采用高斯型核和无网格离散化的非局部对流扩散模型

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Hao Tian, Xiaojuan Liu, Chenguang Liu, Lili Ju
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引用次数: 0

摘要

从分析结构工程中的裂纹和断裂行为,到模拟材料科学中的异常扩散现象,以及模拟异质环境中的对流过程,非局部模型已在一系列关键领域的数值模拟中显示出其不可或缺的作用。在本研究中,我们提出了一种利用高斯型核构建非局部对流扩散模型的新框架。我们的框架通过将恒定扩散系数与高斯核的方差相关联来唯一地制定扩散项。同时,对流项是通过将可变速度场作为多变量高斯分布的期望值积分到核中来定义的,从而促进了对流输运现象的全面表示。我们严格建立了所提出的非局部模型的良好拟合性,并推导出最大值原理,以确保其在数值模拟中的稳定性和可靠性。此外,我们还开发了一种无网格离散化方案,专门用于对我们的模型进行数值模拟,旨在维护离散最大值原理和渐近相容性。通过大量的数值实验,我们验证了我们的框架的有效性和多功能性,证明了它与现有方法相比的优越性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A nonlocal convection–diffusion model with Gaussian‐type kernels and meshfree discretization
Nonlocal models have demonstrated their indispensability in numerical simulations across a spectrum of critical domains, ranging from analyzing crack and fracture behavior in structural engineering to modeling anomalous diffusion phenomena in materials science and simulating convection processes in heterogeneous environments. In this study, we present a novel framework for constructing nonlocal convection–diffusion models using Gaussian‐type kernels. Our framework uniquely formulates the diffusion term by correlating the constant diffusion coefficient with the variance of the Gaussian kernel. Simultaneously, the convection term is defined by integrating the variable velocity field into the kernel as the expectation of a multivariate Gaussian distribution, facilitating a comprehensive representation of convective transport phenomena. We rigorously establish the well‐posedness of the proposed nonlocal model and derive a maximum principle to ensure its stability and reliability in numerical simulations. Furthermore, we develop a meshfree discretization scheme tailored for numerically simulating our model, designed to uphold both the discrete maximum principle and asymptotic compatibility. Through extensive numerical experiments, we validate the efficacy and versatility of our framework, demonstrating its superior performance compared to existing approaches.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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