Offered every fall term.
Brief description:
Mathematical models based on Partial Differential Equations (PDEs) are ubiquitous these days, arising in all areas of science and engineering, and also in finance and economics. In complex models, the PDEs cannot be solved exactly, and one has to rely on approximate solutions obtained using numerical methods on computers.
The goal of this course is threefold. You will receive a solid introduction to the theory of numerical methods for partial differential equations (with derivations of the methods and some proofs). You will learn to implement the computational methods efficiently in Matlab, and you will apply the methods to problems in several fields, for example, fluid mechanics, diffusion processes, wave phenomena, and biomedicine.
Prerequisites:
AMATH 342
Intended audience:
This course will be of interest to anyone who wants to be able to use computers to simulate mathematical models based on partial differential equations.