in measurement, and the to air sampling process. This study could be used as a good example in evaluating uncertainties in the measurement of indoor-air VOC at buildings including a newly-built apartment.

교량의 손상추정을 위한 구조계 규명기법은 신호취득시스템 및 정보처리기술의 발전과 함께 최근에 많은 연구개발이 이루어지고 있다. 신경망기법이나 유전자 알고리즘과 같은 소프트컴퓨팅 기법은 뛰어난 패턴인식성능 때문에 손상추정 문제에 활발히 활용되고 있다. 본 연구에서는 모드계수를 활용한 신경망기법기반 손상추정을 수행하였으며, 신경망을 훈련시키기 위한 훈련패턴을 생성하는 해석모델에서의 불확실성을 효과적으로 고려할 수 있는 방법을 제시하였다. 해석모델의 불확실성 대하여 민감하지 않은 입력자료인 손상 전 후의 모드형상의 차 또는 모드형상의 비를 신경망의 입력자료로 활용하였다. 단 순보와 다주형교량에 대한 수치예제를 통하여 본 연구에서 제시한 기법의 타당성 및 적용성을 검증하였다.

In our previous study, we developed a CFD thermal analysis model for a CANDU spent fuel dry storage silo. The purpose of this model is to reasonably predict the thermal behavior within the silo, particularly Peak Cladding Temperature (PCT), from a safety perspective. The model was developed via two steps, considering optimal thermal analysis and computational efficiency. In the first step, we simplified the complex geometry of the storage basket, which stored 2,220 fuel rods, by replacing it with an equivalent heat conductor with effective thermal conductivity. Detailed CFD analysis results were utilized during this step. In the second step, we derived a thermal analysis model that realistically considered the design and heat transfer mechanisms within the silo. We developed an uncertainty quantification method rooted in the widely adopted Best Estimate Plus Uncertainty (BEPU) method in the nuclear industry. The primary objective of this method is to derive the 95/95 tolerance limits of uncertainty for critical analysis outcomes. We initiated by assessing the uncertainty associated with the CFD input mesh and the physical model applied in thermal analysis. And then, we identified key parameters related to the heat transfer mechanism in the silo, such as thermal conductivity, surface emissivity, viscosity, etc., and determined their mean values and Probability Density Functions (PDFs). Using these derived parameters, we generated CFD inputs for uncertainty quantification, following the principles of the 3rd order Wilks’ formula. By calculating inputs, A database could be constructed based on the results. And this comprehensive database allowed us not only to quantify uncertainty, but also to evaluate the most conservative estimates and assess the influence of parameters. Through the aforementioned method, we quantified the uncertainty and evaluated the most conservative estimates for both PCT and MCT. Additionally, we conducted a quantitative evaluation of parameter influences on both. The entire process from input generation to data analysis took a relatively short period of time, approximately 5 days, which shows that the developed method is efficient. In conclusion, our developed method is effective and efficient tool for quantifying uncertainty and gaining insights into the behavior of silo temperatures under various conditions.

After spent fuel is stored in a dry storage container, it becomes difficult to obtain information on the fuel’s characteristics. As a result, it is necessary to identify the characteristics of spent nuclear fuel in advance and secure the information necessary to establish delivery acceptance requirements for interim storage and disposal in the future. Therefore, it is necessary to evaluate the characteristics of spent fuel before loading dry storage casks. In order to prepare for the dry storage of spent fuel, information on the basic characteristics of the fuel is required. As part of this information, it is also necessary to establish calculation criteria for spent fuel burnup. Spent fuel burnup can be classified into three categories. The first is burnup evaluated using design codes (design burnup), the second is burnup measured by furnace instruments during power plant operation (actual burnup), and the third is burnup measured through measurement equipment (measured burnup). This paper describes a comparative evaluation of design burnup, actual burnup, and measured burnup for specific fuels (40 bundles).

Thermal analysis and safety assessment of spent fuel transport cask are mainly conducted using commercial Computational Fluid Dynamics (CFD) codes based on Finite Volume Method (FVM). The reliability and predictability of CFD codes have greatly been improved by the development in the computer systems, and are widely used to calculate heat flow in complex structures that cannot be analyzed theoretically. In the field of thermal analysis using the CFD code, it is important to clearly reflect the physical model of the transport cask, and a grid configuration suitable for the physical model is essential for accurate analysis. However, since there are no clear standard and guidelines for grid configuration and size, it is highly dependent on the user’s insight. Spatial discretization errors result from the use of finite-width grids and the approximation of the differential terms in the model equations by difference operators. Since the user usually cannot change the truncation error order of a given discretization scheme, spatial discretization errors can only be influenced by the provision of optimal grids. Therefore, it is necessary to quantify the spatial discretization errors caused by the grid. In the case of Orano TN’s NUHOMS® MP197 transport cask, considering four grids for two sets, the temperature uncertainty of the neutron shield, which has the lowest margin at the limit temperature among transport cask components, was quantified by applying 5-step procedure of the Grid Convergence Index (GCI) method for the uncertainty estimation presented in ASME V&V 20-2009. In the case of domestic spent nuclear fuel transport cask (KORAD21), neutron shield among the transport cask components has the lowest margin at the limited temperature. Accordingly, in this study, the temperature uncertainty of the neutron shield was quantified by applying GCI to three sets considering seven grids. As a result of the calculation, the uncertainty was less than ± 1°C, and the temperature of the neutron shield including the uncertainty was evaluated to be maintained below the limit temperature of 148°C.

This study aims to assess the impacts of COVID-19 on International Financial Reporting Standards (IFRS), because of the problems associated with changing and amending the financial reports according to the policies established based on the circumstances of the epidemic. The study sample targeted several international financial reports that were amended based on epidemic conditions. The revised financial reporting period provides standardized reporting procedures for financial transactions worldwide despite the pandemic. Therefore, IFRS has been used to reduce challenges in financial reporting by monitoring the duration of social distancing while reporting matters to eliminate confirmed uncertainty and judgment. After analyzing the data obtained through global search engines, the results conducted provided evidence that COVID-19 affects financial reporting in companies around the world. Therefore, companies face difficulty reporting finances based on the challenging environment that the pandemic represents. Besides, IFRS fair value measurements consider the prices that were predicted according to current market values. The contexts of the changing the standards by IFRS to curb the effects of the COVID19 financial reporting was attained through evaluation of the online files that were randomly selected and filtered to obtain valid data.

기존 기후변화 영향평가에서 발생하는 불확실성에 대한 연구들은 전체과정에서 총 불확실성과 그 전파에 대한 것보다 각 단계별 불확실성에 초점을 맞추어 연구가 진행되었다. 따라서 본 연구에서는 first-order Taylor series expansion에 기반하여 전망의 분산을 이용하는 Uncertainty Delta Method (UDM)를 제안하였으며, 이 방법은 각 단계별 불확실성 정량화와 증감정도, 단계별 불확실성 비율, 총 불확실성의 전파 과정 제시가 가능 하다. 본 연구에서는 기후변화 영향평가 과정의 단계별 불확실성 정량화와 전파과정 분석을 위해 미래 2030년부터 2059년까지를 대상으로 2개 배출 시나리오, 3개 GCM, 2개 상세화기법, 2개 수문모형을 사용하였다. 결과를 분석하면, UDM을 이용한 총 불확실성은 5.45(배출시나리오: 4.45, 상세화기법: 0.45, 상세화기법: 0.27, 수문모형: 0.28)이며, 배출 시나리오의 불확실성(4.45)이 가장 크게 나타났다. 불확실성은 각 단계를 거칠수록 증가하는 것으로 나타났다. 이러한 결과는 어떠한 배출시나리오를 선정하느냐에 따라 미래 수자원전망이 매우 달라질 수 있음을 의미한다. 다음으로 Hawkins and Sutton (2009)가 제안한 Fractional Uncertainty Method (FUM)을 이용한 기후변화 영향평가 불확실성 분석에서 가장 불확 실성이 큰 요인은 배출 시나리오(FUM 불확실성: 0.52)이며, 이 결과는 UDM 결과와 동일하게 나타났다. 따라서 이 연구에서 제안한 UDM은 기후 변화 영향평가에서의 불확실성 이해와 적합한 분석 및 미래 기후변화 대비 보다 나은 수자원 전망이 가능하도록 기여할 것으로 판단된다.