Numerical Methods for the Engineer
Master, University of Strasbourg, Faculty of Physics, 2019
Description of the teaching content
Content (18h CM, 8h TD):
- Numerical resolution of linear systems of equations: direct methods (LU, Cholesky), iterative methods (Jacobi, Gauss-Seidel, relaxation, Krylov spaces, conjugate gradient). Sparse matrices.
- Numerical resolution of non-linear systems of equations : Picard’s iterations, Newton and quasi Newton methods.
- Numerical resolution of differential equations. One-step methods (Runge-Kutta). Multi-step methods. Stability notions.
- Stiff problems, implicit methods.
- Programming langage : Octave/Matlab
Skills to be acquired
Objectives:
- Being able to write a simple program.
- Being able to solve a system of linear equation.
Skills to acquire:
- choose the numerical resolution technique best suited to solve a given engineering problem.
- know how to use numerical techniques.
- understand how numerical tools work.