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Volume 16, Issue 1
Local Discontinuous Galerkin Methods with Decoupled Implicit-Explicit Time Marching for the Growth-Mediated Autochemotactic Pattern Formation Model

Hui Wang, Hui Guo, Jiansong Zhang & Lulu Tian

Adv. Appl. Math. Mech., 16 (2024), pp. 208-236.

Published online: 2023-12

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  • Abstract

In this paper, two fully-discrete local discontinuous Galerkin (LDG) methods are applied to the growth-mediated autochemotactic pattern formation model in self-propelling bacteria. The numerical methods are linear and decoupled, which greatly improve the computational efficiency. In order to resolve the time level mismatch of the discretization process, a special time marching method with high-order accuracy is constructed. Under the condition of slight time step constraints, the optimal error estimates of this method are given. Moreover, the theoretical results are verified by numerical experiments. Real simulations show the patterns of spots, rings, stripes as well as inverted spots because of the interplay of chemotactic drift and growth rate of the cells.

  • AMS Subject Headings

65M15, 65M60

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{AAMM-16-208, author = {Wang , HuiGuo , HuiZhang , Jiansong and Tian , Lulu}, title = {Local Discontinuous Galerkin Methods with Decoupled Implicit-Explicit Time Marching for the Growth-Mediated Autochemotactic Pattern Formation Model}, journal = {Advances in Applied Mathematics and Mechanics}, year = {2023}, volume = {16}, number = {1}, pages = {208--236}, abstract = {

In this paper, two fully-discrete local discontinuous Galerkin (LDG) methods are applied to the growth-mediated autochemotactic pattern formation model in self-propelling bacteria. The numerical methods are linear and decoupled, which greatly improve the computational efficiency. In order to resolve the time level mismatch of the discretization process, a special time marching method with high-order accuracy is constructed. Under the condition of slight time step constraints, the optimal error estimates of this method are given. Moreover, the theoretical results are verified by numerical experiments. Real simulations show the patterns of spots, rings, stripes as well as inverted spots because of the interplay of chemotactic drift and growth rate of the cells.

}, issn = {2075-1354}, doi = {https://doi.org/10.4208/aamm.OA-2022-0217}, url = {http://global-sci.org/intro/article_detail/aamm/22296.html} }
TY - JOUR T1 - Local Discontinuous Galerkin Methods with Decoupled Implicit-Explicit Time Marching for the Growth-Mediated Autochemotactic Pattern Formation Model AU - Wang , Hui AU - Guo , Hui AU - Zhang , Jiansong AU - Tian , Lulu JO - Advances in Applied Mathematics and Mechanics VL - 1 SP - 208 EP - 236 PY - 2023 DA - 2023/12 SN - 16 DO - http://doi.org/10.4208/aamm.OA-2022-0217 UR - https://global-sci.org/intro/article_detail/aamm/22296.html KW - Local discontinuous Galerkin methods, implicit-explicit time-marching scheme, error estimate, growth-mediated autochemotactic pattern formation model. AB -

In this paper, two fully-discrete local discontinuous Galerkin (LDG) methods are applied to the growth-mediated autochemotactic pattern formation model in self-propelling bacteria. The numerical methods are linear and decoupled, which greatly improve the computational efficiency. In order to resolve the time level mismatch of the discretization process, a special time marching method with high-order accuracy is constructed. Under the condition of slight time step constraints, the optimal error estimates of this method are given. Moreover, the theoretical results are verified by numerical experiments. Real simulations show the patterns of spots, rings, stripes as well as inverted spots because of the interplay of chemotactic drift and growth rate of the cells.

Wang , HuiGuo , HuiZhang , Jiansong and Tian , Lulu. (2023). Local Discontinuous Galerkin Methods with Decoupled Implicit-Explicit Time Marching for the Growth-Mediated Autochemotactic Pattern Formation Model. Advances in Applied Mathematics and Mechanics. 16 (1). 208-236. doi:10.4208/aamm.OA-2022-0217
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