• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.12
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• pp.1186-1192
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• 2008

The reliability of gas turbine engine blades was studied. Yield strength, Young’s modulus, engine speed and gas temperature were considered as statistically independent random variables. The failure probability was calculated using five different methods. Advanced Mean Value Method was the most efficient without significant loss in accuracy. When random variables were assumed to have normal, lognormal and Weibull distributions with the same means and standard deviations, the CDF of limit state equation did not change significantly with the distribution functions of random variables. The normalized sensitivity of failure probability with respect to standard deviations of random variables was the largest with gas temperature. The effect of means and standard deviations of random variables was studied. The increase in the mean of gas temperature and the standard deviation of engine speed increased the failure probability the most significantly.

• Journal of the Korean Society of Groundwater Environment
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• v.1 no.2
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• pp.90-99
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• 1994

Heterogeneous hydraulic conductivity in a flow domain is generated under the assumption that it is a random variable with a lognormal, spatially-correlated distribution. The hydraulic head and the conductivity in a groundwater flow system are represented as a stochastic process. The method of Monte Carlo Simulation (MCS) and the finite element method (FEM) are used to determine the statistics of the head and the logconductivity. The second moments of the head and the logconductivity indicate that the cross-covariance of the logconductivity with the head has characteristic distribution patterns depending on the properties of sources, boundary conditions, head gradients, and correlation scales. The negative cross-correlation outlines a weak-response zone where the flow system is weakly responding to a stress change in the flow domain. The stochastic approach has a potential to quantitatively delineate the zone of influence through computations of the cross-covariance distribution.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.1001-1009
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• 2019

Due to recent increasing heavy snow in Korea, the damage caused by heavy snow is also increasing. In Korea, there are many efforts including establishing disaster prevention measures to reduce the damage throughout the country, but it is difficult to establish the design criteria due to the characteristics of heavy snow. In this study, snowfall frequency analysis was performed to estimate design snow depths using observed snow depth data at Jinju, Changwon and Hapcheon stations. The conventional frequency analysis is sometime limted to apply to the snow depth data containing zero values which produce unrealistc estimates of distributon parameters. To overcome this problem, this study employed mixed distributions based on Lognormal, Generalized Pareto (GP), Generalized Extreme Value (GEV), Gamma, Gumbel and Weibull distribution. The results show that the mixed distributions produced smaller design snow depths than single distributions, which indicated that the mixed distributions are applicable and practical to estimate design snow depths.

• Korean Management Science Review
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• v.11 no.2
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• pp.1-27
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• 1994

A reliability data processing MPRDP (Multi-Purpose Reliability Data Processor) has been developed in FORTRAN language since Jan. 1992 at KAERI (Korean Atomic Energy Research Institute). The purpose of the research is to construct a reliability database(plant-specific as well as generic) by processing various kinds of reliability data in most objective and systematic fashion. To account for generic estimates in various compendia as well as generic plants' operating experience, we developed a 'three-stage' Bayesian procedure[1] by logically combining the 'two-stage' procedure[2] and the idea for processing generic estimates[3]. The first stage manipulates generic plant data to determine a set of estimates for generic parameters,e.g. the mean and the error factor, which accordingly defines a generic failure rate distribution. Then the second stage combines these estimates with the other ones proposed by various generic compendia (we call these generic book type data). This stage adopts another Bayesian procedure to determine the final generic failure rate distribution which is to be used as a priori distribution in the third stage. Then the third stage updates the generic distribution by plant-specific data resulting in a posterior failure rate distribution. Both running failure and demand failure data can be handled in this code. In accordance with the growing needs for a consistent and well-structured reliability database, we constructed a generic reliability database by the MPRDP code[4]. About 30 generic data sources were reviewed and available data were collected and screened from them. We processed reliability data for about 100 safety related components frequently modeled in PSA. The underlying distribution for the failure rate was assumed to be lognormal or gamma, according to the PSA convention. The dependencies among the generic sources were not considered at this time. This problem will be approached in further study.

• Structural Engineering and Mechanics
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• v.49 no.1
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• pp.111-128
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• 2014

The stochastic response surface method (SRSM) and the response surface method (RSM) are often used for structural reliability analysis, especially for reliability problems with implicit performance functions. This paper aims to compare these two methods in terms of fitting the performance function, accuracy and efficiency in estimating probability of failure as well as statistical moments of system output response. The computational procedures of two response surface methods are briefly introduced first. Then their capabilities are demonstrated and compared in detail through two examples. The results indicate that the probability of failure mainly reflects the accuracy of the response surface function (RSF) fitting the performance function in the vicinity of the design point, while the statistical moments of system output response reflect the accuracy of the RSF fitting the performance function in the entire space. In addition, the performance function can be well fitted by the SRSM with an optimal order polynomial chaos expansion both in the entire physical and in the independent standard normal spaces. However, it can be only well fitted by the RSM in the vicinity of the design point. For reliability problems involving random variables with approximate normal distributions, such as normal, lognormal, and Gumbel Max distributions, both the probability of failure and statistical moments of system output response can be accurately estimated by the SRSM, whereas the RSM can only produce the probability of failure with a reasonable accuracy.

• Earthquakes and Structures
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• v.14 no.4
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• pp.313-322
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• 2018

The present study is dedicated to investigate the SH body-as well as Love-waves propagation effects in porous media with uncertain porosity and permeability. A unified formulation of the governing equations for one-dimensional (1-D) wave propagation in anisotropic porous layered media is presented deterministically. The uncertainties around the above two cited parameters are taken into account by random fields with the help of Monte Carlo Simulations (MCS). Random samples of the porosity and the permeability are generated according to the normal and lognormal distribution functions, respectively, with a mean value and a coefficient of variation for each one of the two parameters. After performing several thousands of samples, the mathematical expectation (mean) of the solution of the wave propagation equations in terms of amplification functions for SH waves and in terms of dispersion equation for Love-waves are obtained. The limits of the Love wave velocity in a porous soil layer overlaying a homogeneous half-space are obtained where it is found that random variations of porosity change the zeros of the wave equation. Also, the increase of uncertainties in the porosity (high coefficient of variation) decreases the mean amplification function amplitudes and shifts the fundamental frequencies. However, no effects are observed on both Love wave dispersion and amplification function for random variations of permeability. Lastly, the present approach is applied to a case study in the Adapazari town basin so that to estimate ground motion accelerations lacked in the fast-growing during the main shock of the damaging 1999 Kocaeli earthquake.

• Ocean and Polar Research
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• v.36 no.4
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• pp.319-326
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• 2014

Mineral dust in the polar snow plays an important role both in the climate system of the Earth and in global biogeochemical cycles. Analysis of the concentration and the particle size distribution of mineral dust has been carried out in the snow from the Antarctic surface snow and the Greenland snowpit. Among the various particle size determination techniques, a Multisizer 3 Coulter Counter in a class 100 clean bench counted all particles between 1.1 and $30.0{\mu}m$ with a $50{\mu}m$ aperture tube. The aperture tube size, the concentration of electrolytes and the accuracy of the particle size distribution were determined in this study. The number concentrations from the Antarctic surface snow were 81,843 particles $mL^{-1}$, but those from the Greenland snowpit were 10,666 particles $mL^{-1}$. In the volume distribution, the distributions of mineral dust in both the Antarctic surface snow and the Greenland snowpit showed lognormal distribution in the size interval 1.1 to $6.0{\mu}m$ with the mode, 3.562 and $3.836{\mu}m$, respectively. The analysis technique using a coulter counter for mineral dust could be used for reconstructing paleoclimates from polar ice cores.

• Korean Journal of Environment and Ecology
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• v.11 no.2
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• pp.160-165
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• 1997

The objective of this study was to analyze dominance-diversity of Quercus mongolica community which characterize the boreal-temperate deciduous forest in Korea. Employing the releve method of Muller-Domboes and Ellenberg, 100 quadrats were sampled in the natural forest of Mt. Odae, Mt. Chumbong and Mt. Jungwang in Kangwon-do, where Quercus mongolica community is in the situation of climax or subclimax. On the basis of Braun-Blanquet method, field survey, which accounts ffor the characters of the species structure of Quercus mongolica community, was carried out between 1991 and 1994. Quercus mongolica community was relatively in a stable condition because of the even distribution of its various indices: the species diversity index was 0.4~1.2; the species richness index was 2~11; the evenness index was 0.6~0.9. The dominance-diversity curve were comparatively of lognormal distrivution with a gentle slope in all communities. The species sewuence curve for Quercus mongolica - Lindera obtusiloba community had relatively a steep slope, which meant that the evenness of the community would be low. The species sequence curve for Quercus mongolica - Carpinus cordata community had a slow slope, which meant that the evenness and the stability of the community would be high.

• Journal of the Korean Geotechnical Society
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• v.28 no.2
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• pp.43-55
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• 2012

In this study, the resistance bias factors are calculated to determine the resistance factor of Gravel Compaction Piles which is one of the soft ground improvement methods. In order to calculate resistance bias factors for gravel compaction piles, two ultimate bearing capacities were analyzed. One is the ultimate bearing capacity in 2.54 cm settlement measured using data of the field loading test on 41 piles and the other is the ultimate bearing capacity calculated using the seven equations concerning bulging failure. The results of analysis show that the probability density function of the calculated ultimate bearing capacities has a lognormal distribution. Resistance bias factor and the coefficient of variation for Greenwood equation are 0.91 and 0.38, respectively, and for those of Hughes & Withers are 1.19 and 0.39. The two equations are suitable for calculating resistance factors for LRFD of soil improvement using gravel compaction piles.

• Journal of the Earthquake Engineering Society of Korea
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• v.21 no.6
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• pp.277-286
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• 2017

On September 12, 2016, Gyeongju earthquake occurred. Its local magnitude was announced to be $M_L=5.8$ by Korea Meteorological Administration (KMA). Ground motion data recorded at KMA, EMC and KERC stations was obtained from their data bases. From the data, horizontal and vertical response spectra, and V/H ratio were calculated. The horizontal spectrum was defined as geometric mean spectrum, GMRotI50. From the statistical analysis of the geometric mean spectra, a mean plus one standard deviation spectrum in lognormal distribution is obtained. Regression analysis is performed on this curve to determine the shape of spectrum including transition periods. Applying the same procedure, the shape and transition periods of vertical spectrum was obtained. These results were compared with the Korean standard design spectra, which were developed from domestic and overseas intraplate earthquake records. The response spectra of Gyeongju earthquake were found to be almost identical with the newly proposed design spectra. Even the V/H ratios showed good agreement. These results confirmed that the method adopted when developing the standard design spectra were valid and the developed design spectra were reliable.