• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 춘계학술대회
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• pp.1035-1040
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• 2004

In the proto design stage of a new car, the performance of an occupant protection system is often evaluated by CAE instead of the real test. CAE predicts and recommends the appropriate design values hence reducing the number of the real tests. However, the existing researches using CAE in predicting the performances do not consider the uncertainties of parameters, in which inconsistency between the actual test results and CAE exists. In this research, the optimization procedure of a protection system such as airbag and load limiter is suggested for the frontal collision. The DACE modeling known as Kriging interpolation is introduced to obtain the meta model of the system followed by the tabu search method to determine a global optimum. Finally, the distribution of a suggested design is determined through the Monte-Carlo Simulation.

• 한국지리정보학회지
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• 제15권1호
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• pp.16-33
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• 2012

본 연구에서는 크리깅 기법 중 가장 일반적으로 사용되고 있는 정규 크리깅(ordinary kriging)과 여러 보조 자료를 활용한 회귀 모델에 크리깅 기법을 결합한 형태인 회귀 크리깅(regression kriging)을 이용하여 지상부 바이오매스의 탄소저장량 추정을 시도하였다. 분석 결과 단양군의 산림 탄소저장량은 정규 크리깅의 경우 3,459,902 tonC, 회귀 크리깅의 경우 3,384,581 tonC로 추정되었으며 회귀 크리깅에 이용된 회귀 모델의 결정계수는 0.1033으로 나타났다. 표본점을 임상별로(활엽수림, 침엽수림&혼효림) 층화하여 회귀 크리깅을 수행한 경우에는 탄소저장량은 3,336,206 tonC로 가장 낮게 추정되었으며 회귀 모델의 결정 계수는 각각 0.35, 0.18로 표본점 전체를 이용했을 때보다 높은 값을 보였다. 각 기법의 교차 검증(cross validation) 결과 표본점 전체를 이용한 회귀 크리깅의 RMSE(22.32 ton/ha)가 가장 낮았으나 기법간의 차이(0.23 ton/ha)는 크지 않은 것으로 나타났다.

• 대한원격탐사학회지
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• 제11권3호
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• pp.33-47
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• 1995

기후, 토양, 대기, 지질, 지하수 등과 관련된 측정자료는 지역적 규모의 생태 및 환경 목 적의 지리정보시스템(GIS)에서 자주 요구되는 공간자료이다. 이와 같은 환경 인자는 자료의 특성 상 한정된 지점에서의 점관측자료(point observation)에 의존하여 전체 대상 지역의 지리적 분포 를 추정하는 보간법(spatial interpolation)을 이용하여 수치지도의 형태로 변환되고 있으나, 그 추 정의 정확도와 관련하여 다른 GIS 공간자료와의 연계분석시 많은 주의가 요망되고 있다. 전국 63 개소에서 측정된 강우산도 자료를 이용하여 보다 정확도가 높은 연속면(continuous surface)을 나 타내는 디지탈지도를 제작하기 위하여 세 가지 공간추정방법을 적용하였다. 미측정지점에서의 강 우산도를 추정하기 위하여 강우산도와 상관관계가 높은 서남해안으로부터의 거리를 보조변수로 사용하여 Co-kriging 방법을 적용하였고, 위의 추정 결과와의 비교 목적으로 보조변수를 사용하 지 않는 거리반비례평균법과 Kriging을 이용하였다. 세 가지 공간보간법에 의하여 추정된 연속면 지도를 비교한 결과, 보조 변수를 이용한 Co-kriging 방법에 의한 수치지도가 강우산도의 미세한 분포 양상을 나타내는 데 적합하게 판정되었다. 또한 실지 관측지와 추정치와의 차이를 분석하는 역검정방법을 이용하여 추정오차를 구한 결과, Co-kriging에 의한 추정치가 최소의 오차를 보여 주었다. Co-kriging이 현재의 GIS 사용자들에서 다소 익숙치 않은 공간추정방법이지만, 여러 종 류의 점관측 환경인자의 공간추정에 매우 적합한 방법이라 할 수 있다.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2005년도 창립60주년 기념 추계 학술대회
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• pp.196.2-196.2
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• 2005

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2005년도 학술발표회 논문집
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• pp.867-872
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• 2005

This study introduces a method to evaluate the probability of a specific area to be affected by a drought of a given severity and shows its potential for investigating agricultural drought characteristics. The method is applied to Gyeonggi as a case study. The proposed procedure includes Standard Precipitation Index(SPI) time series, which are linearly transformed by the Empirical Orthogonal Functions(EOF) method, These EOFs are extended temporally with AutoRegressive Moving Average(ARMA) method and spatially with Kriging method. By performing these simulations, long time series of SPI can be simulated for each designed grid cell in whole Gyeonggi area. The probability distribution functions of the area covered by a drought and the drought severity are then derived and combined to produce drought severity-area-frequency(SAF) curves.

• 한국환경과학회지
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• 제22권3호
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• pp.303-308
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• 2013

This paper proposed a new method for estimating missing values in time series rainfall data. The proposed method integrated the two most widely used estimation methods, general linear model(GLM) and ordinary kriging(OK), by taking a weighted average of covariance matrices derived from each of the two methods. The proposed method was cross-validated using daily rainfall data at thirteen rain gauges in the Hyeong-san River basin. The goodness-of-fit of the proposed method was higher than those of GLM and OK, which can be attributed to the weighting algorithm that was designed to minimize errors caused by violations of assumptions of the two existing methods. This result suggests that the proposed method is more accurate in missing values in time series rainfall data, especially in a region where the assumptions of existing methods are not met, i.e., rainfall varies by season and topography is heterogeneous.

• 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.

• International Journal of Aeronautical and Space Sciences
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• 제17권3호
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• pp.423-431
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• 2016

In this study, wing design optimization for long-endurance unmanned aerial vehicles (UAVs) is investigated. The fluid-structure integration (FSI) analysis is carried out to simulate the aeroelastic characteristics of a high-aspect ratio wing for a long-endurance UAV. High-fidelity computational codes, FLUENT and DIAMOND/IPSAP, are employed for the loose coupling FSI optimization. In addition, this optimization procedure is improved by adopting the design of experiment (DOE) and Kriging model. A design optimization tool, PIAnO, integrates with an in-house codes, CAE simulation and an optimization process for generating the wing geometry/computational mesh, transferring information, and finding the optimum solution. The goal of this optimization is to find the best high-aspect ratio wing shape that generates minimum drag at a cruise condition of $C_L=1.0$. The result shows that the optimal wing shape produced 5.95 % less drag compared to the initial wing shape.

• 한국기계가공학회지
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• 제8권4호
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• pp.69-75
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• 2009

Recently developed automotive components are getting lighter providing a higher fuel efficiency and performance. Following the current trend, this study proposes a structural optimization method for the lower control arm installed at the front side of a Vehicle. Lightweight design of lower control arm can be achieved through design and material technology. In this research, the shape of lower control arm was determined by applying the optimization technology and aluminum was selected as a steel-substitute material. Strength performance is the most important design requirement in the structural design of a control arm. This study considers the static strength in the optimization process. For the optimum design, the durability analysis is performed to predict its fatigue life. In this study, the kriging interpolation method is adopted to obtain the minimum weight satisfying the strength constraint. Optimum designs are obtained by the in-house program, EXCEL-Kriging. Also, based on the optimum model obtained for the static strength, the optimization of Index of Fatigue Durability is carried out to get th optimum fatigue performance.

• 한국물환경학회지
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• 제30권4호
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• pp.409-417
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• 2014

Spatial prediction methods have been useful to determine the variability of water quality in space and time due to difficulties in collecting spatial data across extensive spaces such as watershed. This study compares two kriging methods in predicting BOD concentration on the unmonitored sites in the Geum River Watershed and to assess its predictive performance by leave-one-out cross validation. This study has shown that cokriging method can make better predictions of BOD concentration than ordinary kriging method across the Geum River Watershed. Challenges for the application of cokriging on the spatial prediction of surface water quality involve the comparison of network-distance-based relationship and euclidean-distance-based relationship for the improvement in the predictive performance.