• 소성∙가공
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• 제29권5호
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• pp.241-250
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• 2020

In this study, the methodology of the springback prediction of automotive parts applied 3rd generation AHSS was investigated using the response surface model analysis based on a regression model, and the meta model analysis based on a Kriging model. To design the learning data set for constructing the springback prediction models, and the experimental design was conducted at three levels for each processing variable using the definitive screening designs method. The hat-shaped member, which is the basic shape of the member parts, was selected and the springback values were measured for each processing type and processing variable using the finite element analysis. When the nonlinearity of the variables is small during the hat-shaped member forming, the response surface model and the meta model can provide the same processing parameter. However, the accuracy of the springback prediction of the meta model is better than the response surface model. Even in the case of the simple shape parts forming, the springback prediction accuracy of the meta model is better than that of the response surface model, when more variables are considered and the nonlinearity effect of the variables is large. The efficient global optimization algorithm-based Kriging is appropriate in resolving the high computational complexity optimization problems such as developing automotive parts.

• 한국분말재료학회지
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• 제29권6호
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• pp.459-467
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• 2022

Soft magnetic powder materials are used throughout industries such as motors and power converters. When manufacturing Fe-based soft magnetic composites, the size and shape of the soft magnetic powder and the microstructure in the powder are closely related to the magnetic properties. In this study, Fe-Si-Al-P alloy powders were manufactured using various manufacturing process parameter sets, and the process parameters of the vacuum induction melt gas atomization process were set as melt temperature, atomization gas pressure, and gas flow rate. Process variable data that records are converted into 6 types of data for each powder recovery section. Process variable data that recorded minute changes were converted into 6 types of data and used as input variables. As output variables, a total of 6 types were designated by measuring the particle size, flowability, apparent density, and sphericity of the manufactured powders according to the process variable conditions. The sensitivity of the input and output variables was analyzed through the Pearson correlation coefficient, and a total of 6 powder characteristics were analyzed by artificial neural network model. The prediction results were compared with the results through linear regression analysis and response surface methodology, respectively.

• 열처리공학회지
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• 제33권4호
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• pp.185-192
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• 2020

In this study, materials characterization of pure copper and copper based carbon nano-tube composite prepared by powder metallurgy method were investigated. Prior to evaluate materials characterization, spark plasma sintering processing variables such as sintering temperature, pressure, thickness and diameter of compacts was optimized to ensure the microstructure and materials property of pure Cu and Cu-CNT composite. In addition, corrosion behavior of Cu-based CNT composite produced by powder sintering method was investigated. It was confirmed from this study that the corroded surfaces of the composite shows less dissolution compared with pure copper in 3.5 wt% NaCl solution. The measured corrosion current density (I_corr) indicates improved corrosion property of Cu based composite containing small additions of CNTs in chloride containing media. Micro-galvanic activity between Cu and CNT was not observed in given sintering condition.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.1150-1155
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• 2008

Parameter analysis has been performed for an equal channel angular process. The processing variables such as channel configuration, friction coefficient, and ram speed were investigated by means of the magnitudes and distributions of effective plastic strain analysis through the deformation. The materials considered were pure aluminum and titanium. Here firstly, a finite element implementation by using the commercial ABAQUS software was carried out for both the aluminum and titanium materials based on the L-channel configuration. The experimental investigation then has been conducted using the obtained data. Finally, the ability of robust metals which can be produced by the optimized ECAP has been discussed by the appropriate parameter analysis.

• 한국표면공학회지
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• 제39권5호
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• pp.199-205
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• 2006

Titanium nitride (TiN) coatings were produced on AISI 420 stainless steel by DC magnetron sputtering of a Ti target changing the processing variables, such as the flow rate of $N_2/Ar$, substrate temperature and the existence of Ti interlayer between TiN coatings and substrates. The hardness and residual stress in the films were investigated using nanoindentation and a laser scanning device, respectively. The stoichiometry and surface morphology were investigated using X-Ray Diffraction and SEM. The corrosion property of the films was also studied using a polarization method in NaCl (0.9%) solution. Mechanical properties including hardness and residual stress were related to the ratio of $N_2/Ar$ flow rate. The corrosion resistance also was related to the processing variables.

• 반도체디스플레이기술학회지
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• 제7권1호
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• pp.53-57
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• 2008

$Pb(ZrTi)O_3$ thin films were prepared on transparent conducting oxides, through sol-gel processing. The processing variables such as spin velocity, spin time and annealing temperature were investigated using a statistical design of experiments. Dielectric properties were determined through capacitance-voltage measurements and electrical characterizations evaluated using current-voltage characteristics. The leakage currents is determined mainly by annealing. The capacitance and breakdown voltage is found to be independent of the processing variables. The sophisticatedly controlled PZT thin films have been confirmed through microscopic images.

• 한국분말재료학회지
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• 제20권3호
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• pp.191-196
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• 2013

Nano-sized cobalt powder was fabricated by wet chemical reduction method at room temperature. The effects of various experimental variables on the overall properties of fabricated nano-sized cobalt powders have been investigated in detail, and amount of NaOH and reducing agent and dropping speed of reducing agent have been properly selected as experimental variables in the present research. Minitab program which could find optimized conditions was adopted as a statistic analysis. 3D Scatter-Plot and DOE (Design of Experiments) conditions for synthesis of nano-sized cobalt powder were well developed using Box-Behnken DOE method. Based on the results of the DOE process, reproducibility test were performed for nano-sized cobalt powder. Spherical nano-sized cobalt powders with an average size of 70-100 nm were successfully developed and crystalline peaks for the HCP and FCC structure were observed without second phase such as $Co(OH)_2$.

• Food Science and Biotechnology
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• 제16권4호
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• pp.557-564
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• 2007

We prepared caviar analogs encapsulated by calcium-alginate gel membranes as a means to replace higher priced natural caviars. Processing the caviar analogs (beluga type) was optimized by response surface methodology with central composite design. Concentrations of sodium alginate ($X_1$) and $CaCl_2\;(X_2)$ were chosen as the independent variables. In order to compare characteristics of the caviar analogs with the natural caviar, sphericity ($Y_1$), diameter ($Y_2$), membrane thickness ($Y_3$), rupture strength ($Y_4$), rupturing deformation ($Y_5$), and sensory score ($Y_6$) were used as the dependent variables. The sphericity of the caviar analogs showed a similar value to that of natural caviar (over 94%) in the range of independent variables. Generally, the $CaCl_2$ concentration ($X_2$) affected all dependent variables to a greater extent than the sodium alginate concentration ($X_l$), For the multiple response optimization of the 5 dependent variables ($Y_1,\;Y_2,\;Y_4,\;Y_5$, and $Y_6$), the desirability function was defined as the following conditions: target values ($Y_1\;=\;100%,\;Y_2\;=\;3.0\;mm,\;Y_4\;=\;1,470\;g,\;Y_5\;=\;1.1\;mm,\;and\;Y_6\;=\;10\;points$). Membrane thickness ($Y_3$) was eliminated from the dependent variables for multiple response optimization because it could not be measured with an image analyzer. The values of the independent variables as evaluated by multiple response optimization were $X_1\;=\;-0.093$ (78%) and $X_2\;=\;-0.322$ (1.07%), respectively.

• Journal of Information Processing Systems
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• 제3권1호
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• pp.26-32
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• 2007

Although the Java bytecode has numerous advantages, it also has certain shortcomings such as its slow execution speed and difficulty of analysis. In order to overcome such disadvantages, a bytecode analysis and optimization must be performed. The control flow of the bytecode should be analyzed; next, information is required regarding where the variables are defined and used to conduct a dataflow analysis and optimization. There may be cases where variables with an identical name contain different values at different locations during execution, according to the value assigned to a given variable in each location. Therefore, in order to statically determine the value and type, the variables must be separated according to allocation. In order to achieve this, variables can be expressed using a static single assignment form. After transformation into a static single assignment form, the type information of each node expressed by each variable and expression must be configured to perform a static analysis and optimization. Based on the basic type information, this paper proposes a method for finding the related equivalent nodes, setting nodes with strong connection components, and efficiently assigning each node type.

• 대한간호학회지
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• 제14권2호
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• pp.84-92
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• 1984

This article examined relationships between selected variables, such as demographic background, care, treatment variables, environmental characteristics, and patient's daily behavior and mood change. Relationship were determined between independent variabltherapeutic-rapeutie approach, demographic data, environmental management approach-,and dependent variable-patient's daily behavioral and mood change. 35 patients selected within some criteria in a psychiatric ward, were obserbed during 5 weeks by use of Wyatt's Behavior & Mood Rating Scale ac-cording to the object of the study. At the same time, the frequence of the care and treatment were collected. Criteria for sample selection and independent variables as an influential factor to the patient behavioral change, based on a literature revienw and clinical experiences. Pearson's correlation and multiple regression analysis were used to determine the influfntial factors to the patient behavioral change. Systematic reading (r=.8324), Psychiatrist's individual interview (r=.5764), tranquilizer (r=.3441) and hospitalization processing date (r=.4143) were related with patient's behavioral change. That is these 4 variables can be said to influence to the patient's behavior and mood. A stepwise multiple regression analysis of the effect of the independent varibles of systematic reading, psychintrists individual interview, tranquilizer and hospitalization processing date on the dependent variable, patient's behavioral change was carried out. Systematic reading with on R²of. 69 revealed to be the main influential factor to the patient's behavior and mood change, as the next factor psychiatrist individual interview. A total inclusion of these factors revealed a 73% prediction for the patient's behavior and mood change. But the most influential factor was the interaction of the systematic reading and psychiatrist's individual interview.