A Stable Algorithm for Non-Negative Invariant Numerical Solution of Reaction-Diffusion Systems on Complicated Domains
Insoon Yang
EECS Department, University of California, Berkeley
Technical Report No. UCB/EECS-2012-77
May 10, 2012
http://www2.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-77.pdf
We present a Cartesian grid finite difference numerical method for solving a system of reaction-diffusion initial boundary value problems with Neumann type boundary conditions. The method utilizes adaptive time-stepping, which guarantees stability and non-negativity of the solutions. The latter property is critical for models in biology where solutions rep- resent physical measurements such as concentration. The level set representation of the boundary enables us to handle domains with complicated geometry with ease. We pro- vide numerical validation of our method on synthetic and biological examples. Empirical tests demonstrate second order convergence rate in the L1- and L2-norms, as well as in the L∞-norm for many cases.
Advisors: Claire Tomlin
BibTeX citation:
@mastersthesis{Yang:EECS-2012-77, Author= {Yang, Insoon}, Title= {A Stable Algorithm for Non-Negative Invariant Numerical Solution of Reaction-Diffusion Systems on Complicated Domains}, School= {EECS Department, University of California, Berkeley}, Year= {2012}, Month= {May}, Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-77.html}, Number= {UCB/EECS-2012-77}, Abstract= {We present a Cartesian grid finite difference numerical method for solving a system of reaction-diffusion initial boundary value problems with Neumann type boundary conditions. The method utilizes adaptive time-stepping, which guarantees stability and non-negativity of the solutions. The latter property is critical for models in biology where solutions rep- resent physical measurements such as concentration. The level set representation of the boundary enables us to handle domains with complicated geometry with ease. We pro- vide numerical validation of our method on synthetic and biological examples. Empirical tests demonstrate second order convergence rate in the L1- and L2-norms, as well as in the L∞-norm for many cases.}, }
EndNote citation:
%0 Thesis %A Yang, Insoon %T A Stable Algorithm for Non-Negative Invariant Numerical Solution of Reaction-Diffusion Systems on Complicated Domains %I EECS Department, University of California, Berkeley %D 2012 %8 May 10 %@ UCB/EECS-2012-77 %U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-77.html %F Yang:EECS-2012-77