• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.2803-2815
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• 2021

This paper addresses the uncertainty quantification and sensitivity analysis of a depleted light-water fuel assembly of the Turkey Point-3 benchmark. The uncertainty of the fuel assembly decay heat and isotopic densities is quantified with respect to three different groups of diverse parameters: nuclear data, assembly design, and reactor core operation. The uncertainty propagation is conducted using a two-step analysis code system comprising the lattice code STREAM, nodal code RAST-K, and spent nuclear fuel module SNF through the random sampling of microscopic cross-sections, fuel rod sizes, number densities, reactor core total power, and temperature distributions. Overall, the statistical analysis of the calculated samples demonstrates that the decay heat uncertainty decreases with the cooling time. The nuclear data and assembly design parameters are proven to be the largest contributors to the decay heat uncertainty, whereas the reactor core power and inlet coolant temperature have a minor effect. The majority of the decay heat uncertainties are delivered by a small number of isotopes such as ²⁴¹Am, ¹³⁷Ba, ²⁴⁴Cm, ²³⁸Pu, and ⁹⁰Y.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.3
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• pp.401-409
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• 2023

Oscillating water column (OWC) type wave power generator system is a power generation system that uses wave energy, a sustainable and renewable energy source. Irregular cycles and wave heights act as factors that make it difficult to secure generation efficiency of the wave power generator system. Recently, research for improving power generation efficiency is being conducted by applying digital twin technology to OWC type wave energy converter system. However, digital twin using sensor data can predict erroneous performance due to uncertainty in the sensor data. Therefore, this study proposes an uncertainty analysis method for sensor data which is used in digital twin to secure the reliability of digital twin prediction results. Uncertainty quantification considering sensor data characteristics and future uncertainty information according to uncertainty propagation were derived mathematically, and confidence interval estimation was performed based on the proposed method.

• Atmosphere
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• v.25 no.3
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• pp.511-520
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• 2015

Existing studies on radar rainfall uncertainties were performed to reduce the uncertainty for each stage by using bias correction during the quantitative radar rainfall estimation process. However, the studies do not provide quantitative comparison with the uncertainties for all stages. Consequently, this study proposes a suitable approach that can quantify the uncertainties at each stage of the quantitative radar rainfall estimation process. First, the new approach can present initial and final uncertainties, increasing or decreasing the uncertainty, and the uncertainty percentage at each stage. Furthermore, Maximum Entropy (ME) was applied to quantify the uncertainty in the entire process. Second, for the uncertainty quantification of radar rainfall estimation at each stage, this study used two quality control algorithms, two rainfall estimation relations, and two bias correction techniques as post-processing and progressed through all stages of the radar rainfall estimation. For the proposed approach, the final uncertainty (ME = 3.81) from the ME of the bias correction stage was the smallest while the uncertainty of the rainfall estimation stage was higher because of the use of an unsuitable relation. Additionally, the ME of the quality control was at 4.28 (112.34%), while that of the rainfall estimation was at 4.53 (118.90%), and that of the bias correction at 3.81 (100%). However, this study also determined that selecting the appropriate method for each stage would gradually reduce the uncertainty at each stage. Finally, the uncertainty due to natural variability was 93.70% of the final uncertainty. Thus, the results indicate that this new approach can contribute significantly to the field of uncertainty estimation and help with estimating more accurate radar rainfall.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.2
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• pp.199-206
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• 2013

In general, radial velocity of a target can be obtained by acquiring doppler frequency shift in case of a doppler radar, or can be obtained by acquiring range rate in case of a pulse radar. Then radial velocity can be converted to tangential velocity using aspect angle or position variation per unit time. These two ways have the same meaning in physically, but result in different uncertainty finally. In this paper, it is described not only the two transformation procedures to calculate tangential velocity from radar measurement data, but also the result of combined uncertainty comparison between these two procedures.

• Structural Engineering and Mechanics
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• v.58 no.3
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• pp.443-458
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• 2016

In this paper, we propose a method for taking into account uncertainties based on the projection on polynomial chaos. Due to the manufacturing and assembly errors, uncertainties in material and geometric properties, the system parameters including assembly defect, damping coefficients, bending stiffness and traction-compression stiffness are uncertain. The proposed method is used to determine the dynamic response of a one-stage spur gear system with uncertainty associated to gear system parameters. An analysis of the effect of these parameters on the one stage gear system dynamic behavior is then treated. The simulation results are obtained by the polynomial chaos method for dynamic analysis under uncertainty. The proposed method is an efficient probabilistic tool for uncertainty propagation. The polynomial chaos results are compared with Monte Carlo simulations.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1388-1392
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• 2008

Water resources management depends on dealing inherent uncertainties stemming from climatic and hydrological inputs and models. Dealing with these uncertainties remains a challenge. Streamflow forecasts basically contain uncertainties arising from model structure and initial conditions. Recent enhancements in climate forecasting skill and hydrological modeling provide an breakthrough for delivering improved streamflow forecasts. However, little consideration has been given to methodologies that include coupling both multiple climate and multiple hydrological models, increasing the pool of streamflow forecast ensemble members and accounting for cumulative sources of uncertainty. The approach here proposes integration and coupling of global climate models (GCM), multiple regional climate models, and numerous hydrological models to improve streamflow forecasting and characterize system uncertainty through generation of ensemble forecasts.

• Journal of Korean Society on Water Environment
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• v.22 no.3
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• pp.427-430
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• 2006

Uncertainty is one of the key issues of the water quality management. Uncertainty occurs in the course of all water quality management stages including monitoring, modeling, and regulation enforcement. To reduce uncertainties of water quality monitoring, manualized monitoring methodology should be developed and implemented. In addition, long-term monitoring is essential for acquiring reliable water quality data which enables best water quality management. For the water quality management in the watershed scale, fate of pollutant including its generation, transport and impact should be considered while regarding each stage of water quality management as an unit process. Uncertainties of each stage of water quality management should be treated properly to prevent error propagation transferred to the next stage of management for successful achievement of water quality conservation.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.1
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• pp.71-83
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• 1994

Recently, an interest in the uncertainty analysis on measurement and prediction has been growing. An uncertainty analysis method is applied to the P.O.W test where error sources, estimated errors, their propagation route and their sensitivities to the uncertainty items are clearly illustrated. The uncertainty range for the results obtained from the HMRI Propeller Open Water test is within ${\pm}1%$ which is assumed to be lower than an usual measurement error range of ${\pm}1%$. It has been noticed that the uncertainty analysis can be used quite usefully for detecting dominant error-sources and hence improving the experimental measurement accuracy.

• Journal of Astronomy and Space Sciences
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• v.16 no.2
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• pp.159-166
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• 1999

As the spatial resolution of remote sensing satellites becomes higher, very accurate determination of the position of a LEO (Low Earth Orbit) satellite is demanding more than ever. Non-symmetric Earth gravity is the major perturbation force to LEO satellites. Since the orbit propagation is performed in the celestial frame while Earth gravity is defined in the terrestrial frame, it is required to convert the coordinates of the satellite from one to the other accurately. Unless the coordinate conversion between the two frames is performed accurately the orbit propagation calculates incorrect Earth gravitational force at a specific time instant, and hence, causes errors in orbit prediction. The coordinate conversion between the two frames involves precession, nutation, Earth rotation and polar motion. Among these factors, unpredictability and uncertainty of Earth rotation, called UTI-UTC, is the largest error source. In this paper, the effect of UTI-UTC on the accuracy of the LEO propagation is introduced, tested and analzed. Considering the maximum unpredictability of UTI-UTC, 0.9 seconds, the meaningful order of non-spherical Earth harmonic functions is derived.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.4
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• pp.395-400
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• 2009

As the variables affecting the fatigue behavior have uncertainty, the fatigue crack propagation is stochastic in nature. Therefore, the fatigue life prediction is critical for the design and the maintenance of many structural components. In this study, fatigue experiments are conducted on the specimens of magnesium alloy under the different thicknesses of specimen. The effects of specimen thickness on the probability distribution of the fatigue crack propagation life and the crack size are estimated experimentally. The probability distribution of the crack size and the fatigue life for different specimen thicknesses are investigated by Anderson-Darling test and the best fit for those probability distributions are also presented.