• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 한국지하수토양환경학회 2004년도 총회 및 춘계학술발표회
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• pp.477-481
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• 2004

지하수 수질자료의 분포가 광역적이고 자료의 수가 많은 지역과 자료의 분포가 국부적이고 갯수가 적은 지역을 선정하여, 모수적 통계기법인 정규크리깅과 비모수적 통계기법인 지시크리깅을 동시에 적용하였다. 베리오그램 분석은 각 수질자료의 원시 자료와 제한값을 적용하여 제한값 보다 낮거나 동일하면 '1' 의 값으로, 제한값 보다 높으면 '0' 의 값으로 변환된 자료에 대해 실시하였는데, 원시 염소이온 성분은 선형 모델이 선정되었으며, 비소 성분은 지수형 모델이 가장 적합한 것으로 선정되었다. 변환된 염소이온 성분과 비소 성분은 모두 구상형 모델이 가장 적합한 것으로 선정되었다. 정규크리깅과 지시크리깅 기법을 이용하여 지하수 오염 분포도를 작성하여 비교해 본 결과, 정규크리깅 기법은 연구지역의 자료 분포, 갯수와 범위의 영향을 크게 받는 것으로 나타났고, 지시크리깅 기법은 연구지역의 자료 분포와 특히 제한값에 따라 변환된 자료의 갯수의 영향을 크게 받는 것으로 나타났다. 정량적으로 나타낼 수 정규크리깅 기법과 정성적으로 나타낼 수 있는 지시크리깅 기법을 같이 적용한다면 지하수 오염 현황을 효과적으로 파악할 수 있을 것으로 판단된다.

• Transactions of the Korean Society of Mechanical Engineers A
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• 제34권5호
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• pp.541-547
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• 2010

The rigorous validation of the accuracy of metamodels is an important topic in research on metamodel techniques. Although a leave-k-out cross-validation technique involves a considerably high computational cost, it cannot be used to measure the fidelity of metamodels. Recently, the mean$_0$ validation technique has been proposed to quantitatively determine the accuracy of metamodels. However, the use of mean$_0$ validation criterion may lead to premature termination of a sampling process even if the kriging model is inaccurate. In this study, we propose a new validation technique based on the mean and variance of the response evaluated when sequential sampling method, such as maximum entropy sampling, is used. The proposed validation technique is more efficient and accurate than the leave-k-out cross-validation technique, because instead of performing numerical integration, the kriging model is explicitly integrated to accurately evaluate the mean and variance of the response evaluated. The error in the proposed validation technique resembles a root mean squared error, thus it can be used to determine a stop criterion for sequential sampling of metamodels.

• Transactions of the Korean Society of Mechanical Engineers A
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• 제41권5호
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• pp.381-389
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• 2017

The kernel density was determined based on sampling points obtained in a Markov chain simulation and was assumed to be an important sampling function. A Kriging metamodel was constructed in more detail in the vicinity of a limit state. The failure probability was calculated based on importance sampling, which was performed for the Kriging metamodel. A pre-existing method was modified to obtain more sampling points for a kernel density in the vicinity of a limit state. A stable numerical method was proposed to find a parameter of the kernel density. To assess the completeness of the Kriging metamodel, the possibility of changes in the calculated failure probability due to the uncertainty of the Kriging metamodel was calculated.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 한국지하수토양환경학회 2004년도 총회 및 춘계학술발표회
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• pp.482-486
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• 2004

울산지역 수질특성에 관하여 연구하기 위해 228개 지점에서 수질성분 25개 항목을 분석하였다. 그 성분중 지하수 음용수 9개 수질성분(pH, EC, TDS, Cl, Mn, NO$_3$, SO$_4$, F, Fe)에 관해 수질분포특성 및 오염도를 나타내기 위해 모수적 통계기법인 정규크리깅과 비모수적 통계기법인 지시크리깅 기법을 적용하였다. OK와 IK의 성분별 베리오그램 분석한 결과 OK의 경우 모든 수질성분은 구상형모델(Spherical model)로 선정되었으며, IK의 경우 pH, TDS, SO$_4$, Cl, Mn, F, Fe 성분은 구상형모델로, EC는 지수형모델로, NO$_3$는 선형모델로 선정되었다. 그 결과 정규크리깅의 경우 연구지역의 수질특성을 정량적 분포특성이 잘 나타났다. 특히 태화강, 인접한 남구일원과 중구일원, 북구의 북서 일원 그리고 동구의 방어동일원에서 수질성분 9개 성분들이 다소 높게 나타났다. 특히 EC, TDS 그리고 Cl$^{-}$ NO$_3$ 성분이 높게 나타났다. 그리고 지시크리깅의 경우 정규크리깅과 비교하여 이상치가 크게 영향을 미칠 수 있는 통계학적인 오류를 보완하여 분석한 결과 울산지역 9개 성분 오염도는 EC>TDS>NO$_3$>pH>Fe>Mn>Cl>SO$_4$>F 순으로 오염특성이 나타났다.

• Transactions of the Korean Society of Mechanical Engineers A
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• 제36권8호
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• pp.873-879
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• 2012

Metamodels have been developed with a variety of design optimization techniques in the field of structural engineering over the last decade because they are efficient, show excellent prediction performance, and provide easy interconnections into design frameworks. To construct a metamodel, a sequential procedure involving steps such as the design of experiments, metamodeling techniques, and validation techniques is performed. Because validation techniques can measure the accuracy of the metamodel, the number of presampled points for an accurate kriging metamodel is decided by the validation technique in the sequential kriging metamodel. Because the interpolation model such as the kriging metamodel based on computer experiments passes through responses at presampled points, additional analyses or reconstructions of the metamodels are required to measure the accuracy of the metamodel if existing validation techniques are applied. In this study, we suggest a sensitivity validation that does not require additional analyses or reconstructions of the metamodels. Fourteen two-dimensional mathematical problems and an engineering problem are illustrated to show the feasibility of the suggested method.

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

In this paper, we propose a spatial filtering scheme using factorial kriging, one of geostatistical filtering methodin order to separate regional and residual gravity anomaly. This scheme is based on the assumption that regional anomalies have longer distance relation and residual anomalies have effected on smaller range. We decomposed gravity anomalies intotwo variogram models with long and short effectiveranges by means of factorial kriging. And decomposed variogram models produced the regional and residual anomalies. This algorithm was examined using by a synthetic gravity data, and applied to a real microgravity data to figure out abandoned mineshaft.

• Journal of the Computational Structural Engineering Institute of Korea
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• 제37권2호
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• pp.95-101
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• 2024

This paper introduces an optimized design for a sensor bracket used to measure the wear amount of an automobile brake pad, based on a dynamic kriging surrogate model. During testing, the temperature of the brake pad can increase beyond 600℃, which often causes sensor malfunction. Therefore, it is essential to optimize the shape of the sensor bracket to minimize heat transfer. To reduce the computational cost of the optimization, the heat-transfer simulation is replaced by a dynamic kriging surrogate model. Dynamic kriging utilizes the best combination of correlation and basis functions and constructs an accurate surrogate model. Following optimization, the temperature of the sensor position decreases by 7.57%. The results from the surrogate model under optimum conditions are verified by a heat-transfer simulation, and the design optimization using a surrogate model is found to be effective.

• Journal of the Korean Association of Geographic Information Studies
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• 제15권1호
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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.

• Transactions of the Korean Society of Mechanical Engineers A
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• 제34권8호
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• pp.989-996
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• 2010

Statistical regression and/or interpolation models have been used for data analysis and response prediction using the results of the physical experiments and/or computer simulations in structural engineering fields. These models have been employed during the last decade to develop a variety of design methodologies. However, these models only handled responses with respect to space variables such as size and shape of structures and cannot handle time-variant dynamic responses, i.e. response varying with time. In this research, statistical space-time metamodels based on multiple response approach that can handle responses with respect to both space variables and a time variable are proposed. Regression and interpolation models such as the response surface model (RSM) and kriging model were developed for handling time-variant dynamic responses of structural engineering. We evaluate the accuracies of the responses predicted by the two statistical space-time metamodels by comparing them with the responses obtained by the physical experiments and/or computer simulations.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제34권1호
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• pp.91-98
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• 2016

In order to apply Kriging methods for geostatistics of spatial data, an estimation of spatial coherency functions is required priorly based on the spatial distance between measurement points. In the study, the typical coherency functions, such as semi-variogram, homeogram, and covariance function, were estimated using the national geoid model. The test area consisting of 2°×2° and the Unified Control Points (UCPs) within the area were chosen as sampling measurements of the geoid. Based on the distance between the control points, a total of 100 sampling points were grouped into distinct pairs and assigned into a bin. Empirical values, which were calculated with each of the spatial coherency functions, resulted out as a wave model of a semi-variogram for the best quality of fit. Both of homeogram and covariance functions were better fitted into the exponential model. In the future, the methods of various Kriging and the functions of estimated spatial coherency need to be studied to verify the prediction accuracy and to calculate the Mean Squared Prediction Error (MSPE).