A finite element discretization is developed for the Cai-Hu model, describing the formation of biological networks. The model consists of a non linear elliptic equation for the pressure p and a non linear reaction-diffusion equation for the conductivity tensor C. The problem requires high resolution due to the presence of multiple scales, the stiffness in all its components and the non linearities. We propose a low order finite element discretization in space coupled with a semi-implicit time advancing scheme. The code is verified with several numerical tests performed with various choices for the parameters involved in the system. In absence of the exact solution, we apply Richardson extrapolation technique to estimate the order of the method.

Finite Element Discretization of a Biological Network Formation System: A Preliminary Study

Boffi, Daniele;Credali, Fabio
2024-01-01

Abstract

A finite element discretization is developed for the Cai-Hu model, describing the formation of biological networks. The model consists of a non linear elliptic equation for the pressure p and a non linear reaction-diffusion equation for the conductivity tensor C. The problem requires high resolution due to the presence of multiple scales, the stiffness in all its components and the non linearities. We propose a low order finite element discretization in space coupled with a semi-implicit time advancing scheme. The code is verified with several numerical tests performed with various choices for the parameters involved in the system. In absence of the exact solution, we apply Richardson extrapolation technique to estimate the order of the method.
2024
SEMA SIMAI Springer Series
The Mathematics category includes resources dealing with mathematics, applied mathematics, statistics and probability.
Esperti anonimi
Inglese
Internazionale
35
247
257
11
9783031552632
9783031552649
Springer Science and Business Media Deutschland GmbH
GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
Leaf venation; Symmetric tensor; Variational formulation for tensor model
2 Contributo in Volume::2.1 Contributo in volume (Capitolo o Saggio)
3
268
none
Astuto, Clarissa; Boffi, Daniele; Credali, Fabio
info:eu-repo/semantics/bookPart
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1513615
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