• 한국기계가공학회지
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• 제11권5호
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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.

• 대한기계학회논문집A
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• 제21권11호
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• pp.1773-1785
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• 1997

The cooling stage is the very critical and most time consuming stage of the injection molding process, thus it cleary affects both the productivity and the part quality. Even through there are several commercialized package programs available in the injection molding industry to analyze the cooling performance of the injection molding coling stage, optimization of the cooling system has npt yet been accomplished in the literature due to the difficulty in the sensitivity analysis. However, it would be greatly desirable for the mold cooling system designers to have a computer aided design system for the cooling stage. With this in mind, the present study has successfully developed an interated computer aided design system for the injection molding cooling system. The CAD system utilizes the sensitivity analysis via a Boundary Element Method, which we recently developed, and the well-known CONMIN alforuthm as an optimization technique to minimize a weighted combination (objective function) of the temperature non-uniformity over the part surface and the cooling time related to the productivity with side constranits for the design reality. In the proposed objective function , the weighting parameter between the temperature non-uniiformity abd the cooling time can be adjusted according to user's interest. In this cooling system optimization, various design variable are considered as follows : (i) (design variables related to processing conditions) inlet coolant bulk temperature and volumetric flow rate of each cooling channel, and (ii) (design variables related to mold cooling system design) radius and location of each cooling channel. For this optimum design problem, three different radius and location of each cooling channel. For this optimum design problem, three different strategies are suffested based upon the nature of design variables. Three sample problems were successfully solved to demonstrated the efficiency and the usefulness of the CAD system.

• 한국생산제조학회지
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• 제18권4호
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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.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2009년도 춘계학술대회 논문집
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• pp.361-364
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• 2009

The cooling system optimization for injection molds was studied with a response surface method in the previous research. It took so much time to find an optimum solution for a large product due to an extensive amount of calculation time for the CAE analysis. In order to use the optimization technique in the actual design process, the calculation time should be much reduced. In this study, we tried to reduce the number of design variables with the concept of the close relationship between the depth and the distance of cooling channels. The optimum ratio of the distance to the depth of cooling channels for a 2-dimensional problem was 2.0 so that the optimum ratio was again sought out for 4 industrial products. The major cooling effect of the injection molds for large products rely on baffle tubes. The optimum ratio of the distance to the depth for baffle tubes was 2.0 for the large products. The result enables us to reduce the number of the design variables by half in the cooling system optimization problem.

• 설비공학논문집
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• 제29권12호
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• pp.645-653
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• 2017

Thermal and flow modeling and fin structure optimization were performed to reduce the weight of an electrical device with a staggered fin. First, a numerical model for thermal and flow characteristics was suggested, and then, the model was verified experimentally. Using the verified model, improvement in cooling performance of the cooling system through the staggered fins was predicted. As a result, 87.5% of total heat generated was dissipated through the cooling fins, and a thermal island was observed in the rotor because of low velocity of the internal air flow through the air gap. In addition, it was confirmed that the staggered fin improves the cooling performance but it also increases the total pressure drop within the cooling system, by maximizing the leading edge effect. Based on this analysis result, the effect of each design parameter on the thermal and flow characteristics was analyzed to select the main optimal design parameters, and multi-objective optimization was performed by considering the cooling performance and the fin weight. In conclusion, the optimized fin structure improved the cooling performance by 7% and reduced the fin weight by 28% without any compromise of the pressure drop.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2009년도 춘계학술대회 논문집
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• pp.357-360
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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. In this research, we tried the back-propagation algorithm of artificial neural network to find an optimum solution in the cooling system design of injection mold. The cooling system optimization problem that was once solved by a response surface method with 4 design variables was solved by applying the back-propagation algorithm, resulting in a solution with a sufficient accuracy. Furthermore the number of training points was much reduced by applying the fractional factorial design without losing solution accuracy.

• 대한기계학회논문집B
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• 제32권4호
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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.

• 한국수소및신에너지학회논문집
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• 제33권4호
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• pp.451-461
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• 2022

CFD analysis including optimization process was conducted to design shell and tube CO₂ methanation reactor cooling system. The high-pressure saturated water flowed into the cooling system and was evaporated by heat flux from reacting tubes. The optimization process decided the gap between tubes and reactor diameter to satisfy objective functions related to temperature. The results showed that the gap and diameter reduced about 30% and 3.6% respectively. Averaged surface temperature satisfied the target value and the min-max deviation was minimized.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.1100-1103
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• 2007

For the past decade many effort has been delivered to understand noise generation mechanism for the small size engine cooling fan. As a result of that effort, the low noise fan such as the Wave fan was developed. Now the Wave fan becomes the well known low noise engine cooling fan. But in case of the new car development, the system in the new car will be different from previous one. So we need system optimization for every new model. In case of special application, a low speed fan should be developed to match system requirement. In that case, we meet severe engineering requirement by conducting fan system optimization instead of the simple fan scaling. In this paper, I will show you the system optimize process.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.690-694
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• 2008

In this presentation, we study numerically an optimization problem of a fire fighting robot cooling system. The governing equation for the system is the unsteady heat equation with source term. We use a multigrid method for numerical solutions in three-dimensional space. We investigated the effects of various parameters and the results will be presented.