• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2006년도 공동학술대회 논문집
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• pp.155-160
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• 2006

이 논문에서 중력이상에서 광역이상과 잔여이상을 분리하는 문제를 다루었다. 지구통계학의 한 가지 방법인 인자크리깅 기법을 이용하여 공간필터링에 적용하였다. 이 방법은 일반적으로 광역이상은 공간적으로 큰 규모의 상관관계를 가지고 잔여이상은 좁은 지역에서 높은 상관관계를 가진다는 가정에서 출발하였다. 크리깅 방법의 하나인 인자크리깅(Factorial kriging)을 적용하기 위하여 영향 반경이 큰 지역과 작은 지역에 적합한 서로 다른 베리오그램 모델을 적용하여 각각을 광역이상과 잔여이상으로 구분하였다. 이 방법의 적용가능성을 검증하기 위하여 한 방향으로 증가하는 경향을 가정한 광역이상에 단일 이상체를 가정한 잔여이상이 더해진 합성 모델에 대하여 적용하였다. 베리오그램 모델은 각각 광역이상과 잔여이상을 나타내는 두개의 서로 다른 베리오그램 모델의 합으로 근사할 수 있었다. 따라서 서로 다른 두개의 베리오그램 모델에 대하여 인자 크리깅을 이용한 공간필터링을 적용한 결과 광역이상과 잔여이상을 구분할 수 있다. 이 방법을 폐갱도가 존재하는 지역에서의 고정밀중력탐사 자료에서 적용하여 잔여이상을 추출하였고, 다항식 접합법의 결과와도 비교하였다. 이 연구를 통하여 인자크리깅을 이용한 공간필터링 방법이 중력이상에서 광역이상과 잔여이상을 분리해 낼 수 있는 한 가지 방법이 될 수 있음 보였다.

• 대한기계학회논문집B
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• 제31권9호
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• pp.733-740
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• 2007

Microchannel heat sink shape optimization is performed using Kriging method. Design variables relating to microchannel width, depth and fin width are selected, and thermal resistance has been taken as objective function. Design points are selected through a three-level fractional factorial design of sampling method. Navier-Stokes and energy equations for laminar flow and conjugate heat transfer are solved at these design points using a finite volume solver. Solutions are carefully validated with experimental results. Using the numerically evaluated objective function, a surrogate model (Kriging) is constructed and optimum point is searched by sequential quadratic programming. The process of shape optimization greatly improves the thermal performance of microchannel heat sink under constant pumping power.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.2666-2671
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• 2007

This work presents microchannel heat sink shape optimization procedure using Kriging method. Design variables relating to microchannel width, depth and fin width are selected, and thermal resistance has been taken as objective function. Design points are selected through a three-level fractional factorial design of sampling method. Navier-Stokes and energy equations for laminar flow and conjugate heat transfer are solved at these design points using a finite volume solver. Solutions are carefully validated with experimental results. Using the numerically evaluated objective function, a surrogate model (Kriging) is constructed and optimum point is searched by sequential quadratic programming. The process of shape optimization greatly improves the thermal performance of microchannel heat sink under constant pumping power.

• 설비공학논문집
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• 제25권12호
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• pp.654-659
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• 2013

This paper presents a numerical optimization of louvered fins to enhance the JF factor in terms of the design parameters, including the fin pitch, the number of louvers, the louver angle, the fin thickness, and the re-direction louver length. We carried out a parametric study to select the three most important parameters affecting the JF factor, which were the fin pitch, number of louvers, and the louver angle. We optimally designed the louvered fin by using 3rd-order full factorial design, the kriging method, and a micro genetic algorithm. Consequently, the JF factor of the optimum model increased by 16% compared to that of the base model. Moreover, the optimum model reduced the pressure drop by 17% with a comparable heat transfer rate.

• 한국전산유체공학회지
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• 제14권4호
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• pp.31-40
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• 2009

Although optimization by sequentially refining metamodels is known to be computationally very efficient, the metamodel that can be used for this purpose is limited to Kriging method due to the difficulties related with sample points selections. The present study suggests a novel method for sequentially refining metamodels using Pareto Frontiers, which can be used independent of the type of metamodels. It is shown from the examples that the present method yields more accurate metamodels compared with full-factorial optimization and also guarantees global optimum irrespective of the initial conditions. Finally, in order to prove the generality of the present method, it is applied to a 2D transonic airfoil optimization problem, and the successful design results are obtained.

• 유체기계공업학회:학술대회논문집
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• 유체기계공업학회 2006년 제4회 한국유체공학학술대회 논문집
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• pp.367-370
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• 2006

Performances of multiple surrogate models are evaluated in a turbomachinery blade shape optimization. The basic models, i.e., Response Surface Approximation, Kriging and Radial Basis Neural Network models as well as weighted average models are tested for shape optimization. Global data based errors for each surrogates are used to calculate the weights. These weights are multiplied with the respective surrogates to get the final weighted average models. The design points are selected using three level fractional factorial D-optimal designs. The present approach can help address the multi-objective design on a rational basis with quantifiable cost-benefit analysis.

• Journal of Biosystems Engineering
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• 제39권4호
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• pp.377-388
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• 2014

Purpose: Determining the spatial structure of data is important in understanding within-field variability for site-specific crop management. An understanding of the spatial structures present in the data may help illuminate interrelationships that are important in subsequent explanatory analyses, especially when site variables are correlated or are a combined response to multiple causative factors. Methods: In this study, correlation, principal component analysis, and single and nested variogram models were applied to soil electrical conductivity and chemical property data of two fields in central Missouri, USA. Results: Some variables that were highly correlated, or were strongly expressed in the same principal component, exhibited similar spatial ranges when fitted with a single variogram model. However, single variogram results were dependent on the active lag distance used, with short distances (30 m) required to fit short-range variability. Longer active lag distances only revealed long-range spatial components. Nested models generally yielded a better fit than single models for sensor-based conductivity data, where multiple scales of spatial structure were apparent. Gaussian-spherical nested models fit well to the data at both short (30 m) and long (300 m) active lag distances, generally capturing both short-range and long-range spatial components. As soil conductivity relates strongly to profile texture, we hypothesize that the short-range components may relate to the scale of erosion processes, while the long-range components are indicative of the scale of landscape morphology. Conclusion: In this study, we investigated the effect of changing active lag distance on the calculation of the range parameter. Future work investigating scale effects on other variogram parameters, including nugget and sill variances, may lead to better model selection and interpretation. Once this is achieved, separation of nested spatial components by factorial kriging may help to better define the correlations existing between spatial datasets.

• 대한기계학회논문집A
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• 제35권10호
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• pp.1323-1328
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• 2011

자동차 로워암과 같이 다양한 형상설계변수를 갖는 부품모듈의 최근 설계경향은 설계자가 관심을 갖는 설계영역을 선형 및 2 차 다항식으로 근사화시키는 반응표면모델로 탐색하고, 다음 단계로서 최적설계를 수행하는 것이다. 본 연구에서는 로워암의 설계변수 변화에 따른 작용응력과 중량의 비선형적 변화뿐만 아니라 이의 예측에 적합한 신경망모델로 직교성과 균형성을 모두 만족시키는 다수준 전산실험계획법으로 설계영역을 탐색하였다. 구축된 신경망모델에 형상 설계변수의 공차도 같이 고려할 수 있는 식스시그마 제약조건을 적용하여 로워암의 공차 최적설계를 수행하고, 최적해의 공차 강건성을 확보하였다.