• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.112-115
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• 2001

This paper illustrates a new nodal effective load model for nodal probabilistic production cost simulation of the load point in a composite power system. The new effective load model includes capacities and uncertainties of generators as well as transmission lines. The CMELDC based on the new effective load model at HLII has been developed also. The CMELDC can be obtain from convolution integral processing of the outage capacity probabilistic distribution function of the fictitious generator and the original load duration curve given at the load point. It is expected that the new model for the CMELDC proposed. In this study will provide some solutions to many problems based on nodal and decentralized operation and control of an electric power systems under competition environment in future. The CMELDC based on the new model at HLII will extend the application areas of nodal probabilistic production cost simulation, outage cost assessment and reliability evaluation etc. at load points. The characteristics and effectiveness of this new model are illustrated by a case study of a test system.

• KSBB Journal
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• v.21 no.4
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• pp.231-235
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• 2006

This study is a numerical representative modeling analysis for the application of the process that unravels networks between cells in genetics to web of informatics. Using the probabilistic graphical model, the insight from the data describing biological networks is used for making a probabilistic function. Rather than a complex network of cells, we reconstruct a simple lower-stage model and show a genetic representation level from the genetic based network logic. We made probabilistic graphical models from genetic data and extends them to genetic representation data in the method of network modeling in informatics

• Journal of the Korean Society for Precision Engineering
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• v.22 no.10 s.175
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• pp.137-143
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• 2005

The integrity of steam generator tubes in nuclear power plant should be maintained sufficiently during operation. For sake of this, complicated assessment procedures are required such as fracture mechanics analysis, etc. The integrity assessment of tubes has been performed by using conventional deterministic approaches while there are many uncertainties to carry out a rational evaluation. In this respect, probabilistic integrity assessment is considered as an alternative method for integrity assessment. The objectives of this study are to develop an integrity assessment system based on probabilistic fracture mechanics and to predict the failure probability of steam generator tubes containing an axial through-wall crack. The developed integrity assessment system consists of three evaluation modules, which apply first order reliability method, second order reliability method and Monte Carlo simulation method, respectively. The system has been applied to predict failure probability of steam generator tubes and the estimation results showed a promising applicability of the probabilistic integrity assessment system.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.10 s.175
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• pp.158-166
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• 2005

Pressurized gas pipeline is subject to harmful effects both of the surrounding environment and of the materials transmitted in them. In order to maintain the integrity, reliable assessment procedures including tincture mechanics analysis etc are required. Up to now, the integrity assessment has been performed using conventional deterministic approaches even though there are many uncertainties to hinder a rational evaluation. In this respect, probabilistic approach is considered as an appropriate method for gas pipeline evaluation. The objectives of this paper are to estimate the failure probability of corroded pipeline in gas and oil plants and to propose limited operating conditions under different types of leadings. To do this, a probabilistic assessment program using reliability index and simulation techniques was developed and applied to evaluate failure probabilities of corroded API-5L-X52/X60 gas pipelines subjected to internal pressure, bending moment and combined loading. The evaluation results showed a promising applicability of the probabilistic integrity assessment program.

• Nuclear Engineering and Technology
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• v.47 no.3
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• pp.306-314
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• 2015

This paper examines the difference in the value of the nuclear fuel cycle cost calculated by the deterministic and probabilistic methods on the basis of an equilibrium model. Calculating using the deterministic method, the direct disposal cost and Pyro-SFR (sodium-cooled fast reactor) nuclear fuel cycle cost, including the reactor cost, were found to be 66.41 mills/kWh and 77.82 mills/kWh, respectively (1 mill = one thousand of a dollar, i.e., $10^{-3}$ $). This is because the cost of SFR is considerably expensive. Calculating again using the probabilistic method, however, the direct disposal cost and Pyro-SFR nuclear fuel cycle cost, excluding the reactor cost, were found be 7.47 mills/kWh and 6.40 mills/kWh, respectively, on the basis of the most likely value. This is because the nuclear fuel cycle cost is significantly affected by the standard deviation and the mean of the unit cost that includes uncertainty. Thus, it is judged that not only the deterministic method, but also the probabilistic method, would also be necessary to evaluate the nuclear fuel cycle cost. By analyzing the sensitivity of the unit cost in each phase of the nuclear fuel cycle, it was found that the uranium unit price is the most influential factor in determining nuclear fuel cycle costs.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.5
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• pp.649-656
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• 2011

This study is a numerical representative modelling analysis for applying the process that unravels networks between cells in genetics to Network of informatics. Using the probabilistic graphical model, the insight from the data describing biological networks is used for making a probabilistic function. Rather than a complex network of cells, we reconstruct a simple lower-stage model and show a genetic representation level from the genetic based network logic. We made probabilistic graphical models from genetic data and extend them to genetic representation data in the method of network modelling in informatics.

• Computers and Concrete
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• v.3 no.2_3
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• pp.123-144
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• 2006

Reinforced concrete corbels are structural elements widely used in practical engineering. The complex response of these elements is described in design codes in a simplified manner. These formulations are not sufficient to show the real behavior, which, however, is an essential prerequisite for the manufacturing of numerous elements. Therefore, a deterministic and probabilistic study has been performed, which is described in this contribution. Real complex structures have been modeled by means of the finite element method supported primarily by experimental works. The main objective of this study was the detection of uncertainties effects and safety margins not captured by traditional codes. This aim could be fulfilled by statistical considerations applied to the investigated structures. The probabilistic study is based on advanced Monte Carlo simulation techniques and sophisticated nonlinear finite element formulations.

• Wind and Structures
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• v.30 no.4
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• pp.405-421
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• 2020

Quayside container cranes are important delivery machineries located in the most frontiers of container terminals, where strong wind attacks happen occasionally. Since the previous researches on quayside container cranes mainly focused on the mean wind load and static response characteristics, the fluctuating wind load and dynamic response characteristics require further investigations. In the present study, the aerodynamic wind loads on quayside container cranes were obtained from wind tunnel tests. The probabilistic and spectral models of the fluctuating aerodynamic loads were established. Then the joint probabilistic distributions of dynamic wind-induced responses were derived theoretically based on a series of Gaussian and independent assumption of resonant components. Finally, the results were validated by time domain analysis using wind tunnel data. It is concluded that the assumptions are acceptable. And the presented approach can estimate peak dynamic sliding force, overturning moments and leg uplifts of quayside container cranes effectively and efficiently.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.461-470
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• 2014

This paper presents a probabilistic power flow (PPF) analysis method for distribution network incorporating the randomness and correlation of photovoltaic (PV) generation. Based on the multivariate kernel density estimation theory, the probabilistic model of PV generation is proposed without any assumption of theoretical parametric distribution, which can accurately capture not only the randomness but also the correlation of PV resources at adjacent locations. The PPF method is developed by combining the proposed PV model and Monte Carlo technique to evaluate the influence of the randomness and correlation of PV generation on the performance of distribution networks. The historical power output data of three neighboring PV generators in Oregon, USA, and 34-bus/69-bus radial distribution networks are used to demonstrate the correctness, effectiveness, and application of the proposed PV model and PPF method.

• Structural Engineering and Mechanics
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• v.34 no.1
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• pp.15-38
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• 2010

In order to predict the shear strengths of reinforced concrete beams, many deterministic models have been developed based on rules of mechanics and on experimental test results. While the constant and variable angle truss models are known to provide reliable bases and to give reasonable predictions for the shear strengths of members with shear reinforcement, in the case of members without shear reinforcement, even advanced models with complicated procedures may show lack of accuracy or lead to fairly different predictions from other similar models. For this reason, many research efforts have been made for more accurate predictions, which resulted in important recent publications. This paper develops probabilistic shear strength models for reinforced concrete beams without shear reinforcement based on deterministic shear strength models, understanding of shear transfer mechanisms and influential parameters, and experimental test results reported in the literature. Using a Bayesian parameter estimation method, the biases of base deterministic models are identified as algebraic functions of input parameters and the errors of the developed models remaining after the bias-correction are quantified in a stochastic manner. The proposed probabilistic models predict the shear strengths with improved accuracy and help incorporate the model uncertainties into vulnerability estimations and risk-quantified designs.