• Proceedings of the KSME Conference
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• 2007.05a
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• pp.250-255
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• 2007

Steam generator tubes play an important role in safety because they constitute one of the primary barriers between the radioactive and non-radioactive sides of the nuclear power plant. For this reason, the integrity of the tubes is essential in minimizing the leakage possibility of radioactive water. The integrity of the tubes is evaluated based on NDE (non-destructive evaluation) inspection results. Especially ECT (eddy current test) method is usually used for detecting the flaws in steam generator tubes. However, detection capacity of the NDE is not perfect and all of the "real flaws" which actually existing in steam generator tunes is not known by NDE results. Therefore reliability of NDE system is one of the essential parts in assessing the integrity of steam generators. In this study POD (probability of detection) of ECT system for ODSCC in steam generator tubes is evaluated using multivariate logistic regression. The cracked tube specimens are made using the withdrawn steam generator tubes. Therefore the cracks are not artificial but real. Using the multivariate logistic regression method, continuous POD surfaces are evaluated from hit (detection) and miss (no detection) binary data obtained from destructive and non-destructive evaluation of the cracked tubes. Length and depth of cracks are considered in multivariate logistic regression and their effects on detection capacity are evaluated.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2915-2923
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• 2022

There is an increasing interest in passive safety systems to minimize the need for operator intervention or external power sources in nuclear power plants. Because a passive system has a weak driving force, there is greater uncertainty in the performance compared with an active system. In previous studies, several methods have been suggested to evaluate passive system reliability, and many of them estimated the failure probability using thermal-hydraulic analyses and the Monte Carlo method. However, if the functional failure of a passive system is rare, it is difficult to estimate the failure probability using conventional methods owing to their high computational time. In this paper, a procedure for the application of the Chernoff bound to the evaluation of passive system reliability is proposed. A feasibility study of the procedure was conducted on a passive decay heat removal system of a micro modular reactor in its conceptual design phase, and it was demonstrated that the passive system reliability can be evaluated without performing a large number of thermal-hydraulic analyses or Monte Carlo simulations when the system has a small failure probability. Accordingly, the advantages and constraints of applying the Chernoff bound for passive system reliability evaluation are discussed in this paper.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.39-44
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• 2012

Water supply capacity and operational capability in agricultural reservoirs are expressed differently in the limited storage due to seasonal and local variation of precipitation. Since agricultural water supply and demand basically assumes the uncertainty of hydrological phenomena, it is necessary to improve probabilistic approach for potential risk assessment of water supply capacity in reservoir for enhanced operational storage management. Here, it was introduced the irrigation vulnerability characteristic curves to represent the water supply capacity corresponding to probability distribution of the water demand from the paddy field and water supply in agricultural reservoir. Irrigation vulnerability probability was formulated using reliability analysis method based on water supply and demand probability distribution. The lower duration of irrigation vulnerability probability defined as the time period requiring intensive water management, and it will be considered to assessment tools as a risk mitigated water supply planning in decision making with a limited reservoir storage.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.688-693
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• 2002

Adhesive bonding is becoming one of the popular joining techniques in metal industries, since it has some advantages over other techniques such as welding and diffusion bonding, e.g., any dissimilar metals are easily adhesive-bonded together. In this study, the experiments were carried out in order to provide the statistical data with strength evaluation methods: tension, shear and four-point bending tests for thermoplastic epoxy resin based adhesive-bonded metal joints. We should certificate on the probability of the adhesive strength that has the tendency of brittle fracture, the adhesive bonding strength between metals with thermoplastic adhesive has the best probability at four-point bending test. The strength testing method that has higher probability is four-point bending test, shear test and tensile test in order.

• Structural Engineering and Mechanics
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• v.57 no.4
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• pp.587-602
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• 2016

In structural reliability analysis, the response surface method is widely adopted because of its numerical efficiency. It should be understood that the response function must approximate the actual limit state function accurately in the main region influencing failure probability where it is evaluated. However, the size of main region influencing failure probability was not defined clearly in current response surface methods. In this study, the concept of sub-region of interest is constructed, and an improved response surface method is proposed based on the sub-region of interest. The sub-region of interest can clearly define the size of main region influencing failure probability, so that the accuracy of the evaluation of failure probability is increased. Some examples are introduced to demonstrate the efficiency and the accuracy of the proposed method for both numerical and implicit limit state functions.

• Journal of the Korean Society of Safety
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• v.21 no.1 s.73
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• pp.28-34
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• 2006

A procedure of estimating failure probability is demonstrated for a pressurized pipe of CrMo steel used at $538^{\circ}C$. Probabilistic fracture mechanics were employed considering variations of pressure loading, material properties and geometry. Probability density functions of major material variables were determined by statistical analyses of implemented data obtained by previous experiments. Distributions of the major variables were reflected in Monte Carlo simulation and failure probability as a function of operating time was determined. The creep crack growth life assessed by conventional deterministic approach was shown to be conservative compared with those obtained by probabilistic one. Sensitivity analysis for each input variable was also conducted to understand the most influencing variables to the residual life analysis. Internal pressure, creep crack growth coefficient and creep coefficient were more sensitive to failure probability than other variables.

• International Journal of Reliability and Applications
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• v.3 no.1
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• pp.37-50
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• 2002

Simultaneous estimation of accuracy and probability corresponding to a prediction interval is considered in this study. Traditional application of confidence interval forecasting consists in evaluation of interval limits for a given significance level. The wider is this interval, the higher is probability and the lower is the forecast precision. In this paper a measure of stochastic forecast accuracy is introduced, and a procedure for balanced estimation of both the predicting accuracy and confidence probability is elaborated. Solution can be obtained in an optimizing approach. Suggested method is applied to constructing confidence intervals for parameters estimated by normal and t distributions

• Journal of the Korean School Mathematics Society
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• v.20 no.4
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• pp.387-404
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• 2017

In this paper, in the last 4 years(2014~2017 school year), we classified the probability and statistical items based on the evaluation scope of the mathematics subject content knowledge which were presented by the Korea Institute for Curriculum and Evaluation, and the classified items were analyzed. As a result, First, in order to induce normalization of the probability and statistical curriculum, four assessment field should be evenly distributed. Second, integrated thinking and comprehensive analytical thinking assessment is required. Third, item an epilogue should be used to measure mathematical thinking and logical competence. Fourth, the ratio of the number of items in probability and statistics to the number of that was 7.7%~10.0%, and the ratio according to the item weighting was 5.0%~7.5%. Fifth, it maintains the policy of stabilizing a good the level of difficulty of the items. Finally, probability and statistical assessment should focus on measuring problem solving ability from an inductive point of view.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.789-797
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• 2017

Recently, some integrated structural identification/damage detection and reliability evaluation of structures with uncertainties have been proposed. However, these techniques are applicable for off-line synthesis of structural identification and reliability evaluation. In this paper, based on the recursive formulation of the extended Kalman filter, an on-line integration of structural identification/damage detection and reliability evaluation of stochastic building structures is investigated. Structural limit state is expanded by the Taylor series in terms of uncertain variables to obtain the probability density function (PDF). Both structural component reliability with only one limit state function and system reliability with multi-limit state functions are studied. Then, it is extended to adopt the recent extended Kalman filter with unknown input (EKF-UI) proposed by the authors for on-line integration of structural identification/damage detection and structural reliability evaluation of stochastic building structures subject to unknown excitations. Numerical examples are used to demonstrate the proposed method. The evaluated results of structural component reliability and structural system reliability are compared with those by the Monte Carlo simulation to validate the performances of the proposed method.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.4 no.4
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• pp.250-260
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• 1992

Two methods for computing extreme sea levels, which are the extreme probability method and the joint probability method, are examined at five different ports (Incheon, Cheju, Yeosu, Pusan, Mukho). The extreme probability mothod estimates the extreme sea levels from three different probability papers of Gumbel, Weibull and generalized extreme value(GEV) using the least square method, conventional moment method and probability weighted moment method. respectively. The results showed that the extreme sea levels estimated by the Gumbel paper or the least square method appeared higher than those calculated by other papers or methods. The extreme values estimated by the extreme probability method are approximately 5-10 cm lower than the values by the joint probability method.