KAUST DepartmentApplied Mathematics and Computational Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Online Publication Date2016-01-23
Print Publication Date2016-06
Permanent link to this recordhttp://hdl.handle.net/10754/596892
MetadataShow full item record
AbstractWe present new analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transport networks. The model describes the pressure field using a Darcy’s type equation and the dynamics of the conductance network under pressure force effects. Randomness in the material structure is represented by a linear diffusion term and conductance relaxation by an algebraic decay term. The analytical part extends the results of Haskovec et al. (2015) regarding the existence of weak and mild solutions to the whole range of meaningful relaxation exponents. Moreover, we prove finite time extinction or break-down of solutions in the spatially one-dimensional setting for certain ranges of the relaxation exponent. We also construct stationary solutions for the case of vanishing diffusion and critical value of the relaxation exponent, using a variational formulation and a penalty method. The analytical part is complemented by extensive numerical simulations. We propose a discretization based on mixed finite elements and study the qualitative properties of network structures for various parameter values. Furthermore, we indicate numerically that some analytical results proved for the spatially one-dimensional setting are likely to be valid also in several space dimensions.
CitationNotes on a PDE system for biological network formation 2016 Nonlinear Analysis: Theory, Methods & Applications
SponsorsBP is (partially) funded by the french “ANR blanche” project Kibord: “ANR-13-BS01-0004” and by Institut Universitaire de France. PM and JH are supported by KAUST baseline funds and grant no. 1000000193. MS acknowledges support by ERC via Grant EU FP 7 - ERC Consolidator Grant 615216 LifeInverse.