• Proceedings of the KSME Conference
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• 2000.04a
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• pp.218-223
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• 2000

The shot peening is largely used for a surface treatment in which small spherical parts called shots are blasted on a surface of a metallic components with velocities up to 100m/s. This treatment leads to an improvement of fatigue behavior due to the developed compressive residual stresses, and so it has gained widespread acceptance in the automobile and aerospace industries. The residual stress profile on surface layer depends on the parameters of shot peening, which are, shot velocity, shot diameter, coverage, impact angle, material properties etc. and the method to confirm this profile is only measurement by X-ray diffractometer. Despite its importance to automobile and aerospace industries, little attention has been devoted to the accurate modelling of the process. In this paper, the simulation technique is applied to predict the magnitude and distribution of the residual stress and plastic deformation caused by shot peening with the help of the finite element analysis.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.170-174
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• 2004

Despite the widespread use in the various manufacturing industries, the full automation of the robotic CO$_2$ welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this paper, an attempt has been made to develop an Radial basis function network model to predict the weld top-bead width as a function of key process parameters in the robotic CO$_2$ welding. and to compare the developed model and a simple neural network model using two different training algorithms in order to verify performance. of the developed model.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.1
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• pp.117-123
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• 2015

The need for drop simulations for board-leveled flip chips in micro-system packaging has been increasing. There have been many studies on flip chips with various solder ball compositions. However, studies on flip chips with Sn-1.0Ag-0.5Cu and Sn-3.0Ag-0.5Cu have rarely been attempted because of the unknown material properties. According to recent studies, drop simulations with these solder ball compositions have proven feasible. In this study, predictions of the impact lifetime by drop simulations are performed considering Cu and Cu/Ni UBMs using LS-DYNA to alter the design parameters of the flip chips, such as thickness of the flip chip and size of the solder ball. It was found that a smaller chip thickness, larger solder ball diameter, and using the Cu/Ni UBM can improve the drop lifetime of solder balls.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.12
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• pp.1678-1683
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• 2014

This study considers a problem of genomic selection (GS) for adjacent genetic markers of Yorkshire pigs which are typically correlated. The GS has been widely used to efficiently estimate target variables such as molecular breeding values using markers across the entire genome. Recently, GS has been applied to animals as well as plants, especially to pigs. For efficient selection of variables with specific traits in pig breeding, it is required that any such variable selection retains some properties: i) it produces a simple model by identifying insignificant variables; ii) it improves the accuracy of the prediction of future data; and iii) it is feasible to handle high-dimensional data in which the number of variables is larger than the number of observations. In this paper, we applied several variable selection methods including least absolute shrinkage and selection operator (LASSO), fused LASSO and elastic net to data with 47K single nucleotide polymorphisms and litter size for 519 observed sows. Based on experiments, we observed that the fused LASSO outperforms other approaches.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.2
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• pp.330-337
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• 2001

Wire drawing process of the high carbon steel with a high speed is usually conducted at room temperature using a number of passes or reductions through consequently located dies. In multi-stage drawing process, temperature rise in each pass affects the mechanical properties of final product such as bend, twist and tensile strength. Also, this temperature rise during the deformation is the reason that the wire in drawing process is broken by the embrittlement due to rapid strain aging effect. This paper presents the estimation of the wire temperature for the multi-stage wire drawing process. Using the proposed calculation method of wire temperature, temperature rise at deformation zone as well as temperature drop in block considering the heat transfer between the block and wire were calculated. As these calculated wire temperatures were applied to the real industrial fields, it was known that the calculated results were in a good agreement with the measured wire temperature.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.9
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• pp.1273-1281
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• 2003

The present study is mainly motivated to investigate the vaporization, auto-ignition, and combustion of liquid fuel spray injected into high pressure environment. The unsteady, multi-dimensional models were used for realistic simulation of spray as well as prediction of accurate ignition delay time. The Separated Flow (SF) model which considers the finite rate of transport between liquid and gas phases was employed to represent the interactions between spray and gas field. Among the SF models, the Discrete Droplet Model (DDM) which simulates the spray using finite number of representative samples of discrete droplets was adopted. The Eulerian-Lagrangian formulation was used to analyze the two-phase interactions. In order to predict an evaporation rate of droplet in high pressure environment, the high pressure vaporization model was applied using thermodynamic equilibrium and phase equilibrium at droplet surface. The high pressure effect as well as high temperature effect was considered in the calculation of liquid and gas properties. In case of vaporization, an interaction between droplets was studied through the simulation of spray. The interaction is shown up differently whether the ambient gas field is at normal pressure or high pressure. Also, the characteristics of spray behavior in high pressure environment were investigated through the comparison with normal ambient pressure case. In both cases, the spray behaviors are simulated through the distributions of temperature and reaction rate in gas field.

• Journal of Korea Foundry Society
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• v.25 no.5
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• pp.209-215
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• 2005

The design of the Metal mold casting should consider several variables such as the material properties and shape of the mold. In particular, the thermal stress generated by the thermal expansion and contraction depending on the thermal gradient of the mold causes partial plastic deformation on the mold, which causes damage or fracture of the cast. Consequently, the thermal deformation along with thermal stress leads to thermal deformation of the cast itself. In this study, the temperature analysis of the cast and mold is simulated by FDM to control the thermal deformation and stress as a result of the thermal gradient of mold. Using the results from FDM simulation, the thermal deformation and stress are analyzed by FEM and, the optimal mold design with minimum thermal deformation of the cast is suggested.

• Environmental Engineering Research
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• v.11 no.1
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• pp.33-44
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• 2006

The objective of this study was to develop and assess a method for estimating the rain scavenging ratios (RSRs) of particle-bound PAHs and PCBs using measured scavenging ratio of particulate matters (PM) and routinely available data of physico-chemical properties of PM. Paired atmospheric and rainwater sampling was conducted for a total of 4 rain events. Assuming equilibrium partitioning in rainwater-gas-PM system, an equation was derived for estimating the RSR of particle-bound chemicals as a function of RSR of PM and three equilibrium partition constants (i.e. dimensionless Henry's law constant, gas-particle partition coefficient, and water-particle partition coefficient). For all PAHs, the model significantly under-predicted the RSR while the model prediction for PCBs agreed with observation mostly within a factor of 5. The RSR model for the chemicals is of limited use as its accuracy critically depends on how close the observed partitioning of the chemicals in the gas-PM-rainwater system is to that estimated under the equilibrium assumption.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.481-481
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• 2000

We investigated the structure-activity relationships on use of multi-layer neural networks. The relationships are techniques required in developments of medicines. Since many kinds of observations might be adopted on the techniques, we discussed some points between the observations and the properties of multi-layer neural networks. In the structure-activity relationships, an important property is not that standard deviations are nearly equal to zero for observed physiological activity, but prediction ability for unknown medicines. Since we adopted non-linear approximation, the function to represent the activity can be defined by observations; therefore, we believe that the standard deviations have not significance. The function was examined by "leave-one-out" method, which was originally introduced for the multi-regression analysis. In the linear approximation, the examination is significance, however, we believe that the method is inappropriate in case of nonlinear fitting as neural networks; therefore, we derived a new index fer the relationships from the differential of information propagation in the neural network. By using the index, we discussed physiological activity of an anti-cancer medicine, Mitomycine derivatives. The neuro-computing suggests that there is no direction to extend the anti-cancer activity of Mitomycine, which is close to the trend of anticancer developing.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.12 no.2
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• pp.91-96
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• 2006

The widespread use of packaging materials on food packages sometimes causes off-flavor and deterioration in the food by migration of packaging materials which consist of mainly plastic materials and printing ink solvents. Even though migration of the residual packaging materials does not generally cause safety problems in the contained food, it certainly can generate off-flavor and finally deteriorate quality of the finished product. In highly consumer-oriented markets, quality of the finished product is gaining more importance economically, so profound and thorough study about migration into food to maintain the fine quality of the end product becomes an importance issue. Studies have been conducted about migration of various packaging materials and the chemical reactions between the food components and the materials used for food packaging (Brody, 1989; Mcneal and Breder, 1987; Lawson, G and Lawson, C, 1996). Several of these studies have measured partition coefficient values (Kp) between packaging materials and various food samples and involved finding factors that affected the partitioning behavior of packaging materials into the contained food. However, to enable prediction of partitioning, data are still needed on the relation of packaging material chemical structure and properties to partitioning behavior, and on the partitioning behavior of various food ingredients and the total food compositions.