首页> 外文期刊>Engineering analysis with boundary elements >Reproducing kernel particle method for two-dimensional time-space fractional diffusion equations in irregular domains
【24h】

Reproducing kernel particle method for two-dimensional time-space fractional diffusion equations in irregular domains

机译:不规则域中二维时空分数扩散方程的再生核粒子法

获取原文
获取原文并翻译 | 示例

摘要

In recent years, the fractional differential equations have attracted a lot of attention due to their interested characteristics. Meshfree methods are highly accurate and have been extensively explored in engineering and mechanics fields. However, there is few research to develop the reproducing kernel particle method (RKPM), one of the widely used meshfree approach, for fractional partial differential equations. In this work, we solve time-space fractional diffusion equations in 2D regular and irregular domains. The temporal Caputo fractional derivatives are discretized by theL1 finite difference scheme and the spatial Laplacian fractional derivatives are discretized by RKPM based on the matrix transfer method. Especially, the corrected weighted shifted Grünwald–Letnikov scheme is utilized for temporally non-smooth solutions. Numerical examples in rectangular, circular, sector and human brain-like irregular domains are given to assess the efficiency and accuracy of the proposed numerical scheme. The spatial Laplacian fractional derivatives discretized by conventional finite difference method in the rectangular domain are also presented for comparison. The results indicate that RKPM is very effective for analyzing the considered fractional equations in various domains, which lays a concrete foundation for our further research of real application of human brain modeling.
机译:近年来,分数阶微分方程由于其有趣的特性而引起了广泛的关注。无网格方法非常准确,并且已经在工程和力学领域进行了广泛的探索。但是,很少有研究针对分数阶偏微分方程开发再生核粒子法(RKPM),这是一种广泛使用的无网格方法。在这项工作中,我们解决了二维规则和不规则域中的时空分数扩散方程。基于矩阵转移方法,通过L1有限差分方案离散时间Caputo分数导数,并通过RKPM离散空间Laplacian分数导数。特别是,校正后的加权移位的Grünwald–Letnikov方案用于时间上非光滑的解决方案。给出了矩形,圆形,扇形和人脑样不规则域中的数值示例,以评估所提出数值方案的效率和准确性。还提出了在矩形域中通过常规有限差分法离散化的空间拉普拉斯分数导数,以进行比较。结果表明,RKPM对于分析各个领域中的分数方程非常有效,这为我们进一步研究人脑模型的实际应用奠定了基础。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号