• Title/Summary/Keyword: Kriging technique

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Accuracy of Kriging interpolation method with respect to variogram model (베리오그램 모델에 따른 크리깅 보간법의 정확성)

  • Woo, Kwang-Sung;Shin, Young-Shik;Lee, Hui-Jeong
    • 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.

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A novel meshfree model for buckling and vibration analysis of rectangular orthotropic plates

  • Bui, Tinh Quoc;Nguyen, Minh Ngoc
    • Structural Engineering and Mechanics
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    • v.39 no.4
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    • pp.579-598
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    • 2011
  • The present work mainly reports a significant development of a novel efficient meshfree method for vibration and buckling analysis of orthotropic plates. The plate theory with orthotropic materials is followed the Kirchhoff''s assumption in which the only deflection is field variable and approximated by the moving Kriging interpolation approach, a new technique used for constructing the shape functions. The moving Kriging technique holds the Kronecker delta property, thus it makes the method efficiently in imposing the essential boundary conditions and no special techniques are required. Assessment of numerical results is to accurately illustrate the applicability and the effectiveness of the proposed method in the class of eigenvalue problems.

Analysis of the Front Disk Brake Squeal Using Kriging Method (크리깅기법을 이용한 전륜 디스크 브레이크 모델의 스퀼 저감 해석)

  • Sim, Hyun-Jin;Park, Sang-Gil;Kim, Heung-Seob;Oh, Jae-Eung
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.18 no.10
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    • pp.1042-1048
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    • 2008
  • Disc brake noise is an important customer satisfaction and warranty issue for many manufacturers as indicated by technical literature regarding the subject coming from Motor Company. This research describes results of a study to assess disk brake squeal propensity using finite element methods and optimal technique (Kriging). In this study, finite element analysis has been performed to determine likely modes of brake squeal. This paper deals with friction-induced vibration of disc brake system under contact friction coefficient. A linear, finite element model to represent the floating caliper disc brake system is proposed. The complex eigen-values are used to investigate the dynamic stability and in order to verify simulations which are based on the FEM model. In this paper, Kriging from among the meta-modeling techniques is proposed for an optimal design scheme to reduce the brake squeal noise.

Kriging Dimension Reduction Method for Reliability Analysis in Spring Design (스프링 설계문제의 신뢰도 해석을 위한 크리깅 기반 차원감소법의 활용)

  • Gang, Jin-Hyuk;An, Da-Wn;Won, Jun-Ho;Choi, Joo-Ho
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2008.04a
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    • pp.422-427
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    • 2008
  • This study is to illustrate the usefulness of Kriging Dimension Reduction Method(KDRM), which is to construct probability distribution of response function in the presence of the physical uncertainty of input variables. DRM has recently received increased attention due to its sensitivity-free nature and efficiency that considerable accuracy is obtained with only a few number of analyses. However, the DRM has a number of drawbacks such as instability and inaccuracy for functions with increased nonlinearity. As a remedy, Kriging interpolation technique is incorporated which is known as more accurate for nonlinear functions. The KDRM is applied and compared with MCS methods in a compression coil spring design problem. The effectiveness and accuracy of this method is verified.

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Optimization of a Train Suspension using Kriging Meta-model (크리깅 메타모델에 의한 철도차량 현수장치 최적설계)

  • Lee, Kwang-Ki;Lee, Tae-Hee;Park, Chan-Kyoung
    • Proceedings of the KSME Conference
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    • 2001.06c
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    • pp.339-344
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    • 2001
  • In recent engineering, the designer has become more and more dependent on the computer simulations such as FEM (Finite Element Method) and BEM (Boundary Element Method). In order to optimize such implicit models more efficiently and reliably, the meta-modeling technique has been developed for solving such a complex problems combined with the DACE (Design and Analysis of Computer Experiments). It is widely used for exploring the engineer's design space and for building meta-models in order to facilitate an effective solution of multi-objective and multi-disciplinary optimization problems. Optimization of a train suspension is performed according to the minimization of forty-six responses that represent ten ride comforts, twelve derailment quotients, twelve unloading ratios, and twelve stabilities by using the Kriging meta-model of a train suspension. After each Kriging meta-model is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called SQP (Sequential Quadratic Programming).

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Shape Optimization of A Micromixer with Herringbone Grooves Using Kriging Model (헤링본 미세혼합기의 크리깅 모델을 사용한 최적형상설계)

  • Ansari, Mubashshir Ahmad;Kim, Kwang-Yong
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.31 no.8
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    • pp.711-717
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    • 2007
  • Shape optimization of a staggered herringbone groove micromixer using three-dimensional Navier-Stokes analysis has been carried using Kriging model. The analysis of the degree of mixing is performed by the calculation of spatial data statistics. The calculation of the variance of the mass fraction at various nodes on a plane in the channel is used to quantify mixing. A numerical optimization technique with Kriging model is applied to optimize the shape of the grooves on a single wall of the channel. Three design variables, namely, the ratio of groove width to groove pitch, the ratio of the groove depth to channel height ratio and the angle of the groove, are selected for optimization. A mixing index is used as the objective function. The results of the optimization show that the mixing is very sensitive to the shape of the groove which can be used in controlling mixing in microdevices.

Spatial Distribution Analysis of Metallic Elements in Dustfall using GIS (GIS를 이용한 강하분진 중 금속원소의 공간분포분석)

  • 윤훈주;김동술
    • Journal of Korean Society for Atmospheric Environment
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    • v.13 no.6
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    • pp.463-474
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    • 1997
  • Metallic elements in dustfall have been known as notable air pollutants directly or indirectly influencing human health and wealth. The first aim of this study was to obtain precise spatial distribution patterns of 5 elements (Pb, Zn, K, Cr, and Al) in dustfall around Suwon area. To predict isometric lines of metal fluxes deposited on unsupervised random sites, the study has applied both spatial statistics as a receptor model and a GIS (geographic information system). Total of 31 sampling sites were selected in the study area (roughly 3 by 3 km grid basis) and dustfall samples were then collected monthly basis by the British deposit gauges from Dec., 1995 to Nov., 1996. The metallic elements in the dustfall were then analyzed by an atomic absorption spectrometer (AAS). On the other hand, a base map overlapped by 7 layers was constructed by using the AutoCAD R13 and ARC/INFO 3.4D. Four different spatial interpolation and expolation techniques such as IDW (inverse distance weighted averaging), TIN (triangulated irregular network), polynomial regression, and kriging technique were examined to compare spatial distribution patterns. Each pattern obtained by each technique was substantally different as varing pollutant types, land of use types, and topological conditions, etc. Thus, our study focused intensively on uncertainty analysis based on a concept of the jackknife and the sum of error distance. It was found that a kriging technique was the best applicalbe in this study area.

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Sensitivity Validation Technique for Sequential Kriging Metamodel (순차적 크리깅 메타모델의 민감도 검증법)

  • Huh, Seung-Kyun;Lee, Jin-Min;Lee, Tae-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.8
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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.

Comparison of Ordinary Kriging and Artificial Neural Network for Estimation of Ground Profile Information in Unboring Region (미시추 구간의 지반 층상정보 예측을 위한 정규 크리깅 및 인공신경망 기법의 비교)

  • Chun, Chanjun;Choi, Changho;Cho, Jinwoo
    • Journal of the Korean GEO-environmental Society
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    • v.20 no.3
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    • pp.15-20
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    • 2019
  • A large amount of site investigation data is essential to obtain reliable design value. However, site investigations are generally insufficient due to economic problems. It is important to estimate the ground profile information in unboring region for accurate earthwork-volume prediction, and such ground profile information can be estimated by using the geo-statistical approach. Furthermore, the ground profile information in unboring region can be estimated by training a model via machine learning technique such as artificial neural network. In this paper, artificial neural network-based model estimated the ground profile information in unboring region, and this results were compared with that of ordinary kriging technique, which is referred to the geo-statistical approach. Accordingly, a total of 84 ground profile information in an actual bridge environment was split into 75 training and 9 test databases. The observed ground profile information of the test database was compared with those of the ordinary kriging technique and artificial neural network.

Population Distribution Estimation Using Regression-Kriging Model (Regression-Kriging 모형을 이용한 인구분포 추정에 관한 연구)

  • Kim, Byeong-Sun;Ku, Cha-Yong;Choi, Jin-Mu
    • Journal of the Korean Geographical Society
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    • v.45 no.6
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    • pp.806-819
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    • 2010
  • Population data has been essential and fundamental in spatial analysis and commonly aggregated into political boundaries. A conventional method for population distribution estimation was a regression model with land use data, but the estimation process has limitation because of spatial autocorrelation of the population data. This study aimed to improve the accuracy of population distribution estimation by adopting a Regression-Kriging method, namely RK Model, which combines a regression model with Kriging for the residuals. RK Model was applied to a part of Seoul metropolitan area to estimate population distribution based on the residential zones. Comparative results of regression model and RK model using RMSE, MAE, and G statistics revealed that RK model could substantially improve the accuracy of population distribution. It is expected that RK model could be adopted actively for further population distribution estimation.