• Title/Summary/Keyword: Kriging method

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OPTIMIZATION OF A DRIVER-SIDE AIRBAG USING KRIGING AND TABU SEARCH METHODS (크리깅과 타부탐색법을 이용한 운전석 에어백의 최적설계)

  • Kim, Jeung-Hwan;Lee, Kwom-Hee;Joo, Won-Sik
    • Proceedings of the KSME Conference
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    • 2004.04a
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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.

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Estimating Forest Carbon Stocks in Danyang Using Kriging Methods for Aboveground Biomass (크리깅 기법을 이용한 단양군의 산림 탄소저장량 추정 - 지상부 바이오매스를 대상으로 -)

  • Park, Hyun-Ju;Shin, Hyu-Seok;Roh, Young-Hee;Kim, Kyoung-Min;Park, Key-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.1
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    • pp.16-33
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    • 2012
  • The aim of this study is to estimate aboveground biomass carbon stocks using ordinary kriging(OK) which is the most commonly used type of kriging and regression kriging(RK) that combines a regression of the auxiliary variables with simple kriging. The analysis results shows that the forest carbon stock in Danyang is estimated at 3,459,902 tonC with OK and 3,384,581 tonC with RK in which the R-square value of the regression model is 0.1033. The result of RK conducted with sample plots stratified by forest type(deciduous, conifer and mixed) shows the lowest estimated value of 3,336,206 tonC and R-square value(0.35 and 0.18 respectively) is higher than that of when all sample plots used. The result of leave-one-out cross validation of each method indicates that RK with all sample plots reached the smallest root mean square error(RMSE) value(22.32 ton/ha) but the difference between the methods(0.23 ton/ha) is not significant.

Spatial Estimation of Point Observed Environmental Variables: A Case Study for Producing Rainfall Acidity Map (점관측 환경 인자의 공간 추정 - 남한 지역의 강우 산도 분포도 작성)

  • 이규성
    • Korean Journal of Remote Sensing
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    • v.11 no.3
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    • pp.33-47
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    • 1995
  • The representation of point-observed environmental variables in Geographic Information Systems(GIS) has often been inadequate to meet the need of regional-scale ecological and environmental applications. To create a map of continuous surface that would represent more reliable spatial variations for these applications, I present three spatial estimation methods. Using a secondary variable of the proximity to coast line together with rainfall acidity data collected at the 63 acid rain monitoring stations in Korea, average rainfall acidity map was cteated using co-kriging. For comparison, two other commonly used interpolation methods (inverse distance weighting and kriging) were also applied to rainfall acidity data without reference to the secondary variable. These estimation methods were evaluated by both visual assessments of the output maps and the quantitative comparison of error measures that were obtained from cross validation. The co-kriging method produced a rainfall acidity map that showed noticeable improvement in repoducing the inherent spatial pattern as well as provided lower statistical error as compared to the methods using only the primary variable.

A Study for Brought Characteristics of Gyeonggi-Do Using EOF of SPI (SPI의 EOF분석을 이용한 경기도 지역 가뭄특성 연구)

  • Chang, Yun-Gyu;Kim, Sang-Dan;Choi, Gye-Woon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2005.05b
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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.

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Development of a Model Combining Covariance Matrices Derived from Spatial and Temporal Data to Estimate Missing Rainfall Data (공간 데이터와 시계열 데이터로부터 유도된 공분산행렬을 결합한 강수량 결측값 추정 모형)

  • Sung, Chan Yong
    • Journal of Environmental Science International
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    • v.22 no.3
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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.

A NOVEL METHOD FOR REFINING A META-MODEL BY PARETO FRONTIER (파레토 프론티어를 이용한 메타모델 정예화 기법 개발)

  • Jo, S.J.;Chae, S.H.;Yee, K.J.
    • Journal of computational fluids engineering
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    • v.14 no.4
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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.

Wing Design Optimization for a Long-Endurance UAV using FSI Analysis and the Kriging Method

  • Son, Seok-Ho;Choi, Byung-Lyul;Jin, Won-Jin;Lee, Yung-Gyo;Kim, Cheol-Wan;Choi, Dong-Hoon
    • International Journal of Aeronautical and Space Sciences
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    • v.17 no.3
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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.

Structural Design of a Front Lower Control Arm Considering Durability (내구성을 고려한 하부 컨트롤 암의 구조설계)

  • Park, Han-Seok;Kim, Jong-Kyu;Seo, Sun-Min;Lee, Kwon-Hee;Park, Young-Chul
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.8 no.4
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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.

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A Study on Spatial Prediction of Water Quality Constituents Using Spatial Model (공간모형을 이용한 수질오염물질의 공간적 예측 및 평가에 대한 연구)

  • Kang, Taegu;Lee, Hyuk;Kang, Ilseok;Heo, Tae-Young
    • Journal of Korean Society on Water Environment
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    • v.30 no.4
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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.