• Journal of Welding and Joining
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• v.27 no.1
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• pp.95-101
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• 2009

In case of manufacturing the high quality welds or pipeline, the full penetration weld has to be made along the weld joint. Thus the root pass welding is very important and has to be selected carefully. In this study, an experimental method for the selection of optimal welding condition was proposed in the root pass welding which was done along the V-grooved butt weld joint. This method uses the response surface analysis in which the width and height of back bead were chosen as the quality variables of the weld. The overall desirability function, which is the combined desirability function for the two quality variables, was used as the objective function for getting the optimal welding condition. In the experiments, the target values of the back bead width and the height are 6mm and zero respectively for the V-grooved butt weld joint of 8mm thickness mild steel. The optimal welding conditions could predict the back bead profile(bead width and height) as 6.003mm and -0.003mm. From a series of welding test, it was revealed that a uniform and full penetration weld bead can be obtained by adopting the optimal welding condition which was determined according to the method proposed.

• Journal of Computational Design and Engineering
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• v.3 no.1
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• pp.71-90
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• 2016

Steel nitriding is a thermo-chemical process leading to surface hardening and improvement in fatigue properties. The process is strongly influenced by many different variables such as steel composition, nitrogen potential, temperature, time, and quenching media. In the present study, the influence of such parameters affecting physic-chemical and mechanical properties of nitride steels was evaluated. The aim was to streamline the process by numerical-experimental analysis allowing defining the optimal conditions for the success of the process. Input parameters-output results correlations were calculated through the employment of a multi-objective optimization software, modeFRONTIER (Esteco). The mechanical and microstructural results belonging to the nitriding process, performed with different processing conditions for various steels, are presented. The data were employed to obtain the analytical equations describing nitriding behavior as a function of nitriding parameters and steel composition. The obtained model was validated, through control designs, and optimized by taking into account physical and processing conditions.

• Transactions of Materials Processing
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• v.21 no.1
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• pp.42-48
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• 2012

Hydroforming has attracted the attention of manufacturing industries for vehicles and transportation systems. A wide range of products such as subframes, camshafts, radiator frames, axles and crankshafts are made by the hydroforming process. Hydroformed parts often need to be structurally joined to other components during assembly. Therefore it is useful if the hydroformed automotive parts can be attached with a localized flange. In this study, a hydroforming process to produce a rectangular shape flange is proposed. FE analysis to form the flanged rectangular shape was performed by Dynaform 5.5. The hydroforming characteristics at various die aspect ratios and feeding conditions were analyzed and optimal process conditions which can avoid defects are suggested. For validation purposes, hydroforming experiments to form the flange were conducted with the optimized conditions. The results show that the flanged parts can be successfully formed with a hydroforming process without additional processing steps.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1991.10a
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• pp.147-159
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• 1991

Stochastic convexity(concvity) of a stochastic process is a very useful concept for various stochastic optimization problems. In this study we first establish stochastic convexity of a certain class of Markov additive processes through the probabilistic construction based on the sample path approach. A Markov additive process is obtained by integrating a functional of the underlying Markov process with respect to time, and its stochastic convexity can be utilized to provide efficient methods for optimal design or for optimal operation schedule of a wide range of stochastic systems. We also clarify the conditions for stochatic monotonicity of the Markov process, which is required for stochatic convexity of the Markov additive process. This result shows that stochastic convexity can be used for the analysis of probabilistic models based on birth and death processes, which have very wide application area. Finally we demonstrate the validity and usefulness of the theoretical results by developing efficient methods for the optimal replacement scheduling based on the stochastic convexity property.

• Journal of Dairy Science and Biotechnology
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• v.26 no.2
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• pp.51-56
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• 2008

Using central composite design, we have designed optimization of the manufacturing of processed butter. And response surface analysis by least-square regression was used Statistical Analysis System(SAS). Central composite design can be achieved by response surface techniques that allow flexibility in modeling and analysis. Response surface methodology(RSM) was used to optimize hardness(%) using as independent variables; the content of butter($X_1$), ranging from 50 to 90(%), the content of soybean oil($X_2$), from 0 to 20(%), and the hydrogenated soybean oil($X_3$) from 0 to 4(%). The results on the regression coefficients calculated for overrun by response surface by least-square regression(RSREG) were followed. It was considered that the linear regression was significant(p<0.01). As for the processed butter, the regression model equation for the hardness(Y, %) to the change of an independent variable could be predicted as follow: $Y=60.88-8.92X_2-{29.3X_2}^2$. The optimal for the manufacturing of processed butter were determined at the content of butter of 88.22%, soybean oil of 6.71% and hydrogenated soybean oil of 2.36%, respectively. Optimum compositions were resulted in hardness of 65.78 N. Finally the reference sample(Butter in the morning, Seoul Dairy Co-op.) and processed butter manufacturing under the optimal conditions were compared with spreadability test. The spreadability scores result from reference sample and butter under optimal conditions was not found a significant difference.

• Microbiology and Biotechnology Letters
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• v.37 no.3
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• pp.219-225
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• 2009

A bacterial strain, JE-34, producing a high concentration of red pigment was isolated from a sediment in East China Sea. It was identified as Zooshikella sp. JE-34 based on the 16S rRNA gene sequence analysis. The red pigment was purified by solvent extraction and HPLC was identified as prodigiosin-like compound. Nutritional and cultural conditions were optimized for the production of prodigiosin-like pigment in the flask level. Optimal culture conditions were at initial medium pH $6.0{\sim}7.0$, $30^{\circ}C$ and 4 days incubation. For carbon and, nitrogen sources were soluble starch and malt extract.

• Membrane and Water Treatment
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• v.9 no.6
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• pp.447-454
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• 2018

Although flotation techniques are often used for the removal of algal particles, the practicality of algae-harvesting technologies is limited owing to the complex and expensive facilities and equipment required for chemical coagulation. Here, we examined the feasibility of an approach to separating algal particles from water bodies without the need for chemical coagulants, depending on the condition of the algae, and to determine the optimal conditions. Using Anabaena sp., a cyanobacterium causes algal blooms in lakes, we stimulated auto-flocculation in algal particles without coagulants and conducted solid-liquid separation experiments of algal particles under various conditions. The six cultivation columns included in our analysis comprised four factors: Water temperature, light intensity, nutrients, and carbon source; auto-flocculation was induced under all treatments, with the exception of the treatment involving no limits to all factors, and algal particles were well-settled under all conditions for which auto-flocculation occurred. Meanwhile, flotation removal of auto-flocculated algal particles was attained only when nutrients were blocked after algae were grown in an optimal medium. However, no significant differences were detected between the functional groups of the extracellular polymeric substances (EPSs) of floated and settled algal particles in the FT-IR peak, which can cause attachment by collision with micro-bubbles.

• KSBB Journal
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• v.18 no.6
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• pp.473-478
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• 2003

The purpose of this study is to look for the optimal conditions of methane production. The conditions tested for methane production enhancement were temperature, pH, carbon source, nitrogen source, and inhibitor which can affects methane production. As a result, optimal conditions for methane production were 30$^{\circ}C$, neutral pH, methanol as a carbon source, NH$_4$Cl as a nitrogen source. 2-Bromoethanesulfonic acid was used as an inhibitor which can affects methane production. Existence in broth less than 10mM, inhibited methane production. Organic acid measurements revealed that formic acid exists in broth as majority.

• KIEE International Transactions on Power Engineering
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• v.3A no.3
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• pp.161-167
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• 2003

This paper presents a study performed to investigate the steady-state operational strategies of UPFCs in the Jeollanam-Do system in Korea. The objective of the study was to determine the UPFC operating points under normal and contingency conditions. The study consists of developing load flow models to simulate different load levels with and without UPFCs in the system, assessing the effectiveness of UPFCs by contingency analysis, and introducing optimal corrective actions for removing voltage problems caused by contingencies. The paper describes analytical tools, models and approach. It also includes analysis and discussion of the study results. The paper contributes to the area of transmission operational studies with FACTS applications.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.1
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• pp.76-88
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• 1991

Stochastic convexity (concavity) of a stochastic process is a very useful concept for various stochastic optimization problems. In this study we first establish stochastic convexity of a certain class of Markov additive processes through probabilistic construction based on the sample path approach. A Markov additive process is abtained by integrating a functional of the underlying Markov process with respect to time, and its stochastic convexity can be utilized to provide efficient methods for optimal design or optimal operation schedule wide range of stochastic systems. We also clarify the conditions for stochastic monotonicity of the Markov process. From the result it is shown that stachstic convexity can be used for the analysis of probabilitic models based on birth and death processes, which have very wide applications area. Finally we demonstrate the validity and usefulness of the theoretical results by developing efficient methods for the optimal replacement scheduling based on the stochastic convexity property.