A Local RBF‐Based Differential Quadrature Method for Solving the Gray–Scott Model

ABSTRACT By using the local Radial Basis Function‐based Differential Quadrature method (LRBF‐DQ), a numerical simulation technique for Gray–Scott Reaction‐Diffusion (RD) systems was proposed. This paper has used the LRBF‐DQ method for space discretization with Crank–Nicolson format combined with nonlinear processing for time discretization to obtain the numerical format. In addition, the stability of this format was also analyzed by plotting the eigenvalue of the iteration matrix, and an unconditionally stable result was obtained. The LRBF‐DQ method combined with nonlinear processing was used for the first time to simulate the 2D Gray–Scott RD system in this article. After numerical testing, it was found that under the same conditions, this method has higher accuracy and can simulate better spot images with fewer points and longer time intervals.

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Publication Details

Journal
Numerical Methods for Partial Differential Equations
Published
2025-12-26
DOI
https://doi.org/10.1002/num.70065
Primary Topic
Model Reduction and Neural Networks
Type
article
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article

A Local RBF‐Based Differential Quadrature Method for Solving the Gray–Scott Model

Erjie Tian, Rahmatjan Imin, Kaysar Rahman
Numerical Methods for Partial Differential Equations
Model Reduction and Neural Networks
article

A Local RBF‐Based Differential Quadrature Method for Solving the Gray–Scott Model

Erjie Tian, Rahmatjan Imin, Kaysar Rahman
article en

Abstract

ABSTRACT By using the local Radial Basis Function‐based Differential Quadrature method (LRBF‐DQ), a numerical simulation technique for Gray–Scott Reaction‐Diffusion (RD) systems was proposed. This paper has used the LRBF‐DQ method for space discretization with Crank–Nicolson format combined with nonlinear processing for time discretization to obtain the numerical format. In addition, the stability of this format was also analyzed by plotting the eigenvalue of the iteration matrix, and an unconditionally stable result was obtained. The LRBF‐DQ method combined with nonlinear processing was used for the first time to simulate the 2D Gray–Scott RD system in this article. After numerical testing, it was found that under the same conditions, this method has higher accuracy and can simulate better spot images with fewer points and longer time intervals.

Numerical Methods for Partial Differential EquationsVol. 42(1)
Xinjiang University (CN)
Openalex Percentile: Top 31%
Model Reduction and Neural Networks
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