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.