Uncoupling Techniques for Multispecies Diffusion-Reaction Model

M. Vasilyeva, S. Stepanov, Alexey L. Sadovski, Stephen Henry
{"title":"Uncoupling Techniques for Multispecies Diffusion-Reaction Model","authors":"M. Vasilyeva, S. Stepanov, Alexey L. Sadovski, Stephen Henry","doi":"10.3390/computation11080153","DOIUrl":null,"url":null,"abstract":"We consider the multispecies model described by a coupled system of diffusion–reaction equations, where the coupling and nonlinearity are given in the reaction part. We construct a semi-discrete form using a finite volume approximation by space. The fully implicit scheme is used for approximation by time, which leads to solving the coupled nonlinear system of equations at each time step. This paper presents two uncoupling techniques based on the explicit–implicit scheme and the operator-splitting method. In the explicit–implicit scheme, we take the concentration of one species in coupling term from the previous time layer to obtain a linear uncoupled system of equations. The second approach is based on the operator-splitting technique, where we first solve uncoupled equations with the diffusion operator and then solve the equations with the local reaction operator. The stability estimates are derived for both proposed uncoupling schemes. We present a numerical investigation for the uncoupling techniques with varying time step sizes and different scales of the diffusion coefficient.","PeriodicalId":10526,"journal":{"name":"Comput.","volume":"2 1","pages":"153"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/computation11080153","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

We consider the multispecies model described by a coupled system of diffusion–reaction equations, where the coupling and nonlinearity are given in the reaction part. We construct a semi-discrete form using a finite volume approximation by space. The fully implicit scheme is used for approximation by time, which leads to solving the coupled nonlinear system of equations at each time step. This paper presents two uncoupling techniques based on the explicit–implicit scheme and the operator-splitting method. In the explicit–implicit scheme, we take the concentration of one species in coupling term from the previous time layer to obtain a linear uncoupled system of equations. The second approach is based on the operator-splitting technique, where we first solve uncoupled equations with the diffusion operator and then solve the equations with the local reaction operator. The stability estimates are derived for both proposed uncoupling schemes. We present a numerical investigation for the uncoupling techniques with varying time step sizes and different scales of the diffusion coefficient.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
多组分扩散-反应模型的解耦技术
我们考虑由扩散-反应方程耦合系统描述的多物种模型,其中反应部分给出了耦合和非线性。我们利用空间的有限体积近似构造一个半离散形式。采用全隐式格式进行时间逼近,从而在每个时间步上求解耦合非线性方程组。本文提出了基于显隐格式和算子分裂方法的两种解耦技术。在显隐格式中,我们从前一时间层中取耦合项中一种的浓度,得到一个线性解耦方程组。第二种方法是基于算子分裂技术,首先用扩散算子求解解耦方程,然后用局部反应算子求解解耦方程。给出了两种解耦方案的稳定性估计。本文对不同时间步长和不同扩散系数尺度下的解耦技术进行了数值研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A U-Net Architecture for Inpainting Lightstage Normal Maps Implementing Virtualization on Single-Board Computers: A Case Study on Edge Computing Electrocardiogram Signals Classification Using Deep-Learning-Based Incorporated Convolutional Neural Network and Long Short-Term Memory Framework The Mechanism of Resonant Amplification of One-Dimensional Detonation Propagating in a Non-Uniform Mixture Application of Immersive VR Serious Games in the Treatment of Schizophrenia Negative Symptoms
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1