• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.123-132
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• 2014

Inflation uncertainty is known to have deleterious effects on facilities investment by disturbing the corporate decision on the opportunity cost of investment. In this paper, we test the validity of this hypothesis in Korea by estimating the inflation uncertainty with both a time-varing parameter model with GARCH disturbances and the relative price volatility and then, estimate the facilities investment equation which includes those uncertainty indicators. The uncertainty indexes estimated by the above-mentioned methods continue to fluctuate even after the inflation rate has dropped dramatically reflecting the structural changes of Korea's economy since the financial crisis in 1997. As a result of estimation of the investment equation by both OLS and GMM, we find the inflation uncertainty has a negative effect on facilities investment with a statistical significance. Moreover, by means of Markov-switching regression model utilized to verify the non-linearity of this relationship, we draw a conclusion that this negative effect of inflation uncertainty heightens asymmetrically during the downturn periods of business cycle.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.7
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• pp.625-638
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• 2014

In this study, the uncertainties in the critical flow functions (CFFs) calculated by the AGA8-dc equation of state were estimated. To this end, the formulas for enthalpy, entropy, and speed of sound, which are used in calculating the CFF, were expressed in the form of dimensionless Helmholtz free energy and its derivatives, and the uncertainty in Helmholtz free energy was inferred. To consider the variations in the compressibility-dependent variables induced by the variation (i.e., uncertainty) in compressibility, the form of the AGA8-dc equation was modified to have a deviation equal to the uncertainty under each flow condition. For each independent uncertainty component of the CFF, a model for uncertainty contribution was developed. All these changes were applied to GASSOLVER, which is KOGAS's thermodynamic database. As a result, the uncertainties in the CFF were estimated to be 0.025, 0.055, and 0.112 % at 10, 50, and 100 bar, respectively, and are seen to increase with the increase in pressure. Furthermore, these results could explain the deviations in the CFFs across the different labs in which the CFF international comparison test was conducted under the ISO management in 1999.

• Nuclear Engineering and Technology
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• v.48 no.3
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• pp.765-772
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• 2016

In analyzing residual radiation, researchers generally use a two-step Monte Carlo (MC) simulation. The first step (MC1) simulates neutron transport, and the second step (MC2) transports the decay photons emitted from the activated materials. In this process, the stochastic uncertainty estimated by the MC2 appears only as a final result, but it is underestimated because the stochastic error generated in MC1 cannot be directly included in MC2. Hence, estimating the true stochastic uncertainty requires quantifying the propagation degree of the stochastic error in MC1. The brute force technique is a straightforward method to estimate the true uncertainty. However, it is a costly method to obtain reliable results. Another method, called the adjoint-based method, can reduce the computational time needed to evaluate the true uncertainty; however, there are limitations. To address those limitations, we propose a new strategy to estimate uncertainty propagation without any additional calculations in two-step MC simulations. To verify the proposed method, we applied it to activation benchmark problems and compared the results with those of previous methods. The results show that the proposed method increases the applicability and user-friendliness preserving accuracy in quantifying uncertainty propagation. We expect that the proposed strategy will contribute to efficient and accurate two-step MC calculations.

• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.125-135
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• 2013

Analysis and evaluation of uncertainty is adopting the advanced methodology among the methods for greenhouse gas emission assessment that was defined in GPS2000 (Good practice guideline 2000) and GPG-LULUCF (GPG Land Use, Land-Use Change and Forestry). In 2006 IPCC guideline, two approaches are suggested to explain the uncertainty for each section with a national net emission and a prediction value on uncertainty as follows; 1) Spread sheet calculation based on the error propagation algorithm that was simplified with some assumptions, and 2) Monte carlo simulation that can be utilized in general purposes. There are few researches on the agricultural field including greenhouse gas emission that is generated from livestock and cultivation lands due to lack of information for statistic data, emission coefficient, and complicated emission formula. The main objective of this study is to suggest an evaluation method for the uncertainty of greenhouse gas emission in agricultural field by means of intercomparison of the prediction value on uncertainties which were estimated by spread sheet calculation and monte carlo simulation. A statistic analysis for probability density function for uncertainty of emission rate was carried out by targeting livestock intestinal fermentation, excrements treatment, and direct/indirect emission from agricultural lands and rice cultivation. It was suggested to minimize uncertainty by means of extraction of emission coefficient according to each targeting section.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.208-208
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• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.285-292
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• 2024

When calculating sonar detection probability, underwater acoustic uncertainty is assumed to be normal distributed with a standard deviation of 8 dB to 9 dB. However, due to the variability in experimental areas and ocean environmental conditions, predicting detection performance requires accounting for underwater acoustic uncertainty based on ocean experimental data. In this study, underwater acoustic uncertainty was determined using measured mid-frequency (2.3 kHz, 3 kHz) noise level and transmission loss data collected in the shallow water of the East Sea. After calculating the predictable probability of detection reflecting underwater acoustic uncertainty based on ocean experimental data, we compared it with the conventional detection probability results, as well as the predictable probability of detection results considering the uncertainty of the Rayleigh distribution and a negatively skewed distribution. As a result, we confirmed that differences in the detection area occur depending on each underwater acoustic uncertainty.

• Journal of Korean Tunnelling and Underground Space Association
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• v.6 no.1
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• pp.25-40
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• 2004

The supersonic shock wave generated by fully coupled explosion will change into subsonic shock wave, plastic wave, and elastic wave consecutively as the wave propagates through rock mass. While the estimation of the blast-induced peak pressure was the main aim of the companion paper, this paper will concentrate on the estimation of the rise time of blast-induced pressure. The rise time can be expressed as a function of explosive density, isentropic exponent, detonation velocity, exponential coefficient of the peak pressure attenuation, dynamic yield stress, plastic wave velocity, elastic wave velocity, rock density, Hugoniot parameters, etc. Parametric analysis was performed to pinpoint the most influential parameter that affects the rise time and it was found that rock properties are more sensitive than explosive properties. The probabilistic distribution of the rise time is evaluated by the Rosenblueth'S point estimate method from the probabilistic distributions of explosive properties and rock properties. Numerical analysis was performed to figure out the effect of rock properties and explosive properties on the uncertainty of blast-induced vibration. Uncertainty analysis showed that uncertainty of rock properties constitutes the main portion of blast-induced vibration uncertainty rather than that of explosive properties. Numerical analysis also showed that the loading rate, which is the ratio of the peak blasting pressure to the rise time, is the main influential factor on blast-induced vibration. The loading rate is again more influenced by rock properties than by explosive properties.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.208-217
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• 2016

This paper describes a simulation method to generate sensor measurements for location estimation of an underwater robot. Field trial of a navigation method of an underwater robot takes much time and expenses and it is difficult to change the environment of the field trial as desired to test the method in various situations. Therefore, test and verification of a navigation method through simulation is inevitable for underwater environment. This paper proposes a method to generate sensor measurements of range, depth, velocity, and attitude taking the uncertainties of measurements into account through simulation. The uncertainties are Gaussian noise, outlier, and correlation between the measurement noise. Also, the method implements uncertainty in sampling time of measurements. The method is tested and verified by comparing the uncertainty parameters calculated statistically from the generated measurements with the designed uncertainty parameters. The practical feasibility of the measurement data is shown by applying the measurement data for location estimation of an underwater robot.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.2
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• pp.107-113
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• 2019

In this paper, a robust filter based wind velocity estimation algorithm without an air velocity sensor in an air vehicle is presented. The wind velocity is useful information for the air vehicle to perform precise guidance and control. In general, the wind velocity can be obtained by subtracting an air velocity which is obtained by an air velocity sensor such as a pitot-tube, and a ground velocity which is obtained by a navigation equipment. However, in order to simplify the configuration of the air vehicle, the wind estimation algorithm is necessary because the wind velocity can not be directly obtained if the air velocity measurement sensor is not used. At this time, the aerodynamic coefficient of the air vehicle changes due to the turbulence, which causes the uncertainty of the system model of the filter, and the wind estimation performance deteriorates. Therefore, in this study, we propose a wind estimation method using $H{\infty}$ filter to ensure robustness against aerodynamic coefficient uncertainty, and we confirmed through simulation that the proposed method improves the performance in the uncertainty of aerodynamic coefficient.

• Journal of Korea Water Resources Association
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• v.52 no.11
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• pp.931-940
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• 2019

In hydrologic models, parameters are mainly used to reflect hydrologic elements or to supplement the simplified models. In this process, the proper selection of the parameters in the model can reduce the uncertainty. Accordingly, this study attempted to quantify the uncertainty of SWAT parameters using the General Likelihood Uncertainty Estimation (GLUE). Uncertainty analysis on SWAT parameters was conducted by using the formal and informal likelihood measures. The Lognormal function and Nash-Sutcliffe Efficiency (NSE) were used for formal and informal likelihood, respectively. Subjective factors are included in the selection of the likelihood function and the threshold, but the behavioral models were created by selecting top 30% lognormal for formal likelihood and NSE above 0.5 for informal likelihood. Despite the subjectivity in the selection of the likelihood and the threshold, there was a small difference between the formal and informal likelihoods. In addition, among the SWAT parameters, ALPHA_BF which reflects baseflow characteristics is the most sensitive. Based on this study, if the range of SWAT model parameters satisfying a certain threshold for each watershed is classified, it is expected that users will have more practical or academic access to the SWAT model.