• Journal of the Korean Society for Precision Engineering
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• v.11 no.1
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• pp.192-200
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• 1994

The methodology of a simple probabilistic fatigue crack under random loading is proposed. Using the crack closure concept, the crack opening stress is assumed to be constant during random loading. The loading history was analyzed to determine the probability density functions, probability distribution functions and other related parameters for the probabilistic fatigue crack growth analysis. Fatigue crack growth using the exisiting available data was predicted by the proposed probabilistic analysis and compared with experimental data.

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.6 s.40
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• pp.23-29
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• 2004

The design earthquake used for the seismic analysis and design of NPP (Nuclear Power Plant) is determined by the deterministic or probabilistic methods. The probabilistic seismic hazard analysis(PSHA) for the nuclear power plant sites was performed for the probabilistic seismic risk assessment. The probabilistic seismic hazard analysis for the nuclear power plant site had been completed as a part of the probabilistic seismic risk assessment. The probabilistic method become a resonable method to determine the design earthquakes for NPPs. In this study, the defining method of the probability based scenario earthquake was established, and as a sample calculation, the probability based scenario earthquakes were estimated by the de-aggregation of the probabilistic seismic hazard. By using this method, it is possible to define the probability based scenario earthquakes for the seismic design and seismic safety evaluation of structures. It is necessary to develop the rational seismic source map and the attenuation equations for the development of reasonable scenario earthquakes.

• Advances in aircraft and spacecraft science
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• v.3 no.4
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• pp.503-521
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• 2016

Variances in turbomachinery blades caused by manufacturing, operation or regeneration can result in modified structural behavior. In this work, the scatter of geometrical and material properties of a turbine blade and its influence on structure performance is discussed. In particular, the vibration characteristics and the lifetime of a turbine blade are evaluated. Geometrical variances of the surface of the blades are described using the principal component analysis. The scatter in material properties is considered by 16 varying material parameters. Maximum vibration amplitudes and the number of load cycles the turbine blade can withstand are analyzed by finite element simulations incorporating probabilistic principles. The probabilistic simulations demonstrate that both geometrical and material variances have a significant influence on the scatter of vibration amplitude and lifetime. Dependencies are quantified and correlations between varied input parameters and the structural performance of the blade are detected.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.2
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• pp.95-101
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• 2018

The objective of this study is to evaluate the liquefaction cyclic shear stress ratio considering the soil uncertainty. In this study, the probabilistic ground response analysis and the cyclic shear stress ratio analysis for the liquefaction potential evaluation are performed considering the soil variability. The statistical properties of input ground parameters were analyzed to investigate the parameters affecting the seismic response analysis. The Probabilistic analysis was carried out by Monte Carlo Simulation method. The ground response analysis was performed considering the soil variability and the probability distribution characteristics of the ground acceleration. The probability distribution of the peak ground acceleration by seismic characteristics was presented. The differences of liquefaction shear stress ratio results according to soil variability were compared and analyzed. The maximum acceleration of the ground by the deterministic method was analyzed to be overestimation of the ground amplification phenomenon. Also, the shear stress ratio was overestimated.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.49-58
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• 2004

In this talk we proposed an asymptotic test for dimensionality in the latent variable model for probabilistic principal component analysis with missing values at random. Proposed algorithm is a sequential likelihood ratio test for an appropriate Normal latent variable model for the principal component analysis. Modified EM-algorithm is used to find MLE for the model parameters. Results from simulations and real data sets give us promising evidences that the proposed method is useful in finding necessary number of components in the principal component analysis with missing values at random.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.6
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• pp.93-101
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• 2007

In general, geotechnical properties have many uncertain aspects, thus probabilistic analysis have been used to consider these aspects. It is, however, quite difficult to select an appropriate target probability for a certain structure or construction process. In this study, minimum expected cost design method based on probabilistic analysis is suggested for design of vertical drains generally used to accelerate consolidation in soft clayey soils. A sensitivity analysis is performed to select the most important uncertain parameters for the design of vertical drains. Monte Carlo simulation is used in sensitivity analysis and probabilistic analysis. Total expected cost, defined as the sum of initial cost and expected additive cost, varies widely with variation of input parameters used in design of vertical drain systems. And probability of failure to get the minimum total expected cost varies under the different design conditions. A minimum value of total expected cost is suggested as a design value in this study. The proposed design concept is applicable to unit construction process because this approach is to consider the uncertainties using probabilistic analysis and uncertainties of geotechnical properties.

• Journal of the Korean Geotechnical Society
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• v.18 no.5
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• pp.271-280
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• 2002

A probabilistic approach to identify the effects of uncertainties of soil strength parameters on searching a critical slip surface with the lowest reliability is introduced. In general construction field, it is impossible for the engineer to always gather a variety of statistical information of soil strength parameters for which lots of laboratory and in-situ soil testing are required and to use it with enough statistical knowledge. Thus, in order that the engineer may easily understand the probabilistic concept for the slope stability analysis, this study proposes a combined procedure to incorporate the engineering probabilistic tools into the existing deterministic slope stability analysis methods. Using UTEXAS 3, a slope stability analysis computer program developed by U.S. Army Corps of Engineers (U.S. COE), this study provides the results of this probabilistic slope stability analysis in terms of probability of failure or reliability index. This probabilistic method f3r slope stability analysis appears to yield more comprehensive results of slope reliability than does existing deterministic methods with safety factors alone.

• The Magazine of the IEIE
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• v.36 no.11
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• pp.66-82
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• 2009

Probabilistic atlases for the human brain structure are more suitable than single brain atlases for representing population anatomy. In this study, we hypothesized the group-specific probabilistic atlas for accurate characteristic feature coding. Our proposed method for a new group comparison study, using a subpopulation specific probabilistic atlas, was based on this hypothesis. A knowledge-based automatic labeling technique using nonlinear registration was applied to encode group-specific regional probabilistic information. Direct atlas-based comparison using volume counting above the probability threshold, distance measurement and correlation analysis were performed based on the probabilistic atlas. Here, we applied this method for comparison between Korean and occidental groups. The results showed that this method could provide simple but intuitive regions of interest-based group analysis for the entire cortex area.

• Geomechanics and Engineering
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• v.18 no.6
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• pp.595-603
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• 2019

A modified model combining Kriging and Monte Carlo method (MC) is proposed for probabilistic estimation of tunnel face stability in this paper. In the model, a novel uniform design is adopted to train the Kriging, instead of the existing active learning function. It has advantage of avoiding addition of new training points iteratively, and greatly saves the computational time in model training. The kinematic approach of limit analysis is employed to define the deterministic computational model of face failure, in which the Hoek-Brown failure criterion is introduced to account for the nonlinear behaviors of rock mass. The trained Kriging is used as a surrogate model to perform MC with dramatic reduction of calls to actual limit state function. The parameters in Hoek-Brown failure criterion are considered as random variables in the analysis. The failure probability is estimated by direct MC to test the accuracy and efficiency of the proposed probabilistic model. The influences of uncertainty level, correlation relationship and distribution type of random variables are further discussed using the proposed approach. In summary, the probabilistic model is an accurate and economical alternative to perform probabilistic stability analysis of tunnel face excavated in spatially random Hoek- Brown media.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.12
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• pp.70-79
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• 2020

This paper describes a comparative study of characteristics of probabilistic design using various reliability analysis methods in the structure design of an automatic salt collector. The thickness sizing variables of the main structural member were considered to be random variables, including the uncertainty of corrosion, which would be an inevitable hazard in the work environment of the automatic salt collector. Probabilistic performance functions were selected from the strength performances of the automatic salt collector structure. First-order reliability method, second-order reliability method, mean value reliability method, and adaptive importance sampling method were applied during the reliability analyses. The probabilistic design performances such as reliability probability and numerical costs based on the reliability analysis methods were compared to the Monte Carlo simulation results. The adaptive importance sampling method showed the most rational results for the probabilistic structure design of the automatic salt collector.