• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.78-82
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• 2004

This paper suggests the power system reliability evaluation fur transmission lines planning in composite power systems. In recent the importance and necessity of some studies on reliability evaluation of grid comes from the recent black-out accidents occurred in the world. Since probabilistic criterion can reflect recognize the probabilistic nature of system components, the application of probabilistic criterion has received a lot of attention. This paper introduces features and operation modes of the Transmission Reliability Evaluation fur Large-Scale Systems(TRELSS) Version 6.2, a program made in EPRI, for assessing reliability indices of composite power system. The characteristics of the TRELSS program are illustrated by the case studies using the KEPCO system.

• Smart Structures and Systems
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• v.20 no.2
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• pp.207-217
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• 2017

Because of the inevitable uncertainties such as structural parameters, external excitations and measurement noises, the effects of uncertainties should be taken into consideration in structural damage detection. In this paper, two probabilistic structural damage detection approaches are proposed to account for the underlying uncertainties in structural parameters and external excitation. The first approach adopts the statistical moment-based structural damage detection (SMBDD) algorithm together with the sensitivity analysis of the damage vector to the uncertain parameters. The approach takes the advantage of the strength SMBDD, so it is robust to measurement noise. However, it requests the number of measured responses is not less than that of unknown structural parameters. To reduce the number of measurements requested by the SMBDD algorithm, another probabilistic structural damage detection approach is proposed. It is based on the integration of structural damage detection using temporal moments in each time segment of measured response time history with the sensitivity analysis of the damage vector to the uncertain parameters. In both approaches, probability distribution of damage vector is estimated from those of uncertain parameters based on stochastic finite element model updating and probabilistic propagation. By comparing the two probability distribution characteristics for the undamaged and damaged models, probability of damage existence and damage extent at structural element level can be detected. Some numerical examples are used to demonstrate the performances of the two proposed approaches, respectively.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.9
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• pp.431-439
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• 2001

This Paper illustrates a new numerical analysis method using a 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(composite power system effective load duration curve) based on the new effective load model at HLll(Hierarchical Level H) has been developed also. The CMELDC can be obtained 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 HLll 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 MRBTS(Modified Roy Billinton Test System).

• 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.

• Journal of the Korean Geotechnical Society
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• v.18 no.2
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• pp.97-105
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• 2002

Random properties of discontinuities were attributed to the limitation of test methods and lack of obtained data. Therefore, the uncertainties are pervasive and inevitable in rock slope engineering as well as other geotechnical engineering fields. The probabilistic analysis has been proposed to deal properly with the uncertainty. However, previous probabilistic approaches do not take account of the condition of kinematic instability but consider only kinetic instability. In this study, in order to overcome the limitation of the previous studies, the geometric characteristics as well as the shear strength characteristics in discontinuities are taken account into the probabilistic analysis. Then, the new approach to evaluate the probability of failure is suggested. The results of the deterministic analysis which was carried out to compare with the result of the probabilistic analysis, are somewhat different from those of the probabilistic approach. This is because the selected and used data in the deterministic approach do not take account of the random properties of discontinuities.

• The Journal of the Acoustical Society of Korea
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• v.16 no.6
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• pp.94-99
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• 1997

This paper describes a technique of probabilistic spectral subtraction which uses the knowledge of both noise and speech so as to reduce automatic speech recognition errors in noisy environments. Spectral subtraction method estimates a noise prototype in non-speech intervals and the spectrum of clean speech is obtained from the spectrum of noisy speech by subtracting this noise prototype. Thus noise can not be suppressed effectively using a single noise prototype in case the characteristics of the noise prototype are different from those of the noise contained in input noisy speech. To modify such a drawback, multiple noise prototypes are used in probabilistic subtraction method. In this paper, the probabilistic characteristics of noise and the knowledge of speech which is embedded in hidden Markov models trained in clean environments are used to suppress noise. Futhermore, dynamic feature parameters are considered as well as static feature parameters for effective noise suppression. The proposed method reduced error rates in the recognition of 50 Korean words. The recognition rate was 86.25% with the probabilistic subtraction, 72.75% without any noise suppression method and 80.25% with spectral subtraction at SNR(Signal-to-Noise Ratio) 10 dB.

• Journal of Applied Reliability
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• v.18 no.3
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• pp.271-279
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• 2018

Purpose: Probabilistic safety analysis was performed to enhance the safety and reliability of nuclear power plants because traditional deterministic approach has limitations in predicting the risk of failure by crack growth. The study introduces a probabilistic approach to establish a basis for probabilistic safety assessment of passive components. Methods: For probabilistic modeling of fatigue crack growth rate (FCGR), various FCGR tests were performed either under constant load amplitude or constant ${\Delta}K$ conditions by using heat treated X-750 at low temperature with adequate cathodic polarization. Bayesian inference was employed to update uncertainties of the FCGR model using additional information obtained from constant ${\Delta}K$ tests. Results: Four steps of Bayesian parameter updating were performed using constant ${\Delta}K$ test results. The standard deviation of the final posterior distribution was decreased by a factor of 10 comparing with that of the prior distribution. Conclusion: The method for developing a probabilistic crack growth model has been designed and demonstrated, in the paper. Alloy X-750 has been used for corrosion fatigue crack growth experiments and modeling. The uncertainties of parameters in the FCGR model were successfully reduced using the Bayesian inference whenever the updating was performed.

• 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 GEO-environmental Society
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• v.13 no.11
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• pp.81-91
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• 2012

This paper mainly deals with the analysis of probabilistic characteristics of the disturbed function proposed to predict dynamic behavior of Geosynthetic-soil interface as the lining and cover systems used in waste landfills. Calibration and statistical property estimation of the parameters in the disturbed function model were first performed using many experimental data obtained from a new multi-purpose interface apparatus (M-PIA). In order to analyze the effect due to changes in chemical degradation and normal loads condition, probabilistic properties such as mean, coefficient of variation and distribution type of the disturbed function were evaluated using both the LHS method known to be a very efficient sampling scheme and the estimated statistical property of A and Z. As a result, variation of the disturbed function is found to range approximately from 10~28% according to the level of ${\xi}_D$ and Weibull appears to be the most adequate distribution type at almost all levels of ${\xi}_D$. It is concluded that a probabilistic safety assessment method for Geosynthetic-soil interface considering uncertainty in shear strength can be developed by utilizing probabilistic properties of the disturbed function obtained in this study.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.4
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• pp.449-456
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• 2021

Impatience characteristics are an important factor to be considered in the defense field, which is sensitive to time, but there are not many cases applied. In addition, due to the difficulty of analysis that must consider various probabilistic factors (breakdown/maintenance distribution, impatience characteristics, etc.), military decision makers consider only simple data (number of occurrences per year, maintenance time, etc.) Therefore, in this study, a model capable of analyzing the performance of the emergency maintenance system for determining the appropriate size and organization of military and civilian maintenance personnel was presented in consideration of impatience characteristics and probabilistic factors. And through numerical analysis, the appropriate size of the military and civilian emergency maintenance teams was analyzed. This study is significant in that it can improve readiness of operational power and prevent waste of defense budget through efficient operation of the military's emergency maintenance system.