• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.10a
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• pp.262-265
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• 2007

Cooling circuit of injection mold affects part quality and cycle time of injection molding process. Examination on mold cooling circuit is usually omitted in part design stage because cooling circuit is designed in the mold design stage. It is desirable to examine mold cooling circuit with respect to part quality in the part design stage. In order to make the examination process convenient and fast, cooling circuit design should be automated without intervention of skilled designer. In this study, optimization of cooling circuit design is automated with commercial softwares; Visual DOC and Moldflow MPI. Effect of initial value for optimization is examined for the optimization result.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.4
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• pp.417-422
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• 2009

The injection mold cooling circuit optimization 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 channel. 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 large automotive parts. Therefore, the number of design variables for the cooling circuit optimization can be reduced in half, resulting in much faster running time for the optimization as a design tool.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.2
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• pp.177-183
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• 2013

We describe a new method for selecting design variables for shape optimization of high-voltage gas circuit breaker using a Kriging meta-model and a genetic algorithm. Firstly we sample balance design variables using the Latin Hypercube Sampling. Secondly, we build meta-model using the Kriging. Thirdly, we search the optimal design variables using a genetic algorithm. To obtain the more exact design variable, we adopt the boundary shifting method. With the proposed optimization frame, we can get the improved interruption design and reduce the design time by 80%. We applied the proposed method to the optimization of multivariate optimization problems as well as shape optimization of a high - voltage gas circuit breaker.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.735-739
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• 2002

PTB(Power Transfer Breaker) is a device which incorporate the functions of ACB(Air Circuit Breaker) and ATS(Automatic Transfer Switch). ACB is a circuit breaker against overload and ATS is a switching device to transfer the load between two electric power sources. An existing PTB design based upon the 5 bar & cam mechanism has been regarded to be too complex and thus a simpler 4 bar mechanism with trigger lock is proposed. Experimentation and optimization of the trigger lock is presented.

• ETRI Journal
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• v.44 no.5
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• pp.837-848
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• 2022

Analog circuit design is comparatively more complex than its digital counterpart due to its nonlinearity and low level of abstraction. This study proposes a novel low-level hybrid of the sine-cosine algorithm (SCA) and modified grey-wolf optimization (mGWO) algorithm for machine learning-based design automation of CMOS analog circuits using an all-CMOS voltage reference circuit in 40-nm standard process. The optimization algorithm's efficiency is further tested using classical functions, showing that it outperforms other competing algorithms. The objective of the optimization is to minimize the variation and power usage, while satisfying all the design limitations. Through the interchange of scripts for information exchange between two environments, the SCA-mGWO algorithm is implemented and simultaneously simulated. The results show the robustness of analog circuit design generated using the SCA-mGWO algorithm, over various corners, resulting in a percentage variation of 0.85%. Monte Carlo analysis is also performed on the presented analog circuit for output voltage and percentage variation resulting in significantly low mean and standard deviation.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2125-2138
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• 2023

The printed circuit heat exchanger (PCHE) with airfoil fins has the benefits of high compactness, high efficiency and superior heat transfer performance. A novel multi-objective optimization approach is presented to design the airfoil fin PCHE in this paper. Three optimization design variables (the vertical number, the horizontal number and the staggered number) are obtained by means of dimensionless airfoil fin arrangement parameters. And the optimization objective is to maximize the Nusselt number (Nu) and minimize the Fanning friction factor (f). Firstly, in order to investigate the impact of design variables on the thermal-hydraulic performance, a parametric study via the design of experiments is proposed. Subsequently, the relationships between three optimization design variables and two objective functions (Nu and f) are characterized by an improved particle swarm optimization-backpropagation artificial neural network. Finally, a multi-objective optimization is used to construct the Pareto optimal front, in which the non-dominated sorting genetic algorithm II is used. The comprehensive performance is found to be the best when the airfoil fins are completely staggered arrangement. And the best compromise solution based on the TOPSIS method is identified as the optimal solution, which can achieve the requirement of high heat transfer performance and low flow resistance.

• 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.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.8
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• pp.64-70
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• 1997

This paper presents a parameter optimization method using evolutionary programming in voltage reference circuit because the designer must select appropriate parameter values of the circuit taking into consideration both powr voltage and temperature variation. In this paper, evolutionary programming is suggested as an approach for finding good parameters with which the reference voltage variation is small with respect to temperature variation. Simulation results. Simulation results show that this method is effective in circuit design.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.623-627
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• 1995

This paper describes analysis and optimization of Weil-Dobke synthetic testing circuit parameters, which is efficient and economical test method in high capacity AC circuit breaker. In this paper, analysis of synthetic short-circuit test circuit parameter proposed nondimensional factor that is reciprocal comparison value of circuit parameter and is not related to rated of circuit breaker, in particular, this study induce minimization of required energy of critical TRV generation specified in IEC 56 standards and present optimal design of synthetic short circuit testing facilities.

• Journal of Magnetics
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• v.21 no.4
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• pp.570-576
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• 2016

The shape optimization of the stator and the rotor is important for electrical motor design. Among many motor design parameters, the stator tooth and yoke width are a few of the determinants of noload back-EMF and load torque. In this study, we proposed an equivalent magnetic circuit of motor stator for efficient stator tooth and yoke width shape optimization. Using the proposed equivalent magnetic circuit, we found the optimal tooth and yoke width for minimal magnetic resistance. To verify if load torque is truly maximized for the optimal tooth and yoke width indicated by the proposed method, we performed finite element analysis (FEA) to calculate load torque for different tooth and yoke widths. From the study, we confirmed reliability and usability of the proposed equivalent magnetic circuit.