• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.4
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• pp.89-99
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• 2003

Smoothed particle hydrodynamics, SPH, is a gridless Lagrangian technique which is a useful alternative numerical analysis method to simulate high velocity deformation problems as well as astrophysical and cosmological problems. The SPH method brings about some difficulties such as tensile Instability and stress oscillation. A new SPH method, so called normalized algorithm, was introduced to overcome these difficulties. In this paper we aimed to estimate this method and have developed an one-dimensional normalized SPH program. The high velocity impact model of an aluminum bar has been analysed by using the developed program and a commercial hydrocode, LS-DYNA. The obtained numerical results showed good agreement with the results of the same model in reference. The program also showed more stable results than those of LS-DYNA in stress oscillation. We hopefully expect that the developed one-dimensional normalized SPH program can be used to solve hydrodynamic problems especially for explosive detonation analysis.

• Journal of Ocean Engineering and Technology
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• v.23 no.6
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• pp.82-86
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• 2009

Several damping materials have been employed to reduce the vibration of structures. While it is important to estimate the damping matrix when analyzing damped composite structures using the finite element method (FEM), at present, there is no FEM program that can correctly estimate the damping matrix. In this paper, a new global curve-fitting method is proposed for identifying the system parameters of non-proportional damping structures using a frequency response function. An experimental test for a cantilever beam attached damping material was carried out to verify the performance of the method proposed in this study.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.8
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• pp.495-497
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• 2005

Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a neural network used for identification of the process dynamics of s signal input and signal output system and it was shown that this method offered superior capability over the conventional back propagation algorithm. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident. This paper goal estimate input signal about controller using neural networks.

• Communications for Statistical Applications and Methods
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• v.21 no.5
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• pp.387-393
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• 2014

Recurrent gap times are analyzed with diverse methods under several assumptions such as a marginal model or a frailty model. Several resampling techniques have been recently suggested to estimate the covariate effect; however, these approaches can be applied with a time-fixed covariate. According to simulation results, these methods result in biased estimates for a time-varying covariate which is often observed in a longitudinal study. In this paper, we extend a resampling method by incorporating new weights and sampling scheme. Simulation studies are performed to compare the suggested method with previous resampling methods. The proposed method is applied to estimate the effect of an educational program on traffic conviction data where a program participation occurs in the middle of the study.

• Journal of the Korean Graphic Arts Communication Society
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• v.21 no.2
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• pp.89-100
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• 2003

We have reviewed the method for surface tension of printing inks. Most of the methods fir for the low viscosity inks and solvents for inks. However, the inks for the offset lithography and intaglio should have high viscosity and high tack. The elongation of the ink filaments has more effect on the measuring surface tension than the energy of the surface molecules. In this paper, we propose the elongation method to estimate the surface tension of high viscosity printing inks. Even though we could measure the surface tension for low viscosity inks such as gravure and screen, elongation method could more useful to estimate the surface tension of lithography and intaglio inks than any other methods.

• Ocean and Polar Research
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• v.39 no.1
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• pp.51-59
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• 2017

The purpose of this paper is to estimate the economic value of beaches which are the major part of the East Sea Coast. ITCM (Individual Travel Cost Method) is applied to estimate the economic value of its beaches using Poisson, negative binomial, truncated Poisson and truncated negative binomial models. The consumer surplus during length of stay per capita is 214,088 won in beaches overall on the East Sea Coast, 206,398 won in Gangwon-do beaches and 271,171 won in Gyeongbuk/Ulsan beaches. Annual total economic value of its beaches considering the number of visitors at beaches is 6,269 billion won (3,970 billion won in Kangwondo beaches, 2,299 billion won in Kyungbuk/Ulsan beaches).

• Journal of the Korean Graphic Arts Communication Society
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• v.22 no.2
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• pp.23-36
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• 2004

The surface tension method has been possible only for the low viscosity materials. However, the inks for the off-set lithography and intaglio should have high viscosity and high tack. In this paper, we propose the elongation method to estimate the surface tension of high viscosity printing inks. The elongation method could be more useful to estimate the surface tension and shown in this research, it is possible to calculate the surface tension of high viscoxity ink without diluting the sample.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.18-20
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• 2005

Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a neural network used for identification of the process dynamics of s signal input and signal output system and it was shown that this method offered superior capability over the conventional back propagation algorithm. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident. This paper goal estimate input signal about controller using neural networks.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.70-74
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• 2018

In order to ensure the flow of goods available and more flexible, reduce labor costs, many factories and industrial zones around the world are gradually moving to use automated solutions. One of them is to use Automated guided vehicles (AGV). Currently, there are a line tracing method as an AGV operating method, and a method of estimating the current position of the AGV and matching with a factory map and knowing the moving direction of the AGV. In this paper, we propose ceiling Light and guided line based moving direction estimation algorithm using multi-camera on the AGV in smart factory that can operate stable AGV by compensating the disadvantages of existing AGV operation method. The proposed algorithm is able to estimate its position and direction using a general - purpose camera instead of a sensor. Based on this, it can correct its movement error and estimate its own movement path.

• Journal of the Korean Society of Safety
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• v.10 no.1
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• pp.56-63
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• 1995

Two methods of the numerical method of CPQRA(Chemical Process Quantitative Risk Analysis) and the manual method of IAEA(International Atomic Energy Agency) were used to estimate the individual risk and societal risk around the chemical plant. Where, the CPQRA is introduced to verify the theoritical background of the manual of international atomic energy agency. The Gaussian plume model which has a weather stability class D with velocity of 5m/s was applied to calculate dispersion of hazard material. Also, 8-point method was employed to the effects of accidents for wind distribution. Furthermore, historical record, FTA(Fault Tree Analysis) and ETA(Event Tree Analysis) were used to estimate the probability or frequency of accidents. Eventually, the individual risk shows isorisk contour and the societal risk shows F-N curve around hazard facility, especially in chemical plants. Caulculated results, which both individual and societal risk, by using IAEA manual show simillar results to those of calculation by numerical method of CPQRA.