• 소성∙가공
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• 제30권3호
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• pp.125-133
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• 2021

In this study, response surface method (RSM), back propagation neural network (BPNN), and genetic algorithm (GA) were used for modeling and multi-objective optimization of the parameters of AA5052-H32 in incremental sheet forming (ISF). The goal of optimization is to determine the maximum forming angle and minimum surface roughness, while varying the production process parameters, such as tool diameter, tool spindle speed, step depth, and tool feed rate. A Box-Behnken experimental design (BBD) was used to develop an RSM model and BPNN model to model the variations in the forming angle and surface roughness based on variations in process parameters. Subsequently, the RSM model was used as the fitness function for multi-objective optimization of the ISF process the GA. The results showed that RSM and BPNN can be effectively used to control the forming angle and surface roughness. The optimized Pareto front produced by the GA can be utilized as a rational design guide for practical applications of AA5052 in the ISF process

• Advances in materials Research
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• 제13권1호
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• pp.1-18
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• 2024

The present experimental investigation focuses on finding optimal parametric data-set of laser micro-drilling operation with minimum taper and Heat-affected zone during laser micro-drilling of Carbon Nanotube/Epoxy-based composite materials. Experiments have been conducted as per Box-Behnken design (BBD) techniques considering cutting speed, lamp current, pulse frequency and air pressure as input process parameters. Then, the relationship between control parameters and output responses is developed using second-order nonlinear regression models. The analysis of variance test has also been performed to check the adequacy of the developed mathematical model. Using the Response Surface Methodology (RSM) and an Accelerated particle swarm optimization (APSO) technique, optimum process parameters are evaluated and compared. Moreover, confirmation tests are conducted with the optimal parameter settings obtained from RSM and APSO and improvement in performance parameter is noticed in each case. The optimal process parameter setting obtained from predictive RSM based APSO techniques are speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), Air pressure (1 kg/cm²) for Taper and speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), air pressure (3 kg/cm²) for HAZ. From the confirmatory experimental result, it is observed that the APSO metaheuristic algorithm performs efficiently for optimizing the responses during laser micro-drilling process of nanocomposites both in individual and multi-objective optimization.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 A
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• pp.269-271
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• 1998

Reluctance Synchronous Motors(RSM) with new rotor shape are considered in this paper. Since the stator of a RSM is similar as that of an induction motor, attention is focused here on the rotor structure. We have designed the parameter of RSM and analyzed the characteristics of the electromagnetic energy conversion.

• 반도체디스플레이기술학회지
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• 제14권1호
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• pp.39-43
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• 2015

This paper is to derive information about the optimal shape of the pack has a minimum temperature range of a Li-ion battery equipped with a module. We selected the shape of the pack in order to reduce the temperature deviation between the batteries as a variable. And we derived the experimental points with a minimum of DOE by D-optimal. We analyzed the temperature and the flow within the battery pack by using a numerical analysis verified in previous studies. We derive the equation for the temperature variation in the objective function using the RSM and performed optimization. As a result, it was confirmed that with the variation in the $1.706e-4^{\circ}C$ when to apply an optimized shape.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.167-169
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• 2006

대용량 BLDC 모터의 진동 및 소음의 원인은 영구자석과 슬롯 개구부 형상에 의한 코깅토크와 전류 파형에 의하여 발생하게 된다. 특히 대용량 BLDC의 경우 코깅토크에 의한 진동 및 소음의 영향이 상대적으로 큰 값을 가지게 된다. 따라서 코깅토크 발생원인 중 하나인 영구자석의 형상에 RSM(Response Surface Method) 최적화 이론을 적용하여 코깅토크 저감을 연구하였다. FEM과 RSM을 결합하여 영구자석의 형상을 최적화한 결과 코깅토크의 ripple이 25%이상 감소되었다.

• Composites Research
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• 제16권4호
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• pp.36-43
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• 2003

본 논문에서는 메타모델을 이용한 복합재 구조물의 지적화가 수행되었다. 일반적으로 복합재 구조물에서 시간이 오래 걸리는 해석의 결과를 최적화하고자 할 때 전체 최적화에 많은 시간이 든다. 따라서 이와 같은 구조물 해석을 메타 모델로 치환해 보았다. 본 연구에서는 RSM, kriging과 같은 메타모델을 사용하였다. 복합재 평판의 최종 파손 강도 해석을 메타모델을 이용해 근사화하였다 최종 파손 강도를 최대화하는 최적화를 유전자 알고리즘과 메타로델을 이용해 수행하였다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집C
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• pp.580-585
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• 2001

A response surface method(RSM) is utilized for structural optimization and implemented on a parametric CAD platform. Once an approximation of the performance function is made, no formal design sensitivity analysis is necessary. The approximation gives the designer the sensitivity information and furthermore intuition on the performance functions. The scheme for the design of experiment chosen for the RSM has a large influence on the accuracy of converged solutions and the amount of computation. The D-optimal design criterion as implemented in this paper is found efficient for the structural optimization. The program is developed on a parametric CAD platform and tested using several shape design problems of such as a torque arm and a belt clip. It is observed that the RSM used provides a faster convergence than other approximation methods for design sensitivity.

• 전기학회논문지
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• 제58권4호
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• pp.735-741
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• 2009

This paper presents an algorithm for the permanent magnet shape optimization of a large scale BLDC(Brushless DC) motor to minimize the cogging torque. A response surface method (RSM) using multiquadric radial basis function is employed to interpolate the objective function in design parameter space. In order to get a reasonable response surface with relatively small number of sampling data points, additional sampling points are added on the basis of design sensitivity analysis computed by using FEM. The algorithm has 2 stages: the first stage is to determine the PM arc angle, and the 2nd stage is to optimize the magnet pole shape. The developed algorithm is applied to a 5MW BLDC motor to get a minimum cogging torque. After 3 iterations with 4 design parameters, the cogging torque is reduced to 13.2% of the initial one.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2001년도 추계 학술대회논문집
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• pp.44-50
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• 2001

A numerical study was made to choose the better turbulence model for the flow in the discharge flow path from a diffuser to a wall. In this study standard $\kappa-\epsilon$ model(SKE), RNG $\kappa-\epsilon$ model(RNG), and Reynolds stress model(RSM) were applied. In case of the flow with relatively high Reynolds number at a diffuser inlet, the pressure loss coefficients by RNG have a tendency to be near to those by SKE at small ratio(below about 0.35) of $h/D_o$, but to those by RSM at large ratio(above about 0.35). At large ratio RNG begins to enlarge the effects of rapid strain and streamline curvature. RNG & RSM are recommended as the appropriate turbulence models for this case. But it is noticeable that the velocity gradient pattern in RNG is same as in SKE, and also that the total pressure distribution in RNG is same as in RSM only at swirling flow area, same as in SKE only at main flow area.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.74-76
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• 2007

A hybrid optimization method is proposed for cogging torque reducing in BLDC motor. The proposed hybrid optimization method comprises a response surface method (RSM) and a gradient search method (GSM). The RSM is effective and global method in optimization problem but having large approximation error. The GSM is accurate and fast search method for optimal solution but having local behavior. To reduce approximation error and computation time a hybrid method (RSM+GSM) is proposed method. To illustrate the effectiveness of the proposed method, a comparison between conventional RSM and the proposed hybrid method is made. A simulation results verify that the hybrid method can achieve favorable design performance.