• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2005.10a
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• pp.247-249
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• 2005

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.471-483
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• 1998

The influence of observations on the misclassification probability in multiple discriminant analysis under the equal covariance assumption is investigated by the local influence method. Under an appropriate perturbation we can get information about influential observations and outliers by studying the curvatures and the associated direction vectors of the perturbation-formed surface of the misclassification probability. We show that the influence function method gives essentially the same information as the direction vector of the maximum slope. An illustrative example is given for the effectiveness of the local influence method.

• Journal of Hydrogen and New Energy
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• v.19 no.3
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• pp.239-247
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• 2008

Hydrogen production facility using very high temperature gas cooled reactor lies in situation of high temperature and corrosion which makes hydrogen release easily. In that case of hydrogen release, there lies a danger of explosion. However, from the point of thermal-hydraulics view, the long distance of them makes lower efficiency result. In this study, therefore, outlines of hydrogen production using nuclear energy are researched. Several methods for analyzing the effects of hydrogen explosion upon high temperature gas cooled reactor are reviewed. Reliability physics model which is appropriate for assessment is used. Using this model, leakage probability, rupture probability and structure failure probability of very high temperature gas cooled reactor are evaluated and classified by detonation volume and distance. Also based on standard safety criteria which is value of $1{\times}10^{-6}$, safety distance between the very high temperature gas cooled reactor and the hydrogen production facility is calculated.

• Journal of Environmental Impact Assessment
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• v.22 no.6
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• pp.713-724
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• 2013

In terms of waste load allocation, inequality of waste load discharge must be considered as well as economic aspects such as minimization of waste load abatement. The inequality of waste load discharge between areas was calculated with Gini coefficient and was included as one of the objective functions of the multi-objective waste load allocation. In the past, multi-objective functions were usually weighted and then transformed into a single objective optimization problem. Recently, however, due to the difficulties of applying weighting factors, multi-objective genetic algorithms (GA) that require only one execution for optimization is being developed. This study analyzes multi-objective waste load allocation using NSGA-II-aJG that applies Pareto-dominance theory and it's adaptation of jumping gene. A sensitivity analysis was conducted for the parameters that have significant influence on the solution of multi-objective GA such as population size, crossover probability, mutation probability, length of chromosome, jumping gene probability. Among the five aforementioned parameters, mutation probability turned out to be the most sensitive parameter towards the objective function of minimization of waste load abatement. Spacing and maximum spread are indexes that show the distribution and range of optimum solution, and these two values were the optimum or near optimal values for the selected parameter values to minimize waste load abatement.

• Structural Engineering and Mechanics
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• v.81 no.4
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• pp.429-441
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• 2022

A probabilistic assessment of the seismic-excited buildings with a multiple-tuned-mass-damper (MTMD) system is carried out in the presence of uncertainties of the structural model, MTMD system, and the stochastic model of the seismic excitations. A free search optimization procedure of the individual mass, stiffness and, damping parameters of the MTMD system based on the snap-drift cuckoo search (SDCS) optimization algorithm is proposed for the optimal design of the MTMD system. Considering a 10-story structure in three cases equipped with single tuned mass damper (STMS), 5-TMD and 10-TMD, sensitivity analyses are carried out using Sobol' indices based on the Monte Carlo simulation (MCS) method. Considering different seismic performance levels, the reliability analyses are done using MCS and kriging-based MCS methods. The results show the maximum structural responses are more affected by changes in the PGA and the stiffness coefficients of the structural floors and TMDs. The results indicate the kriging-based MCS method can estimate the accurate amount of failure probability by spending less time than the MCS. The results also show the MTMD gives a significant reduction in the structural failure probability. The effect of the MTMD on the reduction of the failure probability is remarkable in the performance levels of life safety and collapse prevention. The maximum drift of floors may be reduced for the nominal structural system by increasing the TMDs, however, the complexity of the MTMD model and increasing its corresponding uncertainty sources can be caused a slight increase in the failure probability of the structure.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.226-234
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• 2003

Put Many researcher have made much progress in studying an estimate for fracture probability of brittle materials. However, studies of the fracture probability for the elastic-plasticity have not been made yet. An estimate method for fracture probability which is grafted onto 2-parameter criterion and statistical probability analysis is not only introduced in this study, but also applied to the simple 2dimensional model and carbon steel piping to evaluate the effect of random variable.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.310-315
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• 2003

This paper presents the effect of boundary condition of failure pressure model for buried pipelines on failure prediction by using a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with various corrosion defects for long exposure periods in years. A failure pressure model based on a failure function composed of failure pressure and operation pressure is adopted for the assessment of pipeline failure. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically studied by using a failure probability model for the corrosion pipeline.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.2
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• pp.93-101
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• 2004

This paper is intended to assess a dynamic system reliability. Bayesian networks, however, have difficulties in their application for assessing the system reliability especially when the system consists of dependent components and the probability of failure of each component varies over time. Hence, we suggest a method for resolving the difficulties by considering a hoist system composed of two wires. Firstly, we explain the method of calculating the failure probability of the system components. Secondly, we show how to calculate the failure probability of the system for two cases that failure probability of each wire is constant and varying in time, respectively. finally, based on the calculated failure probability of the system, we infer the probability that two interesting events occur.

• Journal of Mechanical Science and Technology
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• v.18 no.1
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• pp.55-64
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• 2004

Many researchers have made a lot of progress in studying the evaluation of fracture probability of brittle materials. However, studies of fracture probability for elastic-plasticity have not been made yet. An evaluation method for fracture probability which is grafted onto a 2-parameter criterion and statistical probability analysis is not only introduced in this study, but also applied to the simple 2-dimensional model and carbon steel piping to vealuate the effect of statistical variables.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.36-51
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• 2016

This study assessed urban flood risk using a Bayesian probability statistical method and GIS incorporating a climate change scenario. Risk is assessed based on a combination of hazard probability and its consequences, the degree of impact. Flood probability was calculated on the basis of a Bayesian model and future flood occurrence likelihoods were estimated using climate change scenario data. The flood impacts include human and property damage. Focusing on Seocho-gu, Seoul, the findings are as follows. Current flood probability is high in areas near rivers, as well as low lying and impervious areas, such as Seocho-dong and Banpo-dong. Flood risk areas are predicted to increase by a multiple of 1.3 from 2030 to 2050. Risk assessment results generally show that human risk is relatively high in high-rise residential zones, whereas property risk is high in commercial zones. The magnitude of property damage risk for 2050 increased by 6.6% compared to 2030. The proposed flood risk assessment method provides detailed spatial results that will contribute to decision making for disaster mitigation.