Numerical Methods For Differential Equations

Period: First semester

Course unit contents: Introduction, Krylov subspace methods for large and sparse linear systems.
Numerical methods for ODEs. Implicit and explicit methods, multistep methods, Runge-Kutta methods.

Numerical methods for Elliptic/parabolic problems: Finite element and finite difference methods, coupled problems and solution strategies.

Numerical project implementing a finite element/finite difference method in a computer for solving a transient 2D partial differential equation.

Planned learning activities and teaching methods: During the course, the students will have to carry on three numerical projects on different subjects for the implementation of the algorithms discussed and their interpretation in the light of the theory.

In addition to contacting the course instructor, students with disabilities, Specific Learning Disorders (SLD), Special Educational Needs (SEN), and other health conditions can reach out to the Student Services Office - Inclusion Unit to receive more information about opportunities to access teaching with specific support and tools.