• Journal of Advanced Marine Engineering and Technology
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• 제31권1호
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• pp.58-66
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• 2007

Genetic Algorithms (GA) have some difficulties in practical applications because of too many function evaluations. To overcome these limitations, an approximated modeling method such as Response Surface Modeling(RSM) is coupled to GAs. Original RSM method predicts linear or convex problems well but it is not good for highly nonlinear problems cause of the average effect of the least square method(LSM). So the locally approximated methods. so called as moving least squares method(MLSM) have been used to reduce the error of LSM. In this study, the efficient evolutionary GAs tightly coupled with RSM with MLSM are constructed and then a 2-dimensional inviscid airfoil shape optimization is performed to show its efficiency.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2006년도 추계학술대회 논문집 Vol.19
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• pp.302-303
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• 2006

The response surface modeling of the pretilt angle control using ion-beam (IB) alignment on nitrogen doped diamond-like carbon (NDLC) thin film layer is investigated. The response surface model is used to analyze the variation of the pretilt angle under various process conditions IB exposure angle and IB exposure time are considered as Input factors. The analysis of variance technique is used to analyze the statistical significance, and effect plots are also investigated to examine the relationships betweenthe process parameters and the response. The model can allow us to reliably predict the pretilt angle with respect to the varying process conditions.

• Journal of Mechanical Science and Technology
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• 제16권2호
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• pp.203-210
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• 2002

For effective response surface modeling during sequential approximate optimization (SAO), the normalized and the augmented D-optimality criteria are presented. The normalized D-optimality criterion uses the normalized Fisher information matrix by its diagonal terms in order to obtain a balance among the linear-order and higher-order terms. Then, it is augmented to directly include other experimental designs or the pre-sampled designs. This augmentation enables the trust region managed sequential approximate optimization to directly use the pre-sampled designs in the overlapped trust regions in constructing the new response surface models. In order to show the effectiveness of the normalized and the augmented D-optimality criteria, following two comparisons are performed. First, the information surface of the normalized D-optimal design is compared with those of the original D-optimal design. Second, a trust-region managed sequential approximate optimizer having three D-optimal designs is developed and three design problems are solved. These comparisons show that the normalized D-optimal design gives more rotatable designs than the original D-optimal design, and the augmented D-optimal design can reduce the number of analyses by 30% - 40% than the original D-optimal design.

• 한국항공우주학회지
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• 제41권1호
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• pp.48-53
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• 2013

다항식 반응면 모델은 실제의 물리적, 수치적 실험을 대체하는 근사모델로 여러 공학분야에서 사용되고 있다. 일반적으로 반응면 구성에 필요한 실험점 수를 줄이기 위하여 낮은 차수의 다항식을 사용하므로, 심한 비선형성이 동반되는 현상에 대한 모델링에는 한계가 있다. 본 연구에서는 다항식의 차수를 증가시키는 방법 및 다항식을 구성하는 최적의 기저함수를 선정하는 방법을 통해 다항식 반응면의 모델링 능력을 확장할 수 있는 방법을 개발하였다. 최적 기저함수의 선정에는 유전 알고리즘을 적용하였으며, 1 변수 및 2변수 함수와 풍동시험 데이터에 대한 모델링 사례를 통해 개발된 방법이 비선형성이 심한 현상을 모델링하는데 적용될 수 있음을 확인하였다.

• Asian-Australasian Journal of Animal Sciences
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• 제16권6호
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• pp.894-902
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• 2003

Prebiotics (peptides, N-acetyglucoamine, fructo-oligosaccharides, isomalto-oligosaccharides and galactooligosaccharides) were added to skim milk in order to improve the growth rate of contained Lactobacillus acidophilus, Lactobacillus casei, Bifidobacterium longum and Bifidobacterium bifidum. The purpose of this research was to study the potential synergy between probiotics and prebiotics when present in milk, and to apply modern optimization techniques to obtain optimal design and performance for the growth rate of the probiotics using a response surface-modeling technique. To carry out response surface modeling, the regression method was performed on experimental results to build mathematical models. The models were then formulated as an objective function in an optimization problem that was consequently optimized using a genetic algorithm and sequential quadratic programming approach to obtain the maximum growth rate of the probiotics. The results showed that the quadratic models appeared to have the most accurate response surface fit. Both SQP and GA were able to identify the optimal combination of prebiotics to stimulate the growth of probiotics in milk. Comparing both methods, SQP appeared to be more efficient than GA at such a task.

• 한국지능시스템학회논문지
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• 제9권6호
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• pp.591-597
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• 1999

플랜트 모델이나 경허에 근거하여 설계된 퍼지제어기를 실제 플랜트에 적용할 경우 무델링 오차와 플랜트에 대한 관련지식의 부족으로 만족할 만한 제어결과를 나타내지 못할 경우가 있다. 이 경우 제어성능을 향상시키기 위해 제어기의 제어인자를 다시 조정하여야 하고 이조정과정은 시행착오방법으로 수행되기 때문에 많은 시간과 비용을 필요로한다. 이런문제점을 해결하기 위해 본연구에서는 반응표면분석법을 이용하여 퍼지제어기를 설계한, 체계적이고 효과적인 방법을 제안한다. 첫단계에서는 모델링 모차를 포함하고 있는 기준 플랜트 모델에 대해 최적화 알고리즘을 이용하여 제어인자의 초기 최적조건을 결정한다. 다음 단계에선 반응표면분석법을 이용하여 제어인자의 최종 최적조건을 결정한다. 제안된 방법의 타당성을 보이기 위해 모의실험을 수행하였다.

• Computers and Concrete
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• 제19권6호
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• pp.737-744
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• 2017

Geopolymer Concrete is typically proportioned with activator solution leading to moderately high material cost. Such cost can be enduring in high value added applications especially when cost savings can be recognized in terms of reduction in size of the members. Proper material selection and mix proportioning can diminish the material cost. In the present investigation, a total of 27 mixes were arrived considering the mix parameters as liquid-binder ratio, slag content and sodium hydroxide concentration to study the mechanical properties of geopolymer concrete (GPC) mixes such as compressive strength, split tensile strength and flexural strength. The derived statistical Response Surface Methodology is beleaguered to develop cost effective GPC mixes. The estimated responses are not likely to contrast in linear mode with selected variables; a plan was selected to enable the model of any response in a quadratic manner. The results reveals that a fair correlation between the experimental and the predicted strengths.

• 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

• Journal of Welding and Joining
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• 제21권2호
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• pp.76-81
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• 2003

Due to the environmental problem, automotive companies are trying to reduce the weight of car body. Therefore, WP(Transformation Induced Plasticity) steels, which are hish strength and ductility have been developed. The application of TRIP steel to the members has been reported to increase the energy absorption capability. Welding process is a complex process; therefore deciding the optimal welding conditions is an effective method on the basis of the experimental data. However, using a trial-and-error method from the beginning in such a wide area, in order to decide the optimal conditions requires too many numbers of experiments. To overcome these problems and to decide the optimal conditions, response surface methodology was used. Response surface methodology is a collection of mathematical and statistical techniques that are for the modeling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. The introduced method was applied to the resistance spot welding process of the TRIP steel and the welding parameters were optimized. (Received December 6, 2002)

• 대한기계학회논문집A
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• 제27권3호
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• pp.381-386
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• 2003

Gradually engineering designers are determined based on computer simulations. Modeling of the computer simulation however is too expensive and time consuming in a complicate system. Thus, designers often use approximation models called metamodels, which represent approximately the relations between design and response variables. There arc general metamodels such as response surface model and kriging metamodel. Response surface model is easy to obtain and provides explicit function. but it is not suitable for highly nonlinear and large scaled problems. For complicate case, we may use kriging model that employs an interpolation scheme developed in the fields of spatial statistics and geostatistics. This class of into interpolating model has flexibility to model response data with multiple local extreme. In this study. metamodeling techniques are adopted to carry out the shape optimization of a funnel of Cathode Ray Tube. which finds the shape minimizing the local maximum principal stress Optimum designs using two metamodels are compared and proper metamodel is recommended based on this research.