• Title/Summary/Keyword: Radial basis function interpolation

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A comparative study of different radial basis function interpolation algorithms in the reconstruction and path planning of γ radiation fields

  • Yulong Zhang;Jinjia Cao;Biao Zhang;Xiaochang Zheng;Wei Chen
    • Nuclear Engineering and Technology
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    • v.56 no.7
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    • pp.2806-2820
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    • 2024
  • Accurate reconstruction of radiation field and path planning are very important for the safety of operators in the process of dismantling nuclear facilities. Based on radial basis function (RBF) interpolation algorithm, this paper discussed the application of inverse multiquadric radial basis Function (IMRBF) interpolation method to the reconstruction of gamma radiation field, and proved the feasibility of reconstructing a radiation field with multiple γ sources. The average relative errors of IMRBF interpolation results were 4.28% and 8.76%, respectively, for the experimental scenarios with single and double gamma sources. After comparing the consistency between the simulated scene and the experimental scene, IMRBF method and Cubic Spline method were respectively used to reconstruct the gamma radiation field by Geant4 simulation data. The results showed that the interpolation accuracy of IMRBF method was superior to that of Cubic Spline method. Further, more RBF interpolation algorithms were used to reconstruct the multi-γ source radiation field, and then the Probabilistic Roadmap (PRM) algorithm was used to optimize the human walking path in the radiation field reconstructed by different interpolation methods. The optimal paths in radiation fields generated by multiple interpolation methods were compared. The results herein contribute to a comprehensive understanding of RBF interpolation methods in reconstructing γ radiation fields and their application in optimizing paths in radiation environments. The insights may provide valuable information for decision-making in radiation protection during the decommissioning of nuclear facilities.

A Stress Analysis of Structural Element Using Meshfree Method(RPIM) (무요소법(RPIM)을 이용한 구조 요소의 응력해석)

  • Han, Sang-Eul;Lee, Sang-Ju;Joo, Jung-Sik
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2007.04a
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    • pp.495-500
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    • 2007
  • A Meshfree is a method used to establish algebraic equations of system for the whole problem domain without the use of a predefined mesh for the domain discretization. A point interpolation method is based on combining radial and polynomial basis functions. Involvement of radial basis functions overcomes possible singularity. Furthermore, the interpolation function passes through all scattered points in an influence domain and thus shape functions are of delta function property. This makes the implementation of essential boundary conditions much easier than the meshfree methods based on the moving least-squares approximation. This study aims to investigate a stress analysis of structural element between a meshfree method and the finite element method. Examples on cantilever type plate and stress concentration problems show that the accuracy and convergence rate of the meshfree methods are high.

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A boundary radial point interpolation method (BRPIM) for 2-D structural analyses

  • Gu, Y.T.;Liu, G.R.
    • Structural Engineering and Mechanics
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    • v.15 no.5
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    • pp.535-550
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    • 2003
  • In this paper, a boundary-type meshfree method, the boundary radial point interpolation method (BRPIM), is presented for solving boundary value problems of two-dimensional solid mechanics. In the BRPIM, the boundary of a problem domain is represented by a set of properly scattered nodes. A technique is proposed to construct shape functions using radial functions as basis functions. The shape functions so formulated are proven to possess both delta function property and partitions of unity property. Boundary conditions can be easily implemented as in the conventional Boundary Element Method (BEM). The Boundary Integral Equation (BIE) for 2-D elastostatics is discretized using the radial basis point interpolation. Some important parameters on the performance of the BRPIM are investigated thoroughly. Validity and efficiency of the present BRPIM are demonstrated through a number of numerical examples.

Point interpolation method based on local residual formulation using radial basis functions

  • Liu, G.R.;Yan, L.;Wang, J.G.;Gu, Y.T.
    • Structural Engineering and Mechanics
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    • v.14 no.6
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    • pp.713-732
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    • 2002
  • A local radial point interpolation method (LRPIM) based on local residual formulation is presented and applied to solid mechanics in this paper. In LRPIM, the trial function is constructed by the radial point interpolation method (PIM) and establishes discrete equations through a local residual formulation, which can be carried out nodes by nodes. Therefore, element connectivity for trial function and background mesh for integration is not necessary. Radial PIM is used for interpolation so that singularity in polynomial PIM may be avoided. Essential boundary conditions can be imposed by a straightforward and effective manner due to its Delta properties. Moreover, the approximation quality of the radial PIM is evaluated by the surface fitting of given functions. Numerical performance for this LRPIM method is further studied through several numerical examples of solid mechanics.

The Estimation of Hopper Dredging Capacity by Combination of DGPS and Echo Sounder (DGPS/Echo Sounder 조합에 의한 호퍼준설량 산정)

  • Kim Jin Soo;Seo Dong Ju;Lee Jong Chool
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.23 no.1
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    • pp.39-47
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    • 2005
  • In this study, three-dimensional information of submarine topography acquired by assembling DGPS method and echo sounder which mainly used in the marine survey. Moreover, the hopper dredging capacity in harbor public affair has been calculated by utilizing kriging, radial basis function and nearest neighbor interpolation. Also, utilization of DGPS/Echo sounder method in calculation of the dredging capacity have been confirmed by comparing and analyzing the hopper dredging capacity and the actual one as per each interpolation. According to this comparison result, in case of applying kriging interpolation, some 1.89% of error rate has been shown as difference of the contents is 15,364 ㎥ and in case of applying radial basis function interpolation and nearest neighbor interpolation, 3.9% and 4.4% of error rates have respectively shown. In case the study for application of the proper interpolation as per characteristics of submarine topography, is preceded in calculation of the dredging capacity relevant to harbor public affairs, it is expected that more speedy and correct calculation for the dredging capacity can be made.

IMPROVED STATIONARY $L_p$-APPROXIMATION ORDER OF INTERPOLATION BY CONDITIONALLY POSITIVE DEFINITE FUNCTIONS

  • Yoon, Jung-Ho
    • Journal of applied mathematics & informatics
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    • v.14 no.1_2
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    • pp.365-376
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    • 2004
  • The purpose of this study is to show that the accuracy of the interpolation method can be at least doubled when additional smoothness requirements and boundary conditions are met. In particular, as a basis function, we are interested in using a conditionally positive definite function $\Phi$ whose generalized Fourier transform is of the form $\Phi(\theta)\;=\;F(\theta)$\mid$\theta$\mid$^{-2m}$ with a bounded function F > 0.

Relation between Multidimensional Linear Interpolation and Regularization Networks

  • 엄경식;민병구
    • Journal of the Korean Institute of Intelligent Systems
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    • v.7 no.3
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    • pp.89-95
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    • 1997
  • This paper examines the relation between multidimensional linear interpolation (MDI) and regularization net-works, and shows that an MDI is a special form of regularization networks. For this purpose we propose a triangular basis function(TBF) network. Also we verified the condition when our proposed TBF becomes a well-known radial basis function (RBF).

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APPROXIMATION METHOD FOR SCATTERED DATA FROM SHIFTS OF A RADIAL BASIS FUNCTION

  • Yoon, Jung-Ho
    • Journal of applied mathematics & informatics
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    • v.27 no.5_6
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    • pp.1087-1095
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    • 2009
  • In this paper, we study approximation method from scattered data to the derivatives of a function f by a radial basis function $\phi$. For a given function f, we define a nearly interpolating function and discuss its accuracy. In particular, we are interested in using smooth functions $\phi$ which are (conditionally) positive definite. We estimate accuracy of approximation for the Sobolev space while the classical radial basis function interpolation applies to the so-called native space. We observe that our approximant provides spectral convergence order, as the density of the given data is getting smaller.

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Electrocardiogram Signal Compression with Reconstruction via Radial Basis Function Interpolation Based on the Vertex

  • Ryu, Chunha;Kim, Tae-Hun;Kim, Jungjoon;Choi, Byung-Jae;Park, Kil-Houm
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.13 no.1
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    • pp.31-38
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    • 2013
  • Patients with heart disease need long-term monitoring of the electrocardiogram (ECG) signal using a portable electrocardiograph. This trend requires the miniaturization of data storage and faster transmission to medical doctors for diagnosis. The ECG signal needs to be utilized for efficient storage, processing and transmission, and its data must contain the important components for diagnosis, such as the P wave, QRS-complex, and T wave. In this study, we select the vertex which has a larger curvature value than the threshold value for compression. Then, we reconstruct the compressed signal using by radial basis function interpolation. This technique guarantees a lower percentage of root mean square difference with respect to the extracted sample points and preserves all the important features of the ECG signal. Its effectiveness has been demonstrated in the experiment using the Massachusetts Institute of Technology and Boston's Beth Israel Hospital arrhythmia database.