• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.6 s.46
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• pp.53-58
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• 2005

Semi-analytical methodology to examine the dynamic responses of a bridge is developed via the joint probability density function. The evolution of joint probability density function is evaluated by the semi-analytical procedure developed. The joint probability function of the bridge responses can be obtained by solving the path-integral solution of the Fokker-Planet equation corresponding to the stochastic differential equations of the system. The response characteristics are observed from the joint probability density function and the boundary of the envelope of the probability density function can provide the maxima ol the bridge responses.

• Transactions of the Korean hydrogen and new energy society
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• v.18 no.3
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• pp.256-264
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• 2007

In order to calculate the relation between the hydrogen and the hydrogen absorption metals in the atomic level, Embedded Atom Method(EAM) is recommended. In this study, we had constructed the EAM programs from constitutive formulas and parameters of the hydrogen and palladium for the purpose of predicting the expansion behavior on hydrogen absorbing in the geometric shape of hydrogen absorption metals, as palladium bars and plates. And the EAM analyses data were compared with the experiment data by using electrochemical method. As results, it is note that the expansion rate in thickness of the palladium plate model by EAM analyses is about 4 times larger than width and length, be similar to experiment results. Also, in the microscopic and macroscopic level the expansion behavior through EAM analyses show good agreement with experiment data.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.725-734
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• 2017

The main purpose of this study is to analyze runoff aggregation structure and energy expenditure pattern of Choyang creek basin within the framework of power law distribution. To this end geomorphologic factors of every point in the basin of interest, which define tractive force and stream power as well as drainage area, are extracted based on GIS, and their complementary cumulative distributions are graphically analyzed through fitting them to power law distribution. The results indicate that three distinct behavioral regimes are observed from the complementary cumulative distributions of three geomorphogic factors. Based on the parameter estimation of power law distribution by maximum likelihood drainage area and stream power can be judged as scale invariance factor without finite scale while tractive force as scale dependence factor with finite scale. Furthermore, it is judged that tractive force would not follow power law distribution because it shows limited complex system behaviors only within the small extent of scale. The exponent of power law distribution for drainage area obtained in this study by maximum likelihood is larger than the previous researches due to the difference of parameter estimation methodologies. And the exponent for stream power is smaller than the previous researches due to the scaling property of channel slope for the basin of interest.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.8 no.2
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• pp.123-133
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• 2010

A statistical evaluation methodology was developed to determine the compliance of candidate waste stream with clearance criteria based upon distribution of radionuclide in a waste stream at a certain confidence level. For the cases where any information on the radionuclide distribution is not available, the relation between arithmetic mean of radioactivity concentration and its acceptable maximum standard deviation was demonstrated by applying widely-known Markov Inequality and One-side Chebyshev Inequality. The relations between arithmetic mean and its acceptable maximum standard deviation were newly derived for normally or lognormally distributed radionuclide in a waste stream, using probability density function, cumulative density function, and other statistical relations. The evaluation methodology was tested for a representative case at 95% of confidence level and 100 Bq/g of clearance level of radioactivity concentration, and then the acceptable range of standard deviation at a given arithmetic mean was quantitatively shown and compared, by varying the type of radionuclide distribution. Furthermore, it was statistically demonstrated that the allowable range of clearance can be expanded, even at the same confidence level, if information on the radionuclide distribution is available.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.61-73
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• 2020

Real-time location-sensing technology using location information collected from IoT devices is being applied for safety management purposes in many industries, such as ports. On the other hand, positional error is always present owing to the characteristics of GPS. Therefore, accident-risk detection algorithms must consider positional error. This paper proposes an methodology of calibration for falling object accident-risk-zone approach detection algorithm considering GPS errors. A probability density function was estimated, with positional error data collected from IoT devices as a probability variable. As a result of the verification, the algorithm showed a detection accuracy of 93% and 77%. Overall, the analysis results derived according to the GPS error level will be an important criterion for upgrading algorithms and real-time risk managements in the future.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.2
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• pp.125-130
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• 2011

Since conventional optimization that is classified as a deterministic method does not consider the uncertainty involved in a modeling or manufacturing process, an optimum design is often determined to be on the boundaries of the feasible region of constraints. Reliability-based design optimization is a method for obtaining a solution by minimizing the objective function while satisfying the reliability constraints. This method includes an optimization process and a reliability analysis that facilitates the quantization of the uncertainties related to design variables. Moment-based reliability analysis is a method for calculating the reliability of a system on the basis of statistical moments. In general, on the basis of these statistical moments, the Pearson system estimates seven types of distributions and determines the reliability of the system. However, it is technically difficult to practically consider the Pearson Type IV distribution. In this study, we propose an enhanced Pearson Type IV distribution based on a kriging model and validate the accuracy of the enhanced Pearson Type IV distribution by comparing it with a Monte Carlo simulation. Finally, reliability-based design optimization is performed for a system with type IV distribution by using the proposed method.