Informations générales
Number of hours
- Lectures 7.0
- Projects 0
- Tutorials 7.0
- Internship 0
- Laboratory works 16.0
ECTSECTS
2.5
Goal(s)
The overall objective of the two Digital Methods courses is to provide students with the means to solve various problems related to modeling in engineering science (differential equations, partial differential equations, optimization, etc.). We use a tool (Matlab or Python) that is both a computing environment, a computer language, and a digital toolbox. The ultimate goal is to become an informed user, i.e., to know how to answer the question: which method for which problem?
The “Numerical Methods 1” course covers methods for solving differential equations and finite difference methods.
Content(s)
- Introduction to Matlab
- Ordinary Differential Equations (Runge Kutta methods, temporal stability, prediction/correction, error control, etc.)
- Finite Differences (steady state, transient state: explicit & implicit schemes, etc.).
Prerequisites
Algorithmic culture
Mathematical tools: derivation, limited developments, differential operators, algebra, matrix calculus.
Test
Bibliography
Computational Materials Science, Raabe D., Wiley-VCH, Weinheim, 1998.
- Numerical recipes : http://www.nr.com/