• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.8
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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 Geotechnical Society
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• v.38 no.10
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• pp.17-29
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• 2022

Recently, the interest in integrated underground geospatial information mapping (IUGIM) to ensure the safety of underground spaces and facilities has been increasing. Because IUGIM is used in the fields of underground space development and underground safety management, the up-to-dateness and accuracy of information are critical. In this study, IUGIM and field data were classified, and the accuracy of IUGIM was improved by spatial interpolation. A spatial interpolation technique was used to process borehole data in IUGIM, and a quantitative evaluation was performed with mean absolute error and root mean square error through the cross-validation of seven interpolation results according to the technique and model. From the cross-validation results, accuracy decreased in the order of nonuniform rational B-spline, Kriging, and inverse distance weighting. In the case of Kriging, the accuracy difference according to the variogram model was insignificant, and Kriging using the spherical variogram exhibited the best accuracy.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.160-165
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• 2008

Kriging interpolation technique has been proposed by Danny Krige of South Africa to find the mineral distribution grade from information of geography and space. It is one of the generally used prediction technique for the mineral distribution grade and underground water level in wide scope also used in computer graphics fields by the ability for the surface regeneration This paper comprises two specific objectives. The first is to examine the applicability of Ordinary Kriging interpolation(OK) to finite element method that is based on variogram modeling in conjunction with different allowable limits of separation distance. The second is to investigate the accuracy according to theoretical variogram such as polynomial, Gauss, and spherical models.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.23-33
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• 2011

In this study, the data that examined the chloride ion concentration of ground water wells in the west coast of Jeollabukdo applying the GIS spatial estimation method were analyzed. In particular, through the designation of a validation point among ground water wells and then the analysis of error characteristics of the chloride ion concentration by each method of IDW (Inverse Distance Weight), Spline, and Kriging Interpolation method which is proper for estimating salt water intrusion was selected. The main conclusion from this study is as follows. First, as a result of analyzing the error characteristics of various spatial estimation methods by using the data from the chloride ion concentration of 485 ground water wells, the IDW method was found to be the most appropriate for estimating chloride ion concentration by salt water intrusion. Second, analyzing the average chloride ion concentration of the targeted regions has revealed that Gunsan-si with the record of $541mg/{\ell}$ did not meet water quality standards even for industrial use. Both Gimje-si and Gochang-gun satisfied drinking water quality standards and Buan-gun with $272mg/{\ell}$ was slightly below the standards for drinking water. Third, concerning the results of analysis according to administrative districts, as the areas adjacent to the west coast such as Daemyeong-dong, Joong-dong, Jangjae-dong and Guemam-dong in Gunsan-si are found to have very high chloride ion concentration, and both Hoehyeon-myeon and Daeya-myeon bounded by the Mankeong river did not meet water quality standards even for industrial use. From these facts, it is concluded that salt water intrusion has a great effect on Gunsan-si generally.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.701-705
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• 2006

강우자료는 수문 모델링 작업에서 가장 기초적인 수문학적 입력자료로 시간과 공간에 따른 변동성이 크므로 규명하기 복잡한 수문현상 중의 하나이다. 산악지역이 많은 우리나라의 지형학적 특성과 태풍, 장마 및 특히, 최근의 게릴라성 집중호우 등으로 인하여 이러한 변동성이 더욱 커지고 있는 실정이다. 장기간 실측된 수문기상 기초 자료가 부족한 우리나라의 실정상 홍수예보 및 수공구조물 설계를 위해 정확한 강우량 자료의 취득이 선행돼야 한다. 따라서 적절한 장소에 수문관측소 설치 및 관리를 통해 양호한 강우량 자료를 획득해야 하지만, 현장 여건상 등의 이유로 미계측 및 결측, 이상자료가 발생하고 있다. 따라서 이러한 미계측 혹은 결측지점의 우량을 추정할 수 있는 방법을 비교, 분석하여 적절한 보정과정을 수행할 필요가 있다. 그간의 연구에서는 미계측 지점 혹은 산악지역에서의 점 강우량 보정방법에 대한 연구가 진행되었지만, 본 연구에서는 '도시홍수재해관리기술연구사업단'에서 운영 중인 도시하천 유역 특히 소배수구역에서의 결측 자료에 대해 여러 추정 방법을 비교, 분석하여 적절한 방안을 찾고자 한다. 이를 위하여 중랑천 유역의 3개 소배수 구역(월계1 배수구역, 군자 배수구역, 어린이대공원 배수구역)에 설치된 3개 우량관측소와 건설교통부 관할 우량관측소 2개소의 우량자료를 사용하였다. 본 연구에서는 결측치 보간을 위하여 널리 이용되고 있는 산술평균법(Arithmetic Average method), 역거리법(Reciprocal Distance Squared method), 거리고도비율법(Ratio of Distance and Elevation method), 인근관측소와의 관계식 이용, 크리깅방법(Simple Kriging method)을 비교, 검토 적용하였다. 중랑천 유역의 소배수구역을 대상으로 연중 발생하는 큰 호우사상에 대해 임의의 강우관측소를 결측지점으로 가정하고 주변의 강우관측소로부터 각각의 방법을 이용해 가중치들을 산정하여 결측지점의 강우량 값을 보정하고자 하였다. 또한 각각의 방법을 이용하여 얻어진 결과에 대해 실측값과 보정값의 오차정도를 평균절대오차법(Mean Absolute Error)과 제곱평균제곱근오차법(Root Mean Squared Error)에 의해 산정하여 보정 방법간의 효율성을 검토하고자 하였다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.849-856
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• 2006

This paper is to examine the applicability of ordinary Kriging interpolation(OK) to the p-adaptivity of the finite element analysis that is based on variogram. In the p-refinement, the analytical domain has to be refined automatically to obtain an acceptable level of accuracy by increasing the p-level non-uniformly or selectively. In case of non-uniform p-distribution, the continuity between elements with different polynomial orders is achieved by assigning zero higher-order derivatives associated with the edge in common with the lower-order derivatives. It is demonstrated that the validity of the proposed approach by analyzing results for stress singularity problem.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1314-1319
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• 2008

Fatigue reliability problems are nowadays actively considered in the design of mechanical components. Recently, Dimension Reduction Method using Kriging approximation (KDRM) was proposed by the authors to efficiently calculate statistical moments of the response function. This method, which is more tractable for its sensitivity-free nature and providing the response PDF in a few number of analyses, is adopted in this study for the reliability analysis. Before applying this method to the practical fatigue problems, accuracies are studied in terms of parameters of the KDRM through a number of numerical examples, from which best set of parameters are suggested. In the fatigue reliability problems, good number of experimental data are necessary to get the statistical distribution of the S-N parameters. The information, however, are not always available due to the limited expense and time. In this case, a family of curves with prediction interval, called P-S-N curve, is constructed from regression analysis. Using the KDRM, once a set of responses are available at the sample points at the mean, all the reliability analyses for each P-S-N curve can be efficiently studied without additional response evaluations. The method is applied to a spring design problem as an illustration of practical applications, in which reliability-based design optimization (RBDO) is conducted by employing stochastic response surface method which includes probabilistic constraints in itself. Resulting information is of great practical value and will be very helpful for making trade-off decision during the fatigue design.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.434-439
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• 2019

Recently, interest in urban temperature change and ground surface temperature change has been increasing due to weather phenomenon due to global warming, heat island phenomenon caused by urbanization in urban areas. In Korea, weather data such as temperature and precipitation have been collected since 1904. In recent years, there are 96 ASOS stations and 494 AWS weather observation stations. However, in the case of terrestrial networks, terrestrial meteorological data except measurement points are predicted through interpolation because they provide point data for each installation point. In this study, to improve the resolution of ground surface temperature measurement, the surface temperature using satellite image was calculated and its applicability was analyzed. For this purpose, the satellite images of Landsat 8 OLI TIRS were obtained for Seoul Metropolitan City by seasons and transformed to surface temperature by applying NASA equation to the thermal bands. The ground measurement data was based on the temperature data measured by AWS. Since the AWS temperature data is station based point data, interpolation is performed by Kriging interpolation method for comparison with Landsat image. As a result of comparing the satellite image base surface temperature with the AWS temperature data, the temperature difference according to the season was calculated as fall, winter, summer, based on the RMSE value, Spring, in order of applicability of Landsat satellite image. The use of that attribute and AWS support starts at $2.11^{\circ}C$ and RMSE ${\pm}3.84^{\circ}C$, which reflects information from the extended NASA.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.8
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• pp.251-260
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• 2014

3D point data is utilized in various industry domains for its high accuracy to the surface information of an object. It is substantially utilized in geography for terrain scanning and analysis. Generally, 3D point data need to be changed by Gridding which produces a regularly spaced array of z values from irregularly spaced xyz data. But it requires long processing time and high resource cost to interpolate grid coordination. Kriging interpolation in Gridding has attracted because Kriging interpolation has more accuracy than other methods. However it haven't been used frequently since a processing is complex and slow. In this paper, we presented a parallel Gridding algorithm which contains Kriging and an application of grid data structure to fit MapReduce paradigm to this algorithm. Experiment was conducted for 1.6 and 4.3 billions of points from Airborne LiDAR files using our proposed MapReduce structure and the results show that the total execution time is decreased more than three times to the convention sequential program on three heterogenous clusters.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.407-415
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• 2008

This study presents the methodology to link with aerial photos for advancing the accuracy of topographic survey data that is used to calculate water volume in urban stream. First, GIS spatial interpolation technique as Inverse Distance Weight (IDW) and Kriging was applied to construct the terrain morphology to the sand-bar and grass area using cross-sectional survey data, and also validation point data was used to estimate the accuracy of created topographic data. As the result of comparison, IDW ($d^{-2}_{ij}$, 2nd square number) in Sand-bar area and Kriging Spherical model in grass area showed more efficient results in the construction of topographic data of river boundary. But the differences among interpolation methods are very slight. Image classification method, Minimum Distance Method (MDM) was applied to extract sand-bar and grass area that are located to river boundary efficiently and the elevation value of extracted layers was allocated to the water level point value. Water volume with topographic data from aerial photos shows the advanced accuracy of 13% (in sand-bar) and 12% (in grass) compared to the water volume of original terrain data. Therefore, terrain analysis method in river linking with aerial photos is efficient to the monitoring about sand-bar and grass area that are located in the downstream of Dam in flooding season, and also it can be applied to calculate water volume efficiently.