CLC number: O302; O451
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
Cited: 4
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LIU Xin. Radial point collocation method (RPCM) for solving convection-diffusion problems[J]. Journal of Zhejiang University Science A, 2006, 7(6): 1061-1067.
@article{title="Radial point collocation method (RPCM) for solving convection-diffusion problems",
author="LIU Xin",
journal="Journal of Zhejiang University Science A",
volume="7",
number="6",
pages="1061-1067",
year="2006",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2006.A1061"
}
%0 Journal Article
%T Radial point collocation method (RPCM) for solving convection-diffusion problems
%A LIU Xin
%J Journal of Zhejiang University SCIENCE A
%V 7
%N 6
%P 1061-1067
%@ 1673-565X
%D 2006
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2006.A1061
TY - JOUR
T1 - Radial point collocation method (RPCM) for solving convection-diffusion problems
A1 - LIU Xin
J0 - Journal of Zhejiang University Science A
VL - 7
IS - 6
SP - 1061
EP - 1067
%@ 1673-565X
Y1 - 2006
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2006.A1061
Abstract: In this paper, collocation method (RPCM)%29&ck%5B%5D=abstract&ck%5B%5D=keyword'>radial point collocation method (RPCM), a kind of meshfree method, is applied to solve convection-diffusion problem. The main feature of this approach is to use the interpolation schemes in local supported domains based on radial basis functions. As a result, this method is local and hence the system matrix is banded which is very attractive for practical engineering problems. In the numerical examination, RPCM is applied to solve non-linear convection-diffusion 2D Burgers equations. The results obtained by RPCM demonstrate the accuracy and efficiency of the proposed method for solving transient fluid dynamic problems. A fictitious point scheme is adopted to improve the solution accuracy while Neumann boundary conditions exist. The meshfree feature of the present method is very attractive in solving computational fluid problems.
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