A universal preprocessing algorithm of average kernel method with Gauss-Laguerre quadrature for double integrals

Fuente: arXiv
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Autores principales: Pan, Kejun, Xie, Mingliang
Formato: Preprint
Publicado: 2025
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author Pan, Kejun
Xie, Mingliang
author_facet Pan, Kejun
Xie, Mingliang
contents To address the computational challenges posed by nonlinear collision kernels in the Smoluchowski equation, this study proposes a universal preprocessing algorithm for the average kernel method based on the Gauss-Laguerre quadrature for double integrals. With this algorithm, the numerical code accurately and efficiently determines the pre-exponential factor of the average kernel. Additionally, the exact pre-exponential factors of the four fundamental average kernels and their associated truncation error estimations were analyzed. The results demonstrate the reasonability and reliability of the preprocessing algorithm.
format Preprint
id arxiv_https___arxiv_org_abs_2502_13378
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A universal preprocessing algorithm of average kernel method with Gauss-Laguerre quadrature for double integrals
Pan, Kejun
Xie, Mingliang
Numerical Analysis
Fluid Dynamics
To address the computational challenges posed by nonlinear collision kernels in the Smoluchowski equation, this study proposes a universal preprocessing algorithm for the average kernel method based on the Gauss-Laguerre quadrature for double integrals. With this algorithm, the numerical code accurately and efficiently determines the pre-exponential factor of the average kernel. Additionally, the exact pre-exponential factors of the four fundamental average kernels and their associated truncation error estimations were analyzed. The results demonstrate the reasonability and reliability of the preprocessing algorithm.
title A universal preprocessing algorithm of average kernel method with Gauss-Laguerre quadrature for double integrals
topic Numerical Analysis
Fluid Dynamics
url https://arxiv.org/abs/2502.13378