Uncertainty and sensitivity analyses for fuel temperature evaluations of U-Mo/Al plate-type dispersion fuel

Sweidan, Faris B.,Tahk, Young-wook,Yim, Jeong-Sik,Ryu, Ho Jin Elsevier 2018 Annals of nuclear energy Vol.120 No.-

<P><B>Abstract</B></P> <P>U-Mo/Al plate-type dispersion fuel is a promising candidate for the conversion of research reactor fuels from highly enriched to low-enriched uranium due to its high uranium density. The fuel temperature is a very important parameter, as it affects the performance of the fuel through various aspects, such as the formation of an interaction layer (IL) between the fuel particles and the matrix, swelling, and the release of fission gas. For these reasons, the fuel temperature as a function of the fission density was calculated for two representative heat flux profiles using best-estimate values and Monte Carlo simulations. Uncertainty and sensitivity analyses which utilized the uncertainties of the critical parameters were then conducted to determine the upper (maximum) and lower (minimum) bounds of the fuel temperature for the selected heat flux profiles. The uncertainty analysis used common uncertainty propagation approaches and a probabilistic sensitivity analysis (Monte Carlo simulation), randomly sampling numbers following a Gaussian distribution. Lastly, the Pearson correlation coefficient was used to identify the input uncertainties which influence the fuel temperature most in the sensitivity analysis. These analyses contribute to safety analyses and to the licensing process, as they are used in best-estimate approaches that apply realistic assumptions complemented with uncertainty analyses, such as the Best Estimate Plus Uncertainty (BEPU) approach.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Uncertainty and sensitivity analyses on U-Mo/Al dispersion fuel were conducted. </LI> <LI> Uncertainties of key parameters on the fuel temperature were evaluated. </LI> <LI> The fuel temperature as a function of the fission density was calculated. </LI> <LI> Pearson correlation coefficient was used to identify the influence of the input uncertainties. </LI> </UL> </P>

Real Option Analysis on Ship Investment Valuation

김치열,김재관,류동근 한국항해항만학회 2009 한국항해항만학회지 Vol.33 No.7

Recent collapse of shipping market right after unprecedent surge clearly demonstrates that shipping industry is extremely risky. Due to the volatile movements of the freight rates, investors tend to ask higher rate of return; higher required return reduces the total net present value of the investment project. For several decades, the Discounted Cash Flow(DCF hereafter) analysis has been the most frequently used valuation technique. However, the main problem of the DCF analysis is its assumption that the discount rate would stay the same during the project life. In other words, it usually does not address the decisions that managers have after a project has been accepted. The purpose of this study is investigate a new valuation method of investment: the Real Option Analysis(ROA hereafter) on ship investment. By replacing the existing valuation methods with the new one, the research will present a new perspective on investment with uncertainty. While uncertainty increases risk of investment and consequently discounts the value of it in the traditional feasibility analysis, in the ROA, a new valuation method which will be addressed in the research, uncertainty means some additional value of flexibility so that the tool can help investors produce more accurate decisions. Contrary to the DCF analysis, the ROA takes managerial flexibilities into account. In reality, capital budgeting and project management is typically dynamic, rather than static in nature. The ROA finds and assesses the values of managerial flexibilities or real options in the investments. The main structures of the research will be as follows: (1) overview of the ship investment project, (2) evaluation of the project by the Net Present Value analysis, (3) evaluation of the same project by the Real Option Analysis, (4) comparision of the two techniques. Recent collapse of shipping market right after unprecedent surge clearly demonstrates that shipping industry is extremely risky. Due to the volatile movements of the freight rates, investors tend to ask higher rate of return; higher required return reduces the total net present value of the investment project. For several decades, the Discounted Cash Flow(DCF hereafter) analysis has been the most frequently used valuation technique. However, the main problem of the DCF analysis is its assumption that the discount rate would stay the same during the project life. In other words, it usually does not address the decisions that managers have after a project has been accepted. The purpose of this study is investigate a new valuation method of investment: the Real Option Analysis(ROA hereafter) on ship investment. By replacing the existing valuation methods with the new one, the research will present a new perspective on investment with uncertainty. While uncertainty increases risk of investment and consequently discounts the value of it in the traditional feasibility analysis, in the ROA, a new valuation method which will be addressed in the research, uncertainty means some additional value of flexibility so that the tool can help investors produce more accurate decisions. Contrary to the DCF analysis, the ROA takes managerial flexibilities into account. In reality, capital budgeting and project management is typically dynamic, rather than static in nature. The ROA finds and assesses the values of managerial flexibilities or real options in the investments. The main structures of the research will be as follows: (1) overview of the ship investment project, (2) evaluation of the project by the Net Present Value analysis, (3) evaluation of the same project by the Real Option Analysis, (4) comparision of the two techniques.

The Explicit Treatment of Model Uncertainties in the Presence of Aleatory and Epistemic Parameter Uncertainties in Risk and Reliability Analysis

Ahn, Kwang-ll,Yang, Joon-Eon Korean Nuclear Society 2003 Nuclear Engineering and Technology Vol.35 No.1

In the risk and reliability analysis of complex technological systems, the primary concern of formal uncertainty analysis is to understand why uncertainties arise, and to evaluate how they impact the results of the analysis. In recent times, many of the uncertainty analyses have focused on parameters of the risk and reliability analysis models, whose values are uncertain in an aleatory or an epistemic way. As the field of parametric uncertainty analysis matures, however, more attention is being paid to the explicit treatment of uncertainties that are addressed in the predictive model itself as well as the accuracy of the predictive model. The essential steps for evaluating impacts of these model uncertainties in the presence of parameter uncertainties are to determine rigorously various sources of uncertainties to be addressed in an underlying model itself and in turn model parameters, based on our state-of-knowledge and relevant evidence. Answering clearly the question of how to characterize and treat explicitly the forgoing different sources of uncertainty is particularly important for practical aspects such as risk and reliability optimization of systems as well as more transparent risk information and decision-making under various uncertainties. The main purpose of this paper is to provide practical guidance for quantitatively treating various model uncertainties that would often be encountered in the risk and reliability modeling process of complex technological systems.

Uncertainty Analysis for Mean Flow Velocity and Discharge Measurements using Floats based on Large-Scale Experiments

안명희,윤병만,지운 대한토목학회 2019 KSCE JOURNAL OF CIVIL ENGINEERING Vol.23 No.8

The uncertainty of flow measurements obtained by the float method is evaluated following the international organization for standardization (ISO) 748 guideline. However, the standard uncertainty of an average flow rate has not been considered and the quantitative uncertainty has never been computed for flow measurements made using the float method. Therefore, in this study, a stream-scale experiment was performed to estimate the standard uncertainty of the mean flow velocity by considering the flow velocity uncertainty of floats. The results demonstrated that the standard uncertainty of the mean flow velocity measured by a surface float was 15.30%, while that measured by a rod float having a 50-cm draft was 11.05%. Through these results, the measurement uncertainty of discharge was evaluated according to the GUM (guide for the expression of uncertainty in measurement) method. The measurement uncertainty was then evaluated considering the standard uncertainty of the mean flow velocity. The measurement uncertainty of the discharge was increased by 3.4% as compared with that calculated without considering the standard uncertainty.

Uncertainty Quantification for the Thermal Analysis of the CANDU Spent Fuel Dry Storage Silo

Tae Gang Lee,Jae Jun Jeong,Tae Hyung Na 한국방사성폐기물학회 2023 한국방사성폐기물학회 학술논문요약집 Vol.21 No.2

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.

UNCERTAINTY AND SENSITIVITY STUDIES WITH THE PROBABILISTIC ACCIDENT CONSEQUENCE ASSESSMENT CODE OSCAAR

HOMMA TOSHIMITSU,TOMITA KENICHI,HATO SHINJI Korean Nuclear Society 2005 Nuclear Engineering and Technology Vol.37 No.3

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.

베이지안 접근법 기반 시뮬레이션 방법을 이용한 입력변수 및 근사모델 불확실성 하에서의 신뢰성 분석

안다운(Dawn An),원준호(Junho Won),김은정(Eunjeong Kim),최주호(Jooho Choi) 대한기계학회 2009 대한기계학회 춘추학술대회 Vol.2009 No.5

Reliability analysis is of great importance in product and process design. For this purpose, uncertainty analysis is needed, there are two types of uncertainties classification - according to amount of data, aleatory and epistemic uncertainty; - according to the subject, input variable and metamodel uncertainty. Aleatory uncertainty is irreducible and related with inherent physical randomness that is completely described by a suitable probability model. Epistemic uncertainty, on the other hand, results from the lack of knowledge such as insufficient data, and can be reduced by collecting more information. Input variable uncertainty is due to the uncertainty of needed variable for design, such as dimension tolerance, material propertyㆍload uncertainty. And lastly, the model uncertainty is due to the simplifying assumptions of response function. For practical reliability based design optimization, integration of input variable and metamodel uncertainty is required. This paper addresses Bayesian framework for the reliability analysis which can take account of both the input variable and metamodel uncertainties. Markov Chain Monte Carlo (MCMC) method is employed as a means for the simulation of posterior distribution. A couple of mathematical and engineering examples are used to demonstrate the proposed method.

Sensitivity and uncertainty analysis for ULOF of PGSFR using PAPIRUS

Kang, Sarah,Choi, ChiWoong,Ha, Kwi-Seok,Heo, Jaeseok Elsevier 2017 Annals of nuclear energy Vol.110 No.-

<P><B>Abstract</B></P> <P>In this research, sensitivity and uncertainty analyses for 23 parameters were performed for unprotected loss of flow (ULOF) for the prototype Gen-IV sodium-cooled fast reactor (PGSFR) by using the parallel computing platform integrated for uncertainty and sensitivity analysis (PAPIRUS). Based on the development of the phenomena and model identification and ranking table (PIRT), the relative importance of the parameters was confirmed through the sensitivity analysis. The objective of the global uncertainty analysis is to evaluate all safety parameters of the system in the combined phase space formed by the parameters and dependent variables. The uncertainty propagation was performed by mapping the uncertainty bands of the model parameters through the MARS-LMR to determine the distributions for the fuel centerline, cladding, and coolant temperatures. The results show that the uncertainty bands of the temperatures are below the melting point.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Sensitivity analysis for the ULOF of the PGSFR was performed using PAPIRUS. </LI> <LI> Uncertainty propagation was performed by mapping uncertainty bands of parameters. </LI> <LI> Distributions for fuel centerline, cladding and coolant temperatures were determined. </LI> </UL> </P>

Modeling metal-sediment interaction processes: Parameter sensitivity assessment and uncertainty analysis

Cho, Eunju,Arhonditsis, George B.,Khim, Jeehyeong,Chung, Sewoong,Heo, Tae-Young Elsevier 2016 Environmental modelling & software Vol.80 No.-

<P><B>Abstract</B></P> <P>Sensitivity and uncertainty analysis of contaminant fate and transport modeling have received considerable attention in the literature. In this study, our objective is to elucidate the uncertainty pertaining to micropollutant modeling in the sediment-water column interface. Our sensitivity analysis suggests that not only partitioning coefficients of metals but also critical stress values for cohesive sediment affect greatly the predictions of suspended sediment and metal concentrations. Bayesian Monte Carlo is used to quantify the propagation of parameter uncertainty through the model and obtain the posterior parameter probabilities. The delineation of periods related to different river flow regimes allowed optimizing the characterization of cohesive sediment parameters and effectively reducing the overall model uncertainty. We conclude by offering prescriptive guidelines about how Bayesian inference techniques can be integrated with contaminant modeling and improve the methodological foundation of uncertainty analysis.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Sensitivity and uncertainty analysis was performed for sediment-metal modeling. </LI> <LI> Suspended sediment predictions are sensitive to critical erosion stress. </LI> <LI> Sediment bed-water partitioning coefficient is critical for metal predictions. </LI> <LI> River flow dynamics affect contaminant fate and model parameter sensitivity. </LI> <LI> Strategies to improve uncertainty analysis of sediment-metal modeling are discussed. </LI> </UL> </P>

경제정책 불확실성이 장단기 국채 수익률에 미치는 영향 분석

박유현(Yuhyeon Bak),송철종(Cheol Jong Song) 한국자료분석학회 2023 Journal of the Korean Data Analysis Society Vol.25 No.5

본 연구는 국내와 해외의 경제정책 불확실성이 국내 장·단기 국채 수익률에 미치는 영향을 분석하였다. 우선 국내 경제정책불확실성이 장기와 단기의 국채 수익률에 미치는 영향을 분석하고, 해외 경제정책 불확실성에 대한 국내 경제정책 불확실성의 비율로 구성한 상대적 불확실성을 이용하였다. 해외 경제정책 불확실성으로 일본, 중국, 미국을 고려하였다. 또한 주성분분석을 통해 한국의 경제정책 불확실성을 한국 고유 요인과 주변국과의 공통 요인으로 구분하였다. 분석 결과는 다음과 같다. 첫째, 한국의 경제정책 불확실성은 장기와 단기 국채 수익률에 유의한 영향을 미치지 않았다. 둘째, 경제정책 불확실성 중 한국의 고유 요인은 단기 국채 수익률을 유의하게 상승시키는 것으로 나타났다. 셋째, 일본, 중국, 미국의 경제정책 불확실성은 한국의 단기국채 수익률을 상승시키는 것으로 나타났다. 넷째, 상대적 경제정책 불확실성을 이용한 경우, 한국의 경제정책 불확실성이 중국보다 상대적으로 커질 때 한국의 단기 국채수익률이 상승하였다. 이는 경제정책 불확실성을 국가 고유 요인과 공통 요인으로 구별해야 불확실성이 국채 수익률에 미치는 영향을 명확하게 이해할 수 있음을 시사한다. This study analyzes the impact of Korean and foreign economic policy uncertainty on Korean short-term and long-term government bond yield. First of all, the effect of domestic economic policy uncertainty on short-term and long-term government bond yields was analyzed, and then relative policy uncertainty, which was constructed as a ratio of Korean economic policy uncertainty to foreign economic policy uncertainty, was used. Japan, China, and the United States were considered for foreign economic policy uncertainty. In addition, through principal component analysis, Korea's economic policy uncertainty was divided into Korea-specific factors and common factors with Japan, China and USA. The analysis results are as follows. First, Korea's economic policy uncertainty did not have a significant effect on long-term and short-term government bond yields. Second, Korea's unique factor in economic policy uncertainty was found to significantly increase short-term government bond yields. Third, the economic policy uncertainties of Japan, China, and the US have been shown to increase Korea's short-term government bond yields. Fourth, in case of analyzing the effect of relative economic policy uncertainty, Korea's short-term government bond yield rises when Korea's economic policy uncertainty is relatively greater than China's. This implies that the impact of uncertainty on government bond yields can be clearly understood only when economic policy uncertainty is distinguished as a country-specific factor and a common factor.