• Journal of the Earthquake Engineering Society of Korea
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• v.19 no.2
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• pp.63-74
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• 2015

This study investigated the influence of probabilistic variability in stiffness and nonlinearity of soil on response of nuclear power plant (NPP) structure subjected to seismic loads considering the soil-structure interaction (SSI). Both deterministic and probabilistic methods have been employed to evaluate the dynamic responses of the structure. For the deterministic method, $SRP_{min}$ method given in USNRC SRP 3.7.2(2013) (envelope of responses using three shear modulus profiles of lower bound($G_{LB}$), best estimate($G_{BE}$) and upper bound($G_{UB}$)) and $SRP_{max}$ method (envelope of responses by more than three ground profiles within range of $G_{LB}{\leq}G{\leq}G_{UB}$) have been considered. The probabilistic method uses the Latin Hypercube Sampling (LHS) that can capture probabilistic feature of soil stiffness defined by the median and the standard deviation. These analysis results indicated that 1) number of samples shall be larger than 60 to apply the probabilistic approach in SSI analysis and 2) in-structure response spectra using equivalent linear soil profiles considering the nonlinear behavior of soil medium can be larger than those based on low-strain soil profiles.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.1
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• pp.11-20
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• 2014

Many classification studies for the community of densely-connected nodes are limited to the comprehensive analysis for detecting the communities in probabilistic networks with nodes and edge of the probabilistic distribution because of the difficulties of the probabilistic operation. This study aims to use convolution method for operating nodes and edge of probabilistic distribution. For the probabilistic hierarchy network with nodes and edges of the probabilistic distribution, the model of this study detects the communities of nodes to make the new probabilistic distribution with two distribution. The results of our model was verified through comparing with Monte-carlo Simulation and other community-detecting methods.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.707-714
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• 2009

The design response spectrum generally used in Korea is decided by the site coefficients determined by deterministic methodology, while it is based on probabilistic seismic hazard analysis. The design response spectrum has to be made using probabilistic method which includes uncertainties of ground motions and ground properties for coincide with probabilistic methodology of seismic hazard analysis. In this study probabilistic site coefficients were developed, which were defined by the results of site response analysis using a set of ground motion that was compatible with present seismic hazard map. The design response spectrum defined by probabilistic seismic coefficients resulted in lower spectrum in long period area and larger spectrum in short period area. Also, the maximum spectral accelerations in site class D and site class E were lower than one in site class C while in the previous design response spectrum the maximum spectral acceleration increased from site class A to E.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.637-644
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• 2010

This paper presents a reliability-based shape optimization (RBSO) using the growth-strain method. An actual design involves uncertain conditions such as material property, operational load, Poisson's ratio and dimensional variation. The purpose of the RBSO is to consider the variations of probabilistic constraint and performances caused by uncertainties. In this study, the growth-strain method was applied to shape optimization of reliability analysis. Even though many papers for reliability-based shape optimization in mathematical programming method and ESO (Evolutionary Structural Optimization) were published, the paper for the reliability-based shape optimization using the growth-strain method has not been applied yet. Growth-strain method is applied to performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints in the change of average mises stress. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization. It was verified that the reliability-based shape optimization using growth-strain method are very effective for general structure. The purpose of this study is to improve structure's safety considering probabilistic variable.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.444-449
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• 2009

This paper introduces a method to establish performance criteria of the in-house power supply system in nuclear power plants. The performance criteria of the system is presented in terms of the number of function failures and amount of the out-of-service time that can be allowed commensurate with the probabilistic safety assessment results of the nuclear power plants. To obtain the performance criteria such as reliability and availability, the functions of the system were analyzed and probabilistic assessment results were utilized. This method provides quantitative guidelines in selecting and monitoring system functions to determine an adequate level of maintenance quality in order to ensure the probabilistic goals for the safety of the nuclear power plants.

• Communications for Statistical Applications and Methods
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• v.24 no.1
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• pp.67-80
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• 2017

Over the last few decades, ensemble forecasts based on global climate models have become an important part of climate forecast due to the ability to reduce uncertainty in prediction. Moreover in ensemble forecast, assessing the prediction uncertainty is as important as estimating the optimal weights, and this is achieved through a probabilistic forecast which is based on the predictive distribution of future climate. The Bayesian model averaging has received much attention as a tool of probabilistic forecasting due to its simplicity and superior prediction. In this paper, we propose a new Bayesian model averaging method for probabilistic ensemble forecasting. The proposed method combines a deterministic ensemble forecast based on a multivariate regression approach with Bayesian model averaging. We demonstrate that the proposed method is better in prediction than the standard Bayesian model averaging approach by analyzing monthly average precipitations and temperatures for ten cities in Korea.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.113-115
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• 2003

The electric power industry throughout the world is undergoing considerable changes from the vertically integrated utility structure to the deregulated market. However, the deregulated electricity market is operated with respect to theory of economical efficiency, and therefore, the system operator requires data with fast contingency ranking for security of the bulk power system. This paper presents fast calculation method for determining contingency ranking using the weather dependant probabilistic risk index(PRI). The probabilistic risk index can be classified into normal weather and adverse weather. This paper proposes calculation method using the probabilistic risk index in determining contingency ranking requiring for security under the deregulated electricity market.

• ETRI Journal
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• v.33 no.6
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• pp.924-934
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• 2011

Sensor networks play an important role in making the dream of ubiquitous computing a reality. With a variety of applications, sensor networks have the potential to influence everyone's life in the near future. However, there are a number of issues in deployment and exploitation of these networks that must be dealt with for sensor network applications to realize such potential. Localization of the sensor nodes, which is the subject of this paper, is one of the basic problems that must be solved for sensor networks to be effectively used. This paper proposes a probabilistic support vector machine (SVM)-based method to gain a fairly accurate localization of sensor nodes. As opposed to many existing methods, our method assumes almost no extra equipment on the sensor nodes. Our experiments demonstrate that the probabilistic SVM method (PSVM) provides a significant improvement over existing localization methods, particularly in sparse networks and rough environments. In addition, a post processing step for PSVM, called attractive/repulsive potential field localization, is proposed, which provides even more improvement on the accuracy of the sensor node locations.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.299-302
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• 2008

The behavior of continuous welded rail tracks is directly affected by the following various parameters: rail size; track curvature; neutral temperature; misalignment; and ballast resistance. Most of these parameters are having the nature of random variables. Therefore, uncertainties exist in the buckling safety assessments. The evaluation of the buckling safety and the maintenance strategy based on the deterministic analysis are very inefficient since the value of deterministic parameters are selected in worst track condition. In this study, the probabilistic approach method were investigated considering the probabilistic distribution of major parameters such as the neutral temperature of rail and the ballast resistance.

• East Asian mathematical journal
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• v.24 no.1
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• pp.27-33
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• 2008

The purpose of this paper is to establish the weak convergence theorem of Mann iterative sequence for nonexpansive mappings in probabilistic Hilbert spaces. In order to establish the weak convergence theorem, a new method was presented in this paper, that is method of mathematical expectation.