• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.3
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• pp.225-233
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• 2004

In this study, the seismic safety of containment building is assessed using response surface method. The structural analyses considering random variables such as load, resistance and analysis by ABAQUS are performed to obtain the structural response. The structural response is represented by polynomial of random variables, and the reliability analysis is performed by Level II method. Drucker-Prager failure criterion is applied as limit state function to take bi-axial stress states into account in the concrete. The lifetime probability of failure is evaluated by considering the lifetime of containment building, the annual occurrence rate of earthquake and the conditional probability of failure. Also the sensitivity analysis on the selection of sampling points is performed to obtain the steady results from response surface method.

• Nuclear Engineering and Technology
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• v.46 no.5
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• pp.699-706
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• 2014

The probabilistic seismic performance of a standard Korean nuclear power plant (NPP) with an idealized isolation is investigated in the present work. A probabilistic seismic hazard analysis (PSHA) of the Wolsong site on the Korean peninsula is performed by considering peak ground acceleration (PGA) as an earthquake intensity measure. A procedure is reported on the categorization and selection of two sets of ground motions of the Tohoku earthquake, i.e. long-period and common as Set A and Set B respectively, for the nonlinear time history response analysis of the base-isolated NPP. Limit state values as multiples of the displacement responses of the NPP base isolation are considered for the fragility estimation. The seismic risk of the NPP is further assessed by incorporation of the rate of frequency exceedance and conditional failure probability curves. Furthermore, this framework attempts to show the unacceptable performance of the isolated NPP in terms of the probabilistic distribution and annual probability of limit states. The comparative results for long and common ground motions are discussed to contribute to the future safety of nuclear facilities against drastic events like Tohoku.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.3
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• pp.103-108
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• 2007

This paper presents the conceptual framework for estimating and predicting system's susceptibility to failure as function of condition parameter value which is representing the current status of performance measure using on-line performance reliability. The performance of such system depends on one parameter with a probability distribution that degrades with time gracefully. Performance reliability represents the probability that physical performance will remain satisfactory over a finite period of time or usage cycles in the future. An empirical physical performance function is constructed to incorporate explanatory variables (operating and environmental conditions) over a time or usage dimension. This function enables one to model device performance and the associated classical reliability measures simultaneously, in the performance domain and time domain. The conditional performance reliability structure developed represents a tool to predict system performance over time or usage for next usage period. By enabling such a framework, it can bring us more efficient planning and execution in system's operation control as well as maintenance to reduce costs and/or increase profits.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1-5
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• 2009

Recently, as a method of green-development and reduction of carbon dioxide emission, increased interest has been focused on a railway. Furthermore, an intensive study has been processed on capabilities of maintenance activities, economic efficiency of maintenance on rail structure and a design of railway structure as well as the development of materials. The purpose of this paper is to develop a deteriorated model of PC Beam Bridge due to timely changes and maintenance activities. Typically, there is definite difference between maintained bridges and non-maintained bridges. As a result of proper maintenance activity, a life time of a structure can be enhanced. In this study, we will research and analyze structures with ongoing maintenance. We will also process same procedures on structures without maintenance. Therefore, we can establish the significant role in a conditional change of a structure. Based on a study, we accomplish the development of a condition-deteriorated model. To develop deteriorated model of PC Beam Bridge, We apply Marcov Theory and develop a transition probability to show the life time of bridge. This study will provide a great benefit to decision making for maintenance activities on the railway bridges for future.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.6
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• pp.641-649
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• 2010

Estimation of uncertain parameters is required in many engineering problems which involve probabilistic structural analysis as well as prognosis of existing structures. In this case, Bayesian framework is often employed, which is to represent the uncertainty of parameters in terms of probability distributions conditional on the provided data. The resulting form of distribution, however, is not amenable to the practical application due to its complex nature making the standard probability functions useless. In this study, Markov chain Monte Carlo (MCMC) method is proposed to overcome this difficulty, which is a modern computational technique for the efficient and straightforward estimation of parameters. Three case studies that implement the estimation are presented to illustrate the concept. The first one is an inverse estimation, in which the unknown input parameters are inversely estimated based on a finite number of measured response data. The next one is a metamodel uncertainty problem that arises when the original response function is approximated by a metamodel using a finite set of response values. The last one is a prognostics problem, in which the unknown parameters of the degradation model are estimated based on the monitored data.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.169-174
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• 2018

In general, the methods of the analysis of variance(ANOVA) for the continuous data and the chi-square test for the discrete data are used for statistical analysis of the effect and the association. In multidimensional data, analysis of hierarchical structure is required and statistical linear model is adopted. The structure of the linear model requires the normality of the data. A multidimensional categorical data analysis methods are used for causal relations, interactions, and correlation analysis. In this paper, Bayesian network model using probability distribution is proposed to reduce analysis procedure and analyze interactions and causal relationships in categorical data analysis.

• Journal of the military operations research society of Korea
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• v.28 no.2
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• pp.70-84
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• 2002

This paper deals with the attrition rate of major facility such as a particular building that is one of the most important target in the war time. In order to estimate the attrition rate, we use JAWS, WinJMEM which are programed by JTCG/ME of AMSAA and spreadsheet package which is able to assist the limitation of those programs and calculate all the procedure of this computation. This method uses the effectiveness index(El) which indicates the numerical measure of the effectiveness of a given weapon of a given target. The range error probable(REP) and the deflection error probable(DEP) in the ground plane also should be used. Those mean the measure of delivery accuracy of the weapon system. In this paper, it is improved that the El can be obtained from the regression analysis using the weight of the warhead explosive as the independent variable. It implies that we are able to obtain the El and the conditional probability of damage of the enemy weapon. After that, the single-sortie probability of damage can be computed using WinJMEM or another assistant program such as the spreadsheet package which shows the result immediately.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.948-958
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• 2022

Since reliability and security of man-machine system increasingly depend on reliability of human, human reliability analysis (HRA) has attracted a lot of attention in many fields especially in nuclear engineering. Dependence assessment among human tasks is a important part in HRA which contributes to an appropriate evaluation result. Most of methods in HRA are based on experts' opinions which are subjective and uncertain. Also, the dependence influencing factors are usually considered to be constant, which is unrealistic. In this paper, a new model based on Dempster-Shafer evidence theory (DSET) and fuzzy number is proposed to handle the dependence between two tasks in HRA under uncertain and dynamic situations. First, the dependence influencing factors are identified and the judgments on the factors are represented as basic belief assignments (BBAs). Second, the BBAs of the factors that varying with time are reconstructed based on the correction BBA derived from time value. Then, BBAs of all factors are combined to gain the fused BBA. Finally, conditional human error probability (CHEP) is derived based on the fused BBA. The proposed method can deal with uncertainties in the judgments and dynamics of the dependence influencing factors. A case study is illustrated to show the effectiveness and the flexibility of the proposed method.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1201-1208
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• 2010

In teaching probability and statistics classes, we should increase efforts to develop examples that enhance teaching methodology in delivering more meaningful knowledge to students. Sports is one field that provides a variety of examples and World Cup Soccer events are a treasure house of many interesting problems. Teaching, using examples from this field, is an effective way to enhance the interest of students in probability and statistics because World Cup Soccer is a matter of national interest. In this paper, we have suggested several examples pertaining to counting the number of cases and computing probabilities. These examples are related to many issues such as possible scenarios in the preliminary round, victory points necessary for each participant to advance to the second round, and the issue of grouping teams. Based on a simulation using a statistical model, we have proposed a logical method for computing the probabilities of proceeding to the second round and winning the championship for each participant in the 2010 South Africa World Cup.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.537-544
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• 2020

Advances in detection techniques, such as mutation and obfuscation, are being advanced with the development of malware technology. In the malware detection technology, unknown malware detection technology is important, and a method for Malware Authorship Attribution that detects an unknown malicious code by identifying the author through distributed malware is being studied. In this paper, we try to extract the compiler information affecting the binary-based author identification method and to investigate the sensitivity of feature selection, probability and non-probability models, and optimization to classification efficiency between studies. In the experiment, the feature selection method through information gain and the support vector machine, which is a non-probability model, showed high efficiency. Among the optimization studies, high classification accuracy was obtained through feature selection and model optimization through the proposed framework, and resulted in 48% feature reduction and 53 faster execution speed. Through this study, we can confirm the sensitivity of feature selection, model, and optimization methods to classification efficiency.