The prerequisite(s) for this Teaching Unit (Unité d’enseignement – UE) for the programmes/courses that offer this Teaching Unit are specified at the end of this sheet.
The course serves three main goals:
- the understanding of basic numerical techniques with the underlying mathematical notions,
- the hability to interpret the reliability of numerical results,
- the programming skills to implement simple numerical algorithms.
At the end of this learning unit, the student is able to : | |
1 | Contribution of the course to the program objectives Regarding the learning outcomes of the program of Bachelor in Engineering, this course contributes to the development and the acquisition of the following learning outcomes:
Specific learning outcomes of the course At the end of the lecture, the student must be able to:
The goal is to cover a wide range of numerical methods to obtain an approximate solution of problems of physics where an exact solution is not available. A broad knowledge is often decisive to choose the right method when developing a new code. A strong emphasis is put on the problem based learning where the participants analyze data, derive, implement, document and execute their own models. Finally, the analytical and the numerical approaches are presented as complementary tools. |
The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Topics include:
- Error analysis: modelling error, truncation error, convergence and approximation order, floating point number representation (IEEE754).
- Approximation and interpolation: Lagrange polynomials, spline functions, NURBS, orthogonal polynomials, error estimators.
- Numerical integration and differentiation: backward and centered finite difference, midpoint, trapezoidal and Simpson formula, adaptive techniques.
- Ordinary Differential Equations (ODE): Taylor and Runge Kutta methods, predictor-corrector methods, stability on unbounded intervals and perturbation analysis.
- Linear equations: factorization methods and iterative techniques, complexity, computation of eigenvalues.
- Nonlinear equations: bisection and Newton methods, optimisation applications.
- Partial Differential Equations (PDE): boundary value problems (Laplace, heat equation, waves equation), approximation by finite differences.
Real-life examples using numerical methods
Use of MATLAB software
A written test is organized during the semester. This test contributes for 1/3 to the final grade provided that its grade is higher than the one of the final examination.
- V Legat, MATHEMATIQUES ET METHODES NUMERIQUES...ou les aspects facetieux du calcul sur un ordinateur (copyright V. Legat, 2015)
- V. Legat, énoncés et solutions des exercices (copyright V. Legat, 2015)
Bibliographie
- Charles F. Van Loan, Introduction to Scientic Computing, Second Edition, Prentice Hall, Upper Saddle River, ISBN 0-13949157-0 (1999).
- Jacques Rappaz, Marco Picasso, Introduction a l'analyse numerique, Presses polytechniques et universitaires romandes, Lausanne, ISBN 2-88074363-X (2000).
- 'Andre Fortin, Analyse numerique pour ingenieurs, Seconde Edition, Presses internationales polytechniques, Montreal, ISBN 2-55300936-4 (2001).
- 'William L. Briggs, Van Emden Henson, Steve F. McCormick, A Multigrid Tutorial,Second Edition, SIAM, Philadelphia, ISBN 0-89871462-1 (2000).
- 'Brigitte Lucquin, Olivier Pironneau, Introduction to Scientic Computing, John Wiley &Sons, New York, ISBN 0-47197266-X (1998).
- Alfio Quarteroni, Fausto Saleri, Scientic Computing with MATLAB, Springer-Verlag, Berlin, ISBN 3-35044363-0 (2003).
- Desmond J. Higham, Nicholas J. Higham Matlab Guide, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, ISBN 0-89871469-9 (2000).
- Michael T. Heath Scientic Computing : an Introduction Survey, McGraw Hill, New-York,ISBN 0-07-115336-5 (1997).
- K. E. Atkinson, An Introduction to Numerical Analysis, Second Edition, John Wiley & Sons,New York (1989).
- S. D. Conte, C. de Boor, Elementary Numerical Analysis, An Algorithmic Approach, Third Edition, McGraw-Hill Book Company, New York (1980).
- B.M. Irons, N.G. Shrive, Numerical Methods in Engineering and Applied Sciences : numbers are fun, Second Edition, John Wiley and Sons (1987).
- John H. Mathews, Numerical Methods for Mathematics, Science and Engineering, Second Edition,
- Prentice Hall, Englewood Clis, ISBN 0-13624990-6 (1992). W. H. Press, S. A. Teukolsky, W. T. Vetterling, B. P. Flannery Numerical Recipes in C: The Art of Scientic Computing, Second Edition, Cambridge University Press, Cambridge (1994).