• Computational Structural Engineering
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• v.2 no.2
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• pp.93-99
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• 1989

Since 1960's, structural engineers have recognized that the inherent random nature of loadings and materials as well as the imperfect structural analysis may be important factors in the structural safety evaluation. Based on the successful developments of the reliability-based structural analysis and design, the design criteria of the standards are recently developed(or modified) in the light of the probabilistic concepts. To develop the probability - based criteria for the domestic buildings, the probabilistic characteristic of loadings acting on structures should be defined first. In this study, therefore, live load data on apartment buildings have been collected and analyzed in systematic manner, and their probabilistic characteristics have been studied. Based on the results, the lifetime extreme values are computed and compared with current design loads. More rational design loads are suggested, which are more consistent in the probabilistic concepts.

• The Journal of Engineering Geology
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• v.8 no.2
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• pp.145-152
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• 1998

• Proceedings of the Korean Nuclear Society Conference
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• 1999.10a
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• pp.341.2-341
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• 1999

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.1
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• pp.63-69
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• 2015

The primary aim of this paper is to evaluate the probabilistic fatigue crack propagation models using the residual of a random variable and to present the probabilistic model fit for the probabilistic fatigue crack growth behavior in Mg-Al-Zn alloys under maximum load conditions. The models used in this study were prepared by applying a random variable to empirical fatigue crack propagation models such as the Paris-Erdogan model, Walker model, Forman model, and modified Forman model. It was verified that the good models for describing the stochastic variation of the fatigue crack propagation behavior in Mg-Al-Zn alloys under maximum load conditions were the 'probabilistic Paris-Erdogan model' and 'probabilistic Walker model'. The influence of the maximum load conditions on the stochastic variation of fatigue crack growth is also considered.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.197-197
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• 2016

Forecasting future drought events in a region plays a major role in water management and risk assessment of drought occurrences. The creeping characteristics of drought make it possible to mitigate drought's effects with accurate forecasting models. Drought forecasts are inevitably plagued by uncertainties, making it necessary to derive forecasts in a probabilistic framework. In this study, a new probabilistic scheme is proposed to forecast droughts, in which a discrete-time finite state-space hidden Markov model (HMM) is used aggregated with the Representative Concentration Pathway 8.5 (RCP) precipitation projection (HMM-RCP). The 3-month standardized precipitation index (SPI) is employed to assess the drought severity over the selected five stations in South Kore. A reversible jump Markov chain Monte Carlo algorithm is used for inference on the model parameters which includes several hidden states and the state specific parameters. We perform an RCP precipitation projection transformed SPI (RCP-SPI) weight-corrected post-processing for the HMM-based drought forecasting to derive a probabilistic forecast that considers uncertainties. Results showed that the HMM-RCP forecast mean values, as measured by forecasting skill scores, are much more accurate than those from conventional models and a climatology reference model at various lead times over the study sites. In addition, the probabilistic forecast verification technique, which includes the ranked probability skill score and the relative operating characteristic, is performed on the proposed model to check the performance. It is found that the HMM-RCP provides a probabilistic forecast with satisfactory evaluation for different drought severity categories, even with a long lead time. The overall results indicate that the proposed HMM-RCP shows a powerful skill for probabilistic drought forecasting.

• Journal of the Korean Geotechnical Society
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• v.26 no.9
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• pp.25-35
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• 2010

Settlement at reclamation area caused by secondary compression should be considered using spatial evaluating method because the thickness of consolidation layer varies at every location. Probabilistic method can be implemented to evaluate uncertainty of spatial distribution of secondary compression. This study spatially evaluated mean and standard deviation of secondary compression in the overall analyzing region using spatial distribution of consolidation thickness estimated by ordinary kriging method and statistical values of soil properties. And then, the area where secondary compression exceeds a design criterion at the specific time was evaluated using probabilistic method. It was observed that the area exceeding the design criterion increased as the variability of $C_{\alpha}/(1+e_o)$ increased or the probabilistic design criterion 0: decreased. It is considered that the probabilistic method can be used for the geotechnical design of soft ground when a probabilistic design criterion is established in the specification.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.9
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• pp.384-391
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• 2006

The harmonic currents generated along with the operating speed of electrical railroad traction are very difficult to analyze because of its nonlinear characteristics. This paper therefore presents probabilistic approach for the evaluation of harmonic currents about the operating speed of the arbitrary single traction. To use probabilistic method for railroad system, PDF(Probability Density Function) using measuring data based on the realistic h 따 monic currents per operating speed is calculated. Measuring data of harmonic current per operating speed is obtained using the result data of PSCAD/EMTDC dynamic simulation based on an IAT(Intra Airport Transit) in Incheon International Airport. The means(expected values) and variances of harmonic currents of single traction also are obtained by the PDF of the operating traction speed and harmonic currents. The uncertainty of harmonic currents can be calculated through the mean and variance of PDF. The probability of harmonic currents generated with the operating of arbitrary many tractions is calculated by the convolution of functions. The harmonics of different number of tractions are systematically investigated to assess the TDD(Total Demand Distortion) for the railroad system. The calculation of TDD was carried out using Monte-Carlo Simulations(MSCs) and the results of TDD evaluation of the power quality in the IAT power feeding system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.3
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• pp.163-172
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• 1993

A probabilistic approach for evaluation of prediction of the strains using Lade's single surface constitutive model was employed, based on first-order approximate mean and variance. Several experiments such as isotropic compression and drained triaxial compression tests were conducted to examine the variabilities of soil parameters for Lade's model. By taking into account the results of the experimental data such as mean values and standard deviations of soil parameter's, a new probabilistic approach, which explains the uncertainty of computed strains, is applied. The magnitude of the COV for each parameter and the correlation coefficient between the two parameters can be effectively used for reducing the number of the parameters for the model. It is concluded that Lade's single surface constitutive model is surperior model for the prediction of the strain, because the COV of strains is under the "0.51".

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.128-138
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• 2008

VE of the scripture season enterprises and it respected LCC analyzes from the research which it sees and to use AHP techniques and definite LCC techniques and probabilistic LCC techniques selects the optimum route the case study which it executed. It presented the quality rating model in about the resultant most route lascivious at the time of VE evaluation, in order to select the alternative of optimum AHP techniques which are one in decision-making technique and an evaluation item by weight and a grade it applied the mountaintop it did. Also the definite LCC analyzer law departments of existing together it applied the probabilistic LCC techniques which use Monte Carlo Simulation in about analytical prices and reliability height boil. The economical efficiency was excellent with VE/LCC analytical resultant route and facility size abridgment, the rivers most it will be able to minimize an environmental effect with short distance traverse, the selection this hit preparation LCC which separates from the land use side decreased, the value (V) above 22.0% with the fact that it improves. And, the reliability of the probabilistic LCC analytical resultant analytical results in compliance with Monte Carlo Simulation with 90.3% was very analyzed with the fact that it is a high level.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.486-495
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• 2009

This paper proposes a new methodology on reliability evaluation of a power system including solar cell generators (SCG). The SCGs using renewable energy resource such as solar radiation(SR) should be modeled as multi-state operational model because the uncertainty of the resource supply may occur an effect as same as the forced outage of generator in viewpoint of adequacy reliability of system. While a two-state model is well suited for modeling conventional generators, a multi-state model is needed to model the SCGs due to the random variation of solar radiation. This makes the method of calculating reliability evaluation indices of the SCG different from the conventional generator. After identifying the typical pattern of the SR probability distribution function(pdf) from SR actual data, this paper describes modelling, methodology and details process for reliability evaluation of the solar cell generators integrated with power system. Two test results indicate the viability of the proposed method.