• Journal of the Korea Safety Management & Science
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• v.13 no.2
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• pp.267-273
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• 2011

Since 'The Act on Private Investment of The Infrastructure' was established in 1994, private investment as well as government's investment in transport infrastructure has been active. However investment in transport infrastructure has more risks than others' due to uncertainty both in traffic volume and in construction cost. In the current appraisal procedure of deciding transportation infrastructure investment, instead of risk management, the sensitivity analysis considering only the changes of benefit, cost and social discount rate which are main factor affecting economic feasibility is carried out. Therefore the uncertainty of various factors affecting demand, cost and benefit are not considered in feasibility study. In this study the problems in current investment appraisal system were reviewed. Using Delphi technique the major factors which have high uncertainty in feasibility study were surveyed and then improvement plan was suggested in the respective of classic 4 step demand forecasting method. The range estimation technique was also mentioned to deal with the uncertainty of the future.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.6
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• pp.797-802
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• 2013

In this paper, using the mass/CG measurement equipment and the MOI measurement equipment developed in-house, Pitch MOI and Roll MOI of test specimen were measured and measurement uncertainties on MOI were studied. The possible factors of the measurement uncertainty that could affect accuracy of MOI measurement were mass, spring, frequency, and length measurement-related elements. The each combined standard uncertainty of pitch MOI and roll MOI was estimated from the uncertainties of the above various factors.

• Journal of Distribution Science
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• v.13 no.5
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• pp.71-82
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• 2015

Purpose - The purpose of this study is to investigate risk price implied from the pricing kernel of Korean stock distribution market. Recently, it is considered that the quantitative easing programs of major developed countries are contributing to a reduction in global uncertainty caused by the 2007~2009 financial crisis. If true, the risk premium as compensation for global systemic risk or economic uncertainty should show a decrease. We examine whether the risk price in the Korean stock distribution market has declined in recent years, and attempt to provide practical implications for investors to manage their portfolios more efficiently, as well as academic implications. Research design, data and methodology - To estimate the risk price, we adopt a non-parametric method; the minimum norm pricing kernel method under the LOP (Law of One Price) constraint. For the estimation, we use 17 industry sorted portfolios provided by the KRX (Korea Exchange). Additionally, the monthly returns of the 17 industry sorted portfolios, from July 2000 to June 2014, are utilized as data samples. We set 120 months (10 years) as the estimation window, and estimate the risk prices from July 2010 to June 2014 by month. Moreover, we analyze correlation between any of the two industry portfolios within the 17 industry portfolios to suggest further economic implications of the risk price we estimate. Results - According to our results, the risk price in the Korean stock distribution market shows a decline over the period of July 2010 to June 2014 with statistical significance. During the period of the declining risk price, the average correlation level between any of the two industry portfolios also shows a decrease, whereas the standard deviation of the average correlation shows an increase. The results imply that the amount of systematic risk in the Korea stock distribution market has decreased, whereas the amount of industry-specific risk has increased. It is one of the well known empirical results that correlation and uncertainty are positively correlated, therefore, the declining correlation may be the result of decreased global economic uncertainty. Meanwhile, less asset correlation enables investors to build portfolios with less systematic risk, therefore the investors require lower risk premiums for the efficient portfolio, resulting in the declining risk price. Conclusions - Our results may provide evidence of reduction in global systemic risk or economic uncertainty in the Korean stock distribution market. However, to defend the argument, further analysis should be done. For instance, the change of global uncertainty could be measured with funding costs in the global money market; subsequently, the relation between global uncertainty and the price of risk might be directly observable. In addition, as time goes by, observations of the risk price could be extended, enabling us to confirm the relation between the global uncertainty and the effect of quantitative easing. These topics are beyond our scope here, therefore we reserve them for future research.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.549-557
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• 2013

An flood inundation map is able to convey spatial distribution of inundation to a decision maker for flood risk management. A roughness coefficient with unclear values and a discharge obtained from the stage-discharge rating equation are key sources of uncertainty in flood inundation mapping by using a hydraulic model. Also, the uncertainty analysis needs an observation for the flood inundation, and satellite images is useful to obtain spatial distribution of flood. Accordingly, the objective of this study is to quantify uncertainty arising roughness and discharge in flood inundation mapping by using a hydraulic model and a satellite image. To perform this, flood inundations were simulated by HEC-RAS and terrain analysis, and ISODATA (Iterative Self-Organizing Data Analysis) was used to classify waterbody from Landsat 5TM imagery. The classified waterbody was used as an observation to calculate F-statistic (likelihood measure) in GLUE (Generalized Likelihood Uncertainty Estimation). The results from GLUE show that flood inundation areas are 74.59 $km^2$ for lower 5 % uncertainty bound and 151.95 $km^2$ for upper 95% uncertainty bound, respectively. The quantification of uncertainty in flood inundation mapping will play a significant role in realizing the efficient flood risk management.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.529-536
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• 2001

We investigate a surface-micromachined capacitive accelerometer with the grid-type electrodes surrounded by a perforated proof-mass frame. An electromechanical analysis of the microaccelerometer has been performed to obtain analytical formulae for natural frequency and output sensitivity response estimation. A set of prototype devices has been designed and fabricated based on a 4-mask surface-micromachining process. The resonant frequency of 5.8$\pm$0.17kHz and the detection sensitivity of 0.28$\pm$0.03mV/g have been measured from the fabricated devices. The parasitic capacitance of the detection circuit with a charge amplifier has been measured as 3.34$\pm$1.16pF. From the uncertainty analysis, we find that the major uncertainty in the natural frequency of the accelerometer comes from the micromachining error in the beam width patterning process. The major source of the sensitivity uncertainty includes uncertainty of the parasitic capacitance, the inter-electrode gap and the resonant frequency, contributing to the overall sensitivity uncertainty in the portions of 75%, 14% and 11%, respectively.

• Journal of Environmental Science International
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• v.20 no.3
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• pp.329-340
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• 2011

The probability concepts mainly used for rainfall or flood frequency analysis in water resources planning are the frequentist viewpoint that defines the probability as the limit of relative frequency, and the unknown parameters in probability model are considered as fixed constant numbers. Thus the probability is objective and the parameters have fixed values so that it is very difficult to specify probabilistically the uncertianty of these parameters. This study constructs the uncertainty evaluation model using Bayesian MCMC and Metropolis -Hastings algorithm for the uncertainty quantification of parameters of probability distribution in rainfall frequency analysis, and then from the application of Bayesian MCMC and Metropolis- Hastings algorithm, the statistical properties and uncertainty intervals of parameters of probability distribution can be quantified in the estimation of probability rainfall so that the basis for the framework configuration can be provided that can specify the uncertainty and risk in flood risk assessment and decision-making process.

• Nuclear Engineering and Technology
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• v.51 no.4
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• pp.968-976
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• 2019

This paper presents a number of verification case studies for a recently developed sensitivity/uncertainty code package. The code package, ROMUSE (Reduced Order Modeling based Uncertainty/Sensitivity Estimator) is an effort to provide an analysis tool to be used in conjunction with reactor core simulators, in particular the Virtual Environment for Reactor Applications (VERA) core simulator. ROMUSE has been written in C++ and is currently capable of performing various types of parameter perturbations and associated sensitivity analysis, uncertainty quantification, surrogate model construction and subspace analysis. The current version 2.0 has the capability to interface with the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) code, which gives ROMUSE access to the various algorithms implemented within DAKOTA, most importantly model calibration. The verification study is performed via two basic problems and two reactor physics models. The first problem is used to verify the ROMUSE single physics gradient-based range finding algorithm capability using an abstract quadratic model. The second problem is the Brusselator problem, which is a coupled problem representative of multi-physics problems. This problem is used to test the capability of constructing surrogates via ROMUSE-DAKOTA. Finally, light water reactor pin cell and sodium-cooled fast reactor fuel assembly problems are simulated via SCALE 6.1 to test ROMUSE capability for uncertainty quantification and sensitivity analysis purposes.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.20 no.1
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• pp.23-32
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• 2022

Pyroprocessing is a promising technology for managing spent nuclear fuel. The nuclear material accounting of feed material is a challenging issue in safeguarding pyroprocessing facilities. The input material in pyroprocessing is in a solid-state, unlike the solution state in an input accountability tank used in conventional wet-type reprocessing. To reduce the uncertainty of the input material accounting, a double-stage homogenization process is proposed in considering the process throughput, remote controllability, and remote maintenance of an engineering-scale pyroprocessing facility. This study tests two types of mixing equipment in the proposed double-stage homogenization process using surrogate materials. The expected heterogeneity and accounting uncertainty of Pu are calculated based on the surrogate test results. The heterogeneity of Pu was 0.584% obtained from Pressurized Water Reactor (PWR) spent fuel of 59 WGd/tU when the relative standard deviation of the mass ratio, tested from the surrogate powder, is 1%. The uncertainty of the Pu accounting can be lower than 1% when the uncertainty of the spent fuel mass charged into the first mixers is 2%, and the uncertainty of the first sampling mass is 5%.

• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2850-2858
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• 2024

Amidst the uncertainties of climate policy, investing in nuclear energy technology emerges as a sustainable strategy, fostering innovation in a critical sector, while simultaneously addressing urgent environmental concerns and managing budgetary dynamics. Our investigation inspects the asymmetric influence of climate policy uncertainty on nuclear energy technology in the top 10 nations with the highest nuclear energy R&D budgets (Germany, Japan, China, France, USA, UK, India, South Korea, Russia, and Canada). Previous studies adopted panel data methods to evaluate the linkage between climate policy uncertainty and nuclear energy technology. Nonetheless, these investigations overlooked the variability in this association across various countries. Conversely, this investigation introduces an innovative tool, 'Quantile-on-Quantile' to probe this connection merely for every economy. This methodology concedes for a more accurate evaluation, offering a holistic global perspective and delivering tailored insights for individual countries. The findings uncover that climate policy uncertainty significantly reduces nuclear energy technology budgets across multiple quantiles in most selected economies. Additionally, our results highlight the asymmetries in the correlations between our variables across the nations. These findings stress the need for policymakers to conduct thorough assessments and skillfully manage climate policy uncertainty and nuclear energy budgets.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.12
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• pp.1116-1123
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• 2015

The lifetime of a geostationary satellite depends on the residual propellant amount and therefore the precise residual propellant gauging is very important for the mitigation of economic loss arised from premature removal of satellite from its orbit, satellites replacement planning, slot management and so on. In this paper, the thermal mass method and its uncertainty are described. The residual propellant analysis of a geostationary satellite is simulated based on the KOREASAT data and the uncertainty of thermal mass method is calculated by using the Monte Carlo method. The results of this study show the importance parameter of estimation residual propellant using the thermal mass method.