• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.18 no.4
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• pp.517-536
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• 2020

The radionuclide inventory in radioactive waste from nuclear power plants should be determined to secure the safety of final repositories. As an alternative to time-consuming, labor-intensive, and destructive radiochemical analysis, the indirect scaling factor (SF) method has been used to determine the concentrations of difficult-to-measure radionuclides. Despite its long history, the original SF methodology remains almost unchanged and now needs to be improved for advanced SF implementation. Intense public attention and interest have been strongly directed to the reliability of the procedures and data regarding repository safety since the first operation of the low- and intermediate-level radioactive waste disposal facility in Gyeongju, Korea. In this review, statistical methodologies for SF implementation are described and evaluated to achieve reasonable and advanced decision-making. The first part of this review begins with an overview of the current status of the scaling factor method and global experiences, including some specific statistical issues associated with SF implementation. In addition, this review aims to extend the applicability of SF to the characterization of large quantities of waste from the decommissioning of nuclear facilities.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.414-422
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• 2022

Presented in this paper is a methodology for combining a Bayesian statistical approach with Data Quality Objectives (a structured decision-making method) to provide increased levels of confidence in analytical data when approaching a waste boundary. Development of sampling and analysis plans for the characterisation of radioactive waste often use a simple, one pass statistical approach as underpinning for the sampling schedule. Using a Bayesian statistical approach introduces the concept of Prior information giving an adaptive sample strategy based on previous knowledge. This aligns more closely with the iterative approach demanded of the most commonly used structured decision-making tool in this area (Data Quality Objectives) and the potential to provide a more fully underpinned justification than the more traditional statistical approach. The approach described has been developed in a UK regulatory context but is translated to a waste stream from the Fukushima Daiichi Nuclear Power Station to demonstrate how the methodology can be applied in this context to support decision making regarding the ultimate disposal option for radioactive waste in a more global context.

• Journal of the Korean Solar Energy Society
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• v.30 no.4
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• pp.55-62
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• 2010

The purpose of this study is to present various analysis result of energy consumption that is a statistical analysis of high school facilities in Korea for setting the goal of energy saving. This study enforced analysis after it provided used energy consumption for the year 2008 and general in formation from 2202 high school facilities in 16 cities in South Korea by the relevant agency. Consequently, it represents that the average energy consumption of electric power was 428.7MWh(65.7%), gas consumption for heating was 129.5MWh(19.8%), oil consumption was 84.6MWh(13.0%), district energy was 10.0MWh(1.5%) in nation after changing as unit 'kWh' only for comparison with every energy source. This result describes that consumption of electric power was large greatly and it reflects the expectation that it will climb the demand regarding this energy in the future. In additionally, it analyzed average energy consumption with $98.3kWh/m^2$ by the unit area of air-conditioning and the district which has large energy consumption was Gyeonggi-do with $115.9kWh/m^2$. Furthermore, it described the average energy consumption of $60.8kWh/m^2$ by the unit area of floor area and the average energy consumption of a student analyzed with 1157.0kWh.

• Proceedings of the ESK Conference
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• 1997.10a
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• pp.303-309
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• 1997

This study is carried out to investigate performance differences between two alarm presentation methods from the viewpoint of human factors and to provide items to be improved. One of the alarm display methods considered in this study displays alarm lists on VDT combined with hardwired alarm panels. The other method displays alarms on plant mimic diagrams of VDT. This alarm display method has other features for operator aid with which operator can get detailed information on the activated alarm in the mimic diagrams, and the capability for alarm processing such as alarm reduction and prioritization. To compare the twodisplay methods, a human factor experiment was performed with a plant simulator in the ITF(Integrated Test Fcility) that plant operators run for 4 event scenarios. During the experiment, physiological measurements, system and operator action log, and audio/video recordings were collected. Operators' subjective opinion was collected as well after the experiment. Time, error rate and situation awareness were major human factor criteria used for the comparison during the analysis stage of the experiment. No statistical significance was found in the results of our statistical comparison analysis. Several findings were identified, however, through the analysis of subjective opinions.

• Nuclear Engineering and Technology
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• v.18 no.1
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• pp.38-47
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• 1986

A statistical procedure, which uses response surface method and Monte Carlo simulation technique, is proposed for analyzing the thermal margin of light water reactor core. The statistical thermal margin analysis method performs the best.estimate thermal margin evaluation by the probabilistic treatment of uncertainties of input parameters. This methodology is applied to KNU-1 core thermal margin analysis under the steady state nominal operating condition. Also discussed are the comparisons with conventional deterministic method and Improved Thermal Design Procedure of Westinghouse. It is deduced from this study that the response surface method is useful for performing the statistical thermal margin analysis and that thermal margin improvement is assured through this procedure.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1157-1167
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• 2010

This paper details a method for establishing a wind energy map having($1Km{\times}1Km$) resolution. The map is essential for measurement and efficiency-testing of wind energy resources and wind site analysis. To this end, a statistical wind field model is estimated that covers 345,682 regions obtained by $1Km{\times}1Km$ lattices made over South Korea. The paper derives various characteristics of a regional wind energy resource under the statistical wind field model and estimates them to construct the wind energy map. Kolmogorov-Smirnov test, based on TMY(typical meteorological year) wind data of 76 weather station areas, shows that a Log-normal model is adequate for the statistical wind field model. The model is estimated by using the wind speed data of 345,682 regions provided by the National Institute of Meteorological Research(NIMR). Various wind energy statistics are studied under the Log-normal wind field model. As an application, the wind energy density(W$/m^2$) map of South Korea is constructed with a resolution of $1Km{\times}1Km$ and its utility for the wind site analysis is discussed.

• Journal of Mechanical Science and Technology
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• v.18 no.11
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• pp.1909-1915
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• 2004

The hermetic rotary compressor is one of the most important components of an air conditioning system since it has a great effect on both the performance and the noise and vibration of the system. Noise and vibration occurs due to gas pulsation during the compression process and to unbalanced dynamic force. In order to reduce noise and vibration, it is necessary to identify their sources and transmission path and effectively control them. Many approaches have been tried in order to identify the noise transmission path of a compressor. However, identification has proven to be difficult since the characteristics of compressor noise are complicated due to the interaction of the compressor parts and gas pulsation. In this study, the statistical energy analysis has been used to trace the energy flow in the compressor and to identify the transmission paths from the noise source to the exterior sound field.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.359-364
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• 2002

Statistical energy method is widely used for the prediction of vibrational and acoustical behavior of complex structures, such as ship building and automobile in mid-, high frequency ranges. However. in order to convince this SEA result, it is important to verify estimated SEA parameters, e. g. modal density, energy in each subsystem, damping loss factor, coupling loss factor. with possible other method. For modal density parameter, the experimental estimations via Experimental Modal Analysis are checked with those from finite element method for both beam- plate and plate-plate cans. Loss factors are calculated by Lyon's simple method for the two subsystem. finally. modal experiments are carried out by varying the mass added on the junction of two subsystem for the purpose of investigating the influence on the coupling loss factor's behavior.

• Proceedings of the Korean Nuclear Society Conference
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• 2003.05a
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• pp.103.1-103.1
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• 2003

• Journal of the Korean Society of Safety
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• v.28 no.1
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• pp.158-163
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• 2013

While job stress evaluations are reported in the recent surveys upon the nuclear power plants(NPPs), any significant advance in the types of questionnaires is not currently found. There are limitations to their usefulness as analytic tools for the management of safety resources in NPPs. Data mining(DM) has emerged as one of the key features for data computing and analysis to conduct a survey analysis. There are still limitations to its capability such as dimensionality associated with many survey questions and quality of information. Even though some survey methods may have significant advantages, often these methods do not provide enough evidence of causal relationships and the statistical inferences among a large number of input factors and responses. In order to address these limitations on the data computing and analysis capabilities, we propose an advanced procedure of survey analysis incorporating the DM method into a statistical analysis. The DM method can reduce dimensionality of risk factors, but DM method may not discuss the robustness of solutions, either by considering data preprocesses for outliers and missing values, or by considering uncontrollable noise factors. We propose three steps to address these limitations. The first step shows data mining with response surface method(RSM), to deal with specific situations by creating a new method called response surface data mining(RSDM). The second step follows the RSDM with detailed statistical relationships between the risk factors and the response of interest, and shows the demonstration the proposed RSDM can effectively find significant physical, psycho-social, and environmental risk factors by reducing the dimensionality with the process providing detailed statistical inferences. The final step suggest a robust stress management system which effectively manage job stress of the workers in NPPs as a part of a safety resource management using the surrogate variable concept.