Course teacher(s)
Pierre-Etienne LABEAU (Coordinator) and Matteo ZanettiECTS credits
3
Language(s) of instruction
english
Course content
Basic concepts and relevance of Monte Carlo simulation
Sampling methods
Estimation of definite integrals
Convergence and accuracy
Variance-reduction methods
Application to various engineering problems, like particle transport problems (neutron reactor physics, radiation therapy...), power system performance, system reliability
Coding exercises and project.
Objectives (and/or specific learning outcomes)
Provide the students with an in-depth understanding of the concepts at hand in Monte Carlo simulation algorithms applied to some engineering problems.
Enable them to learn how to code Monte Carlo algorithms.
Prerequisites and Corequisites
Required and Corequired knowledge and skills
Bachelor level in engineering or sciences
Teaching methods and learning activities
Oral lectures emphasizing the intuition of the students in improving the efficiency of Monte Carlo schemes
Exercises including programming
Seminars on industrial applications
References, bibliography, and recommended reading
See UV
Course notes
- Université virtuelle
Contribution to the teaching profile
Development of the skills of the students in the mathematical modeling of systems
Other information
Contacts
Pierre-Etienne LABEAU, pierre.etienne.labeau@ulb.be
Campus
Solbosch
Evaluation
Method(s) of evaluation
- Project
- Oral presentation
Project
Oral presentation
Assessment based on two parts:
* programming project
* presentation of a scientific paper related to the theory of Monte Carlo methods seen during the lectures
Mark calculation method (including weighting of intermediary marks)
50% programming project, 50% presentation
Language(s) of evaluation
- english