• 전기학회논문지
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• 제59권5호
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• pp.897-903
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• 2010

This paper presents a response surface method(RSM) with Latin Hypercube Sampling strategy, which is employed to optimize a magnet pole shape of large scale BLDC motor to minimize the cogging torque. The proposed LHS algorithm consists of the multi-objective Pareto optimization and (1+1) evolution strategy. The algorithm is compared with the uniform sampling point method in view points of computing time and convergence. In order to verify the developed algorithm, a 6 MW BLDC motor is simulated with 4 design parameters (arc length and 3 variables for magnet) and 4 constraints for minimizing of the cogging torque. The optimization procedure has two stages; the fist is to optimize the arc length of the PM and the second is to optimize the magnet pole shape by using the proposed hybrid algorithm. At the 3rd iteration, an optimal point is obtained, and the cogging torque of the optimized shape is converged to about 14% of the initial one. It means that 3 iterations aregood enough to obtain the optimal design parameters in the program.

• 대한기계학회논문집A
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• 제28권3호
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• pp.267-273
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• 2004

The purpose of this paper is to develop a systematic design method for the suspension system hard points and compliance elements, which have great influence on the handling stability of a vehicle. In this paper, a method to optimize J-turn responses is presented based on the principles of design of experiments, multi-body dynamic analysis and optimum design technique. The design variables associated with the J-turn maneuver are selected through the experimental design sensitivity analysis using the perturbation method. An objective function is defined as an approximate function for the J-turn characteristics using the TSA(Taylor series approximation). The values of the design variables, which make the optimized J-turn characteristics, are obtained using the conjugate gradient method. The result of the J-turn simulation shows that the optimized vehicle has more improved handling stability than the optimized vehicle.

• 한국구조물진단유지관리공학회 논문집
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• 제21권6호
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• pp.113-125
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• 2017

본 연구는 전산실험을 통해 중규모 건물에 설치한 수동형 TMD의 매개변수에 대한 가중 다목적 최적화 설계를 다루고 있다. MATLAB으로 수치 시뮬레이션 코드를 작성함으로써 지진하중에 대한 동적응답을 파악하였으며 중심합성계획법과 반응표면법으로 구성한 전산실험을 기반으로 하는 가중 다목적 최적화 기법을 적용하여 TMD의 최적 동조 매개변수를 찾고자 하였다. 본 연구에서는 10층 건물을 대상으로 El Centro를 벤치마크 지진으로 가진하여 반응모델을 생성하고, AHP를 이용하여 반응변수 사이의 상대적 중요도를 산출한 후 가중다목적최적화 설계를 실시하였다. 본 연구의 방법으로 최적화된 매개변수를 가진 TMD는 지진 응답을 효과적으로 저감하였다. El Centro 지진이 작용하는 경우 RSM 기반 가중 다목적 최적설계방법으로 최적화한 TMD의 진동수 응답과 최상층 평균제곱변위는 비제진시보다 각각 31.6%와 82.3% 향상되었고, 모든 적용 지진에서 기존 설계법보다 동등 또는 이상의 성능을 가진 것으로 확인되었다.

• 한국전산구조공학회논문집
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• 제35권6호
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• pp.351-356
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• 2022

본 논문에서는 3차원 엮임 재료의 유체투과율 향상을 목적으로 수치해석 데이터 기반의 물성치 회귀 분석 및 최적설계를 소개한다. 우선 3차원 엮임 재료를 구성하는 와이어 사이의 간격을 결정하는 배율 계수를 매개변수화 하여 다양한 배율 조합을 가지는 수치 모델을 생성하였고, 전산 수치해석을 통해 계산된 각 모델의 체적 탄성계수, 열전도 계수, 유체투과율 데이터를 이용하여 다항식 기반의 회귀 분석을 수행하였다. 이를 사용해서 체적 탄성계수와 유체투과율 사이의 다목적함수 최적설계를 통한 파레토 최적해를 도출하였으며, 두 물성치가 서로 상충 관계에 있음을 확인하였다. 한편 3차원 엮임 재료의 열전달 효율을 높이기 위해서 유체투과율을 최대화 시키는 것을 목적으로 경사도 기반 최적설계를 수행하였고, 제약조건인 체적 탄성계수의 크기별 유체투과율의 변화율을 분석하였다. 그 결과 설계자가 원하는 최소한의 강성을 가지는 최대 유체투과율 설계 모델을 얻어낼 수 있음을 확인하였으며, 회귀 방정식을 통해서 얻어진 설계가 높은 정확도를 가지고 있음을 추가적으로 검증하였다.

• 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.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 춘계학술대회논문집
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• pp.1086-1092
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• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of a given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a mega model that has a regression model made by sampling data through simulation. In this paper, the neural network is used a mega model that have twenty-nine design variables and forty-six responses. After this mega model is constructed, multi-objective optimal solutions are achieved by using the differential evolution. This paper shows that this optimization method using the neural network and the differential evolution is a very efficient tool to solve the complex optimization problem.

• 한국항공우주학회지
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• 제40권11호
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• pp.963-971
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• 2012

본 논문에서는 항공기 날개의 최적설계 툴을 개발하고, 다중하중스펙트럼 조건에서 항공기 날개의 구조부재에 대한 최적설계를 수행하였다. 공력하중을 계산하기 위해 2차원 CFD의 해석 결과를 사용하였다. 최적화 설계 변수는 리브 및 스파의 개수 및 위치와 두께를 선정하였다. 각각의 비행유형에 대한 순항속도에서의 공력해석 결과로 응력해석을 수행한 후, 피로하중 스펙트럼 임무선도를 활용하여 피로파손해석을 수행하였다. 다중하중 조건의 적용을 위해 손상누적법을 적용하였다. 응력해석에 이은 파손 해석을 포함하는 항공기 날개의 경량화를 진행하였다. 다변수 문제를 효과적으로 최적화하기 위해 PSO(Particle Swarm Optimization) 알고리즘을 사용하였다.

• 한국정밀공학회지
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• 제18권2호
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• pp.177-185
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• 2001

This study shows the process design and forming analysis of permalloy shielding can that support the automobile multi-display parts to indicate the accurate information of car. This study is particularly important, since the strain and thickness of permalloy shielding can is known to affect the magnetic properties such as coercivity and permeability quite thickness of permalloy shielding can is known to affect the magnetic properties such as coercivity and permeability quite sensitively. The objective functions are strain and thickness deviation. The punch radius, die radius and blank holding force are considered as design parameters. Orthogonal array (OA) table and characteristics are applied to neural network (NN) as train data. After training, the optimal and robust condition of design parameters is selected. This study shows the correlation between the design methodology of NN and the statistical design of experiments (DOE) approach.

• 한국유체기계학회 논문집
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• 제17권1호
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• pp.35-40
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• 2014

A multi-objective optimization of a regenerative fan for enhancing the aerodynamic and aeroacoustic performance was carried out using an integrated fan design system, namely, Total FAN-Regen$^{(R)}$. The Total FAN-Regen$^{(R)}$ was developed for non-specialists to carry out a series of design process, viz., computational preliminary design, three-dimensional aerodynamic and aeroacoustic analyses, and design optimization, for a regenerative fan. An aerodynamic analysis of the regenerative fan was conducted by solving three-dimensional Reynolds-averaged Navier-Stokes equations using the shear stress transport turbulence model. And, an aeroacoustic analysis of the regenerative fan was implemented in a finite/infinite element method by solving the variational formulation of Lighthill's analogy based on the results of the unsteady flow analysis. An optimum shape obtained by Total FAN-Regen$^{(R)}$ shows the enhanced efficiency and decreased sound pressure level as much as 1.5 % and 20.0 dB, respectively, compared to those of the reference design. The performance test was carried out for an optimized regenerative fan to validate the performance of the numerically predicted optimal design.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2008년 영문 학술대회
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• pp.330-339
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• 2008

Ground-based interceptors(GBI) comprise a major element of the strategic defense against hostile targets like Intercontinental Ballistic Missiles(ICBM) and reentry vehicles(RV) dispersed from them. An optimum design of the subsystems is required to increase the performance and reliability of these GBI. Propulsion subsystem design and optimization is the motivation for this effort. This paper describes an effort in which an entire GBI missile system, including a multi-stage solid rocket booster, is considered simultaneously in a Genetic Algorithm(GA) performance optimization process. Single goal, constrained optimization is performed. For specified payload and miss distance, time of flight, the most important component in the optimization process is the booster, for its takeoff weight, time of flight, or a combination of the two. The GBI is assumed to be a multistage missile that uses target location data provided by two ground based RF radar sensors and two low earth orbit(LEO) IR sensors. 3Dimensional model is developed for a multistage target with a boost phase acceleration profile that depends on total mass, propellant mass and the specific impulse in the gravity field. The monostatic radar cross section (RCS) data of a three stage ICBM is used. For preliminary design, GBI is assumed to have a fixed initial position from the target launch point and zero launch delay. GBI carries the Kill Vehicle(KV) to an optimal position in space to allow it to complete the intercept. The objective is to design and optimize the propulsion system for the GBI that will fulfill mission requirements and objectives. The KV weight and volume requirements are specified in the problem definition before the optimization is computed. We have considered only continuous design variables, while considering discrete variables as input. Though the number of stages should also be one of the design variables, however, in this paper it is fixed as three. The elite solution from GA is passed on to(Sequential Quadratic Programming) SQP as near optimal guess. The SQP then performs local convergence to identify the minimum mass of the GBI. The performance of the three staged GBI is validated using a ballistic missile intercept scenario modeled in Matlab/SIMULINK.