• Design & Manufacturing
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• v.17 no.4
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• pp.72-78
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• 2023

Injection molding is a process widely used in various industries because of its high production speed and ease of mass production during the plastic manufacturing process, and the product is molded by injecting molten plastic into the mold at high speed and pressure. Since process conditions such as resin and mold temperature mutually affect the process and the quality of the molded product, it is difficult to accurately predict quality through mathematical or statistical methods. Recently, studies to predict the quality of injection molded products by applying artificial neural networks, which are known to be very useful for analyzing nonlinear types of problems, are actively underway. In this study, structural optimization of neural networks was conducted by applying multi-task learning techniques according to the characteristics of the input and output parameters of the artificial neural network. A structure reflecting the characteristics of each process step was applied to the input parameters, and a structure reflecting the quality characteristics of the injection molded part was applied to the output parameters using multi-tasking learning. Building an artificial neural network to predict the three qualities (mass, diameter, height) of injection-molded product under six process conditions (melt temperature, mold temperature, injection speed, packing pressure, pacing time, cooling time) and comparing its performance with the existing neural network, we observed enhancements in prediction accuracy for mass, diameter, and height by approximately 69.38%, 24.87%, and 39.87%, respectively.

• Transactions of Materials Processing
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• v.18 no.1
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• pp.67-72
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• 2009

This paper covers finite element simulations to evaluate tube bending process of auto chassis component i.e. trailing-arm product. The rear of the auto chassis structure is primarily composed of CTBA and trailing-arm. When a car rolls into a corner, the trailing arm reacts to roll in the same degree as the car body. During the bending process of trailing arm the tube undergoes significant deformation. Thus forming defects such as excessive thinning and flattening of the tube will be formed in the outside of the tube. In this paper, we analyzed the effect of process parameters in rotary draw bending process and searched the optimized combination of process parameters using orthogonal arrays method to minimize the forming defects. In this process we analyzed several parameters which are displacement of pressure die, boosting force, initial position of mandrel bar, dimensions of mandrel in regarding to the thinning and flattening of the tube.

• Journal of Welding and Joining
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• v.25 no.4
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• pp.58-64
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• 2007

Recently, the electro-magnetic induction process has been utilizing to substitute the flame heating process in shipyard. However, few studies have been performed to exactly analyze the deformation mechanism of the heating process with mathematical model. This is mainly due to the difficulty of modeling the inductor travelling on plate during the process. In this study, heat flux distribution of the process is firstly numerically analysed with the assumption that the process has a quasi-stationary state and also with the consideration that the heat source itself highly depends on the temperature of base plate. With the heat flux, the thermal and deformation analyses are then performed with a commercial program for 34 combinations of heating parameters. The deformations obtained and heating parameters are synthesized with a statistical method to produce simplified formulas, which easily give the relation between the heating parameters and deformations. The formulas are well compared with results of experiment.

• Design & Manufacturing
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• v.16 no.3
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• pp.1-8
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• 2022

In this study, an artificial neural network(ANN) was constructed to establish the relationship between process condition prameters and the qualities of the injection-molded product in the injection molding process. Six process parmeters were set as input parameter for ANN: melt temperature, mold temperature, injection speed, packing pressure, packing time, and cooling time. As output parameters, the mass, nominal diameter, and height of the injection-molded product were set. Two learning structures were applied to the ANN. The single-task learning, in which all output parameters are learned in correlation with each other, and the multi-task learning structure in which each output parameters is individually learned according to the characteristics, were constructed. As a result of constructing an artificial neural network with two learning structures and evaluating the prediction performance, it was confirmed that the predicted value of the ANN to which the multi-task learning structure was applied had a low RMSE compared with the single-task learning structure. In addition, when comparing the quality specifications of injection molded products with the prediction values of the ANN, it was confirmed that the ANN of the multi-task learning structure satisfies the quality specifications for all of the mass, diameter, and height.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.37.1-37.1
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• 2019

We perform Lyα radiative transfer calculations for reproducing Lyα properties of star-forming galaxies at high redshifts. We model a galaxy as a halo in which the density distributions of Lyα sources and HI plus dust medium are described with exponential functions. We also consider an outflow of the medium that represents a momentum-driven wind in a gravitational potential well. We demonstrate that this outflowing halo model with Lyα scattering can successfully reproduce both the spectrum and the surface brightness profile of eight star-forming galaxies at z=3-6 observed with MUSE. The best-fit model parameters (i.e., the outflowing velocity and optical depth) for these galaxies are in good agreement with other studies. We also demonstrate benefits of using spectrum and surface brightness profile simultaneously to the constraints on model parameters and thus spatial/kinematic distributions of medium. We examine the impacts of individual model parameters and intrinsic spectrum on emerging spectrum and surface brightness profile. Further investigations on the escape fraction, spatially resolved spectra, and the spatial extent of Lyα halos are presented as well.

• Korean Journal of Radiology
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• v.22 no.11
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• pp.1797-1808
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• 2021

Objective: To determine whether volumetric CT texture analysis (CTTA) using fully automatic tumor segmentation can help predict recurrence-free survival (RFS) in patients with intrahepatic mass-forming cholangiocarcinomas (IMCCs) after surgical resection. Materials and Methods: This retrospective study analyzed the preoperative CT scans of 89 patients with IMCCs (64 male; 25 female; mean age, 62.1 years; range, 38-78 years) who underwent surgical resection between January 2005 and December 2016. Volumetric CTTA of IMCCs was performed in late arterial phase images using both fully automatic and semi-automatic liver tumor segmentation techniques. The time spent on segmentation and texture analysis was compared, and the first-order and second-order texture parameters and shape features were extracted. The reliability of CTTA parameters between the techniques was evaluated using intraclass correlation coefficients (ICCs). Intra- and interobserver reproducibility of volumetric CTTAs were also obtained using ICCs. Cox proportional hazard regression were used to predict RFS using CTTA parameters and clinicopathological parameters. Results: The time spent on fully automatic tumor segmentation and CTTA was significantly shorter than that for semi-automatic segmentation: mean ± standard deviation of 1 minutes 37 seconds ± 50 seconds vs. 10 minutes 48 seconds ± 13 minutes 44 seconds (p < 0.001). ICCs of the texture features between the two techniques ranged from 0.215 to 0.980. ICCs for the intraobserver and interobserver reproducibility using fully automatic segmentation were 0.601-0.997 and 0.177-0.984, respectively. Multivariable analysis identified lower first-order mean (hazard ratio [HR], 0.982; p = 0.010), larger pathologic tumor size (HR, 1.171; p < 0.001), and positive lymph node involvement (HR, 2.193; p = 0.014) as significant parameters for shorter RFS using fully automatic segmentation. Conclusion: Volumetric CTTA parameters obtained using fully automatic segmentation could be utilized as prognostic markers in patients with IMCC, with comparable reproducibility in significantly less time compared with semi-automatic segmentation.

• Journal of Korea Water Resources Association
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• v.36 no.5
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• pp.823-838
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• 2003

For many rivers and streams, it has been observed that a single representative discharge may be used to determine the hydraulic geometry of a stable channel. This representative channel forming discharge has been given several names by different researchers, including bankfull, specified recurrence interval, and effective discharge. Therefore, The purpose of this study is to estimate channel forming discharge for study areas using the hydrological characteristic parameters and recording data, and to determine the hydraulic geometry relationships for the relating bankfull dimensions to bankfull discharge. In the Munmak and Seomyun gauging stations, the estimated bankfull discharges are found to have a return period of 1.8 and 1.5 years on the maximum annual series, respectively. The estimated effective discharges at those stations are largely different from bankfull discharges. The hydraulic geometry relationships between bankfull discharge and bankfull width, bankfull depth, velocity, bed slope are established. But the statistical parameters, such as R2, are calculated lower.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.1
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• pp.88-99
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• 1996

The explicit scheme for finite element analysis of sheet metal forming problems has been widely used for providing practical solutions since it improves the convergency problem, memory size and computational time especially for the case of complicated geometry and large element number. The explicit schemes in general use are based on the elastic-plastic modeling of material requiring large computataion time. In the present work, a basic formulation for rigid-plastic explicit finite element analysis of plain strain sheet metal forming problems has been proposed. The effect of some basic parameters involved in the dynamic analysis has been studied in detail. Thus, the effective ranges of parameters have been proposed for numerical simultion by the rigid-plastic explicit finite element method. A direct trial-and-error method is introduced to treat contact and friction. In computation, sheet material is assumed to possess normal anisotropy and rigid-plastic workhardening characteristics. In order to show the validity and effectiveness of the proposed explicit scheme, computations are carried out for cylindrical punch stretching and the computational results are compared with those by the implicit scheme as well as with a commercial code. The proposed rigid-plastic exlicit finite element method can be used as a robust and efficient computational method for analysis of sheet metal forming.

• Composites Research
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• v.36 no.5
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• pp.321-328
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• 2023

This study developed the in-situ stamp-forming process using the multi-axis robotic arm to fabricate thermal composite parts. Optimal fabrication parameters with the multi-axis robotic arm were determined using finite element analysis and these parameters were further refined through the practical manufacturing process. A comparison between the manufactured parts and finite element analysis results was conducted regarding thickness uniformity and wrinkle distribution to confirm the validity of the finite element analysis. Additionally, to evaluate the formability of the manufactured composite parts, measurements of crystallinity and porosity were taken. Consequently, this study establishes the feasibility of the In-situ stamp-forming consolidation using a robotic arm and verifies the potential for producing composite parts through this process.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2008.10a
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• pp.186-189
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• 2008

The flex plate, an automotive part which mounts to the automotive engine to transfer torque to transmission, should have considerable hardness and shape accuracy. As a way to produce the flex plate, the hot press forming technology which takes advantages of high formability at elevated temperature, enhanced strength and shape stability was introduced. Therefore, as one of major process parameters the heat treatment condition should be determined to obtain appropriate hardness in the range of manufacturer's specifications. In this study, two heat treatments, austempering and quenching and tempering (QT), were compared as feasible conditions fur the hot press forming of high-carbon tool steel and the hardness and toughness after heat treatments were evaluated. The study showed that both heat treatments resulted in improved hardness but only quenching and tempering showed practicable range of toughness.