• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1289-1297
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• 2018

Preliminary surface soil Derived Concentration Guideline Levels (DCGLs) were derived conforming to the Multi-Agency Radiation Site Survey and Investigation Manual (MARSSIM) procedure for the site release and reuse of Kori Unit 1 in Korea. Based on the decommissioning experiences of the U.S. nuclear power plants, a suite of residual radionuclides was determined, and uncertainties contributed to the resultant dose by the input parameters were quantified via the sensitivity analysis of parameters. The peak of the mean dose was obtained via the probabilistic analysis of the RESRAD (RESidual RADioactivity)-ONSITE code. Consequently, $DCGL_w$ of Kori Unit 1 in accordance with two scenarios, industrial worker and residential farmer scenario, were derived and the results were compared respectively with other NPPs. It could be used as a basic guideline for establishing regulatory standards for reuse planning, designing the site characterization surveys and implementing final status survey (FSS).

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.1466-1483
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• 2008

This paper discusses the development of an up-to-date computerized CPT (Cone Penetration Test) based soil engineering classification system to provide geotechnical engineers with a handy tool for their daily design activities. Five CPT soil engineering classification systems are incorporated in this effort. They include the probabilistic region estimation and fuzzy classification methods, both developed by Zhang and Tumay, the Schmertmann, the Douglas and Olsen, and the Robertson et al. methods. In the probabilistic region estimation method, a conformal transformation is used to determine the soil classification index, U, from CPT cone tip resistance and friction ratio. A statistical correlation is established between U and the compositional soil type given by the Unified Soil Classification System (USCS). The soil classification index, U, provides a soil profile over depth with the probability of belonging to different soil types, which more realistically and continuously reflects the in-situ soil characterization, which includes the spatial variation of soil types. The CPT fuzzy classification on the other hand emphasizes the certainty of soil behavior. The advantage of combining these two classification methods is realized through implementing them into visual basic software with three other CPT soil classification methods for friendly use by geotechnical engineers. Three sites in Louisiana were selected for this study. For each site, CPT tests and the corresponding soil boring results were correlated. The soil classification results obtained using the probabilistic region estimation and fuzzy classification methods are cross-correlated with conventional soil classification from borings logs and three other established CPT soil classification methods.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.123-130
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• 2003

The estimation of key soil properties and subsequent quantitative assessment of the associated uncertainties has always been an important issue in geotechnical engineering. It is well recognized that soil properties vary spatially as a result of depositional and post-depositional processes. The stochastic nature of spatially varying soil properties can be treated as a random field. A practical statistical approach that can be used to systematically model various sources of uncertainty is presented in the context of reliability analysis of slope stability Newly developed expressions for probabilistic characterization of soil properties incorporate sampling and measurement errors, as well as spatial variability and its reduced variance due to spatial averaging. Reliability analyses of the probability of slope failure using the different statistical representations of soil properties show that the incorporation of spatial correlation and conditional simulation leads to significantly lower probability of failure than obtained using simple random variable approach.

• Tunnel and Underground Space
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• v.12 no.3
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• pp.198-209
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• 2002

To assess deep geological environment for the research and development of hish-level radioactive waste disposal, six boreholes of 3" in diameter were installed in two granitic areas. An areal extent of the rock block scale in the study sites was estimated by the lineament analysis from satellite images and shaded relief maps. The characterization of fracture system developed in rock block scale was carried out based on the acoustic televiewer logging in deep boreholes. In the Yuseong site, the granite rock mass was divided into the upper and lower zones at around -160m based on the probabilistic distribution characteristics of the geometric parameters such as orientation, fracture frequency, spacing and aperture size. Since the groundwater flow is dependent on the fracture system in a fractured rock mass, the correlation of the fracture frequency and cumulative aperture size to the hydraulic conductivity was also discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.8 no.3
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• pp.85-90
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• 1988

A probabilistic model for the failure in a homogeneous soil slope is presented. The Safety of the slope is measured through its probability of failure rather than the customary factor of safety. The safety margin of slope failure is assumed to follow a normal distribution. Sources of uncertainties affecting characterization of soil property in a homogeneous soil layer include inherent spatial variability., estimation error from insufficient samples, and measurement errors. Uncertainties of the shear strength-along potential failure surface are expressed by one-dimensional random field models. The rupture surface, created at toe of a soil slope, has been considered to propagate towards the boundary along a path following an exponential (log-spiral) law. Having derived the statistical characteristics of the rupture surface and of the forces which act along it, the probability of failure of the slope was found. Finally the developed procedure has been applied in a case study to yield the reliability of a soil slope.

• Nuclear Engineering and Technology
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• v.36 no.1
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• pp.83-103
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• 2004

The methodological framework of the Level 2 PSA appears to be currently standardized in a formalized fashion, but there have been different opinions on the way the sources of uncertainty are characterized and treated. This is primarily because the Level 2 PSA deals with complex phenomenological processes that are deterministic in nature rather than random processes, and there are no probabilistic models characterizing them clearly. As a result, the probabilistic quantification of the Level 2 PSA CET / APET is often subjected to two sources of uncertainty: (a) incomplete modeling of accident pathways or different predictions for the behavior of phenomenological events and (b) expert-to-expert variation in estimating the occurrence probability of phenomenological events. While a clear definition of the two sources of uncertainty involved in the Level 2 PSA makes it possible to treat an uncertainty in a consistent manner, careless application of these different sources of uncertainty may produce different conclusions in the decision-making process. The primary purpose of this paper is to characterize typical sources of uncertainty that would often be addressed in the Level 2 PSA and to provide a formal guidance for quantifying their impacts on the PSA Level 2 risk results. An additional purpose of this paper is to give a formal approach on how to combine random uncertainties addressed in the Level 1 PSA with subjectivistic uncertainties addressed in the Level 2 PSA.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.104-115
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• 2019

Since the Fukushima Daiichi accident, there has been an emphasis on the risk resulting from multi-unit accidents. Human reliability analysis (HRA) is one of the important issues in multi-unit probabilistic safety assessment (MUPSA). Hence, there is a need to properly identify all the human and organizational factors relevant to a multi-unit incident scenario in a nuclear power plant (NPP). This study identifies and categorizes the human and organizational factors relevant to a multi-unit incident scenario of NPPs based on a review of relevant literature. These factors are then analyzed to ascertain all possible unit-to-unit interactions that need to be considered in the multi-unit HRA and the pattern of interactions. The human and organizational factors are classified into five categories: organization, work device, task, performance shaping factors, and environmental factors. The identification and classification of these factors will significantly contribute to the development of adequate strategies and guidelines for managing multi-unit accidents. This study is a necessary initial step in developing an effective HRA method for multiple NPP units in a site.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.8
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• pp.955-964
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• 2014

The more importance of international collaboration has increased, the more studies on statues of international collaboration are increasing. However, few studies have attempted to identify the international collaboration. This article aims at a multidirectional characterization of the international collaboration in the field of Computer Science by analysis of articles published in the SCOPUS database. We applied Probabilistic Affinity Index(PAI) and Indicator of Collaboration Strength(ICS) for measuring the intensity of scientific collaboration among countries, and index of Incremental Citation Impact(ICI) for measuring the quality of international collaboration. These analyses identify the trends of international collaboration in the field of Computer Science and it's effect by nation.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• Journal of the Korean Geotechnical Society
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• v.23 no.3
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• pp.111-121
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• 2007

The paper presents a reliability-based method that can capture the impact of uncertainty of seismic loadings. The proposed method incorporates probabilistic concepts into the classical limit equilibrium and the Newmark-type deformation techniques. The risk of damage is then computed by Monte Carlo simulation. Random process and RMS hazard method are introduced to produce seismic motions and also to use them in the seismic slope analyses. The geotechnical variability and sampling errors are also considered. The results of reliability analyses indicate that in a highly seismically active region, characterization of earthquake hazard is the more critical factor, and characterization of soil properties has a relatively small effect on the computed risk of slope failure and excessive slope deformations. The results can be applicable to both circular and non-circular slip surface failure modes.