• Transactions of the Korean Society of Mechanical Engineers B
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• v.32 no.4
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• pp.255-265
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• 2008

This paper presents the optimization process of evaporator for a vapor compression cooling system for high heat flux CPU. The CPU thermal capacity was given by 300W. Evaporating temperature and mass flow rate were $18^{\circ}C$ and 0.00182kg/s respectively. R134a was used as a working fluid. Channel width(CW) and height(CH) were selected as design factors. And thermal resistance, surface temperature of CPU, degree of superheat, and pressure drop were taken as objective responses. Fractional factorial DOE was used in screening phase and RSM(Response Surface Method) was used in optimization phase. As a result, CW of 2.5mm, CH of 2.5mm, and CL of 484mm were taken as an optimum geometry. Surface temperature of CPU and thermal resistance were $33^{\circ}C\;and\;0.0502^{\circ}C/W$ respectively. Thermal resistance of evaporator designed in this study was significantly lower than that of other cooling systems such as water cooling system and thermosyphon system. It was found that the evaporator considered in this work can be a excellent candidate for a high heat flux CPU cooling system.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.2
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• pp.178-184
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• 2015

According to the regulation on the environment and fuel efficiency is becoming strict, many experiments are conducted to improve efficiency and emission in internal combustion engines. LTC (Low temperature combustion) technology is a promised solution for low emissions but there are a few barriers for the commercial engine. This paper includes optimization that applies LTC method to heavy duty diesel engine. Adequate LTC was applied to low and middle load as adaptability in heavy duty diesel engine, and optimization focused on reduction of fuel consumption was proceeded at high load. Through this research, strategy for practical use of LTC was selected, and fuel consumption has improved on the condition that satisfies the emission regulation at systematic viewpoint.

• Food Engineering Progress
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• v.21 no.3
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• pp.256-266
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• 2017

This study was designed to optimize ethanol extraction process of unfertilized corn silk (UCS) to maximize phytochemical contents and bioactivities. The response surface methodology (RSM) with central composite design (CCD) was employed to obtain the optimal extraction conditions. The influence of ethanol concentration, extraction temperature and extraction time on total polyphenol contents, total flavonoid contents, maysin contents, 2,2-diphenyl-1-picrylhydrazyl(DPPH) radical scavenging activities and tyrosinase inhibition were analyzed. For all dependable variables, the most significant factor was ethanol concentration followed by extraction temperature and extraction time. The following optimum conditions were determined by simultaneous optimization of several responses with the Derringer's desirability function using the numerical optimization function of the Design-Expert program: ethanol concentration 80.45%, extraction temperature $53.49^{\circ}C$, and extraction time 4.95 h. Under these conditions, the predicted values of total polyphenol contents, total flavonoid contents, maysin contents, DPPH radical scavenging activity and tyrosinase inhibition were $2758.74{\mu}g\;GAE/g$ dried sample, $1520.81{\mu}g\;QUE/g$ dried sample, 810.26 mg/100g dried sample, 56.86% and 43.49%, respectively, and the overall desirability (D) was 0.74.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.11
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• pp.1100-1107
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• 2007

In this study, a method to characterize material properties of adhesive that is used in a layered plates bonding process is developed by combined evaluation of experiment, simulation and optimization technique. A small bonded specimens of rectangular plate are prepared to this end, and put into a thermal loading conditions. $Moir{\acute{e}}$ interferomety is used to measure submicron displacements occurred during the process. The elevated temperature is chosen as control factors. FE analysis with constant values for the adhesive materials is also carried out to simulate the experiment. Significant differences are observed from the two results, in which the simulation predicts the monotonic increase of the bending displacement whereas the measurement shows decrease of the displacement at above $75^{\circ}C$. In order to minimize the difference of the two, material parameters of the adhesive at a number of different temperatures are posed as unknowns to be determined, and optimization is conducted. As a result, optimum material parameters are found that excellently matches the simulation and experiment, which are decreased with respect to the temperature.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.1
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• pp.34-40
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• 2015

A stack in the proton exchange membrane fuel cell (PEMFC) consists of bipolar plates, a membrane electrode assembly, a gas diffusion layer, a collector and end plates. High current density is usually obtainable partially from uniform temperature distribution in the fuel cell. A size optimization method considering the thermal expansion effect of stacked plates was developed on the basis of finite element analyses. The thermal stresses in end, bipolar, and cooling plates were calculated based on temperature distribution obtained from thermal analyses. Finally, the optimization method was applied and optimum thicknesses of the three plates were calculated considering both fastening bolt tension and thermal expansion of each unit cell (72 cells, 5kW). The optimum design considering both thermal and mechanical loads increases the thickness of an end plate by 0.64-0.83% the case considering only mechanical load. The effect can be enlarged if the number of stack increases as in an automotive application to 200-300 stacks.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.4
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• pp.434-443
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• 2014

A turbo fan engine performance analysis and the optimization using particle swarm optimization(PSO) algorithm have been conducted to investigate the effects of major performance design parameters of an aircraft gas turbine engine. The FJ44-2C turbofan engine, which is widely used in the small business jet, CJ2 has been selected as the basic model. The design parameters consists of the bypass ratio, burner exit temperature, HP compressor ratio, fan inlet mass flow, and nozzle cooling air ratio. The sensitivity analysis of the parameters has been evaluated and the optimization of the parameters has been performed to achieve high net thrust or low specific fuel consumption.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.360-365
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• 2007

This work is concerned with the topology optimization of three-dimensional cooling fins or heat sinks. Motivated by earlier success of the Internal Element Connectivity Method (I-ECP) method in two-dimensional problems, the extension of I-ECP to three-dimensional problems is carried out. The main efforts were made to maintain the numerical trouble-free characteristics of I-ECP for full three-dimensional problems; a serious numerical problem appearing in thermal topology optimization is erroneous temperature undershooting. The effectiveness of the present implementation was checked through the design optimization of three-dimensional fins.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.36-39
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• 1996

In chemical processes, measurement errors reduce the credibility of information and cause inconsistency in material and energy balances. Because multicomposition flows and temperature measurements make material and energy balances nonlinear equations, data reconciliation becomes a nonlinear constrained optimization problem. In multicomposition processes, if we follow general optimization procedure, the number of measurement variables is so large that data reconciliation requires much computation time. We propose the decomposition procedure to reduce the computation time without the decrease of accuracy of data reconciliation. Decomposition procedure finds global variables, that can reduce the nonlinearity of constraints, and divides two sub-optimization problems. Once we optimize the global variables at upper level, we can easily optimize the remain variables at tower level, We can obtain the short computational time and the same accuracy as SQP optimization method.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.5
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• pp.121-128
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• 2012

The optimization of cooling system parameters for designing injection mold is very important to acquire the highest part quality. In this paper, the integration of computer simulations of injection molding and Analysis of Variance(ANOVA) with orthogonal array was used as a design tool to optimize the cooling system parameters aimed at minimizing the part warpage. The design optimizer was applied to find the optimum levels of cooling system parameters for a dustpan. This optimization resulted in more uniform temperature distribution over the part and significant reduction of a part warpage, showing the capability of present method as an effective design tool. The whole optimization process was performed systematically in a proper number of cooling simulations. The design optimizer can be utilized effectively in the industry practice for designing mold cooling system with less cost and time.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.4
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• pp.430-435
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• 2009

The cooling stage greatly affects the product quality in the injection molding process. The cooling system that minimizes temperature variance in the product surface will improve the quality and the productivity of products. The cooling circuit optimization problem that was once solved by a response surface method with 4 design variables. It took too much time for the optimization as an industrial design tool. It is desirable to reduce the optimization time. Therefore, we tried the back-propagation algorithm of artificial neural network(BPN) to find an optimum solution in the cooling circuit design in this research. We tried various ways to select training points for the BPN. The same optimum solution was obtained by applying the BPN with reduced number of training points by the fractional factorial design.