A modified and efficient phase field model for the biological transport network

被引:13
作者
Xia, Qing [1 ]
Jiang, Xiaoyu [1 ]
Li, Yibao [1 ]
机构
[1] Xi An Jiao Tong Univ, Sch Math & Stat, Xian 710049, Peoples R China
基金
中国国家自然科学基金;
关键词
Energy-dissipation-rate preserving; Biological transport networks; Gradient flow; Adaption; Unconditional energy stability; PDE SYSTEM; PRINCIPLE;
D O I
10.1016/j.jcp.2023.112192
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper aims to establish the biological transport network based on the phase field model. In order to ensure that the topological shape is formed under the guidance of electrical conductivity, we generate the biological networks with sufficient information based on the distributions of the venation of the leaf represented by the reaction-diffusion model. We modify the original energy of the network generating model by considering the auxin gradient property. By applying the gradient flow method to minimize the modified energy, we derive the Poisson type equation for pressure, the reaction-diffusion type equation for the network conductance, and the Allen-Cahn type equation for the phase field. The proposed model is significant on the investigation of phase transitions by considering the gradient properties on the boundaries. We have innovatively added conductivity and phase-field coupling terms that inhibit perpendicular transport of nutrients, making it easy to generate thin branches from the trunk through this model. In order to obtain the second-order temporal accuracy, we take the Crank-Nicolson method for the governing system. To obtain the second-order spatial accuracy, we discretize the coupling system with the central finite difference method and linearize the nonlinear terms semi-explicitly to form a linear system at each time step. The discrete energy dissipation is provably preserved and we can use a larger time step. We apply the preconditioned conjugate gradient method with the multigrid method as a preconditioner to implement a practical algorithm with only linear algebraic complexity. The proposed algorithm is easy to implement and achieves a fast convergence. Various numerical tests are demonstrated to verify the efficiency, stability, and robustness of the proposed method.(c) 2023 Elsevier Inc. All rights reserved.
引用
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页数:19
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