Mathematical modelling of physical systems

linma2720  2019-2020  Louvain-la-Neuve

Mathematical modelling of physical systems
Note from June 29, 2020
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
5 credits
30.0 h + 22.5 h
Q2
Teacher(s)
Keunings Roland;
Language
English
Prerequisites
LFSAB1103, LFSAB1104, LMECA1901.
Prerequisites: basic Physics and Applied Mathematics courses as offered in Bac 1-3.
Main themes
The focus is mainly set on the mathematical modeling of physical systems described by partial differential equations.  Multi-scale modeling is also covered.
Aims

At the end of this learning unit, the student is able to :

1 Contribution of the course to the program objectives :
  • AA1.1, AA1.2, AA1.3
  • AA2.1
  • AA5.2, AA5.3
The main objective of this course is to allow the student to gain understanding of mathematical modeling approaches for continuous physical systems. 
With this course, the student will be able to:
  • Formulate a mathematical model of a complex physical problem using appropriate principles of Physics and suitable constitutive models;
  • Identify the main governing mechanisms by means of dimensional analysis, and, if relevant, apply adequate perturbation methods;
  • Understand in depth (for the generic example of diffusion processes covered in the lectures) the different available approaches to the modeling of a complex problem;
  • In the course of his/her project, analyse in a detailed and critical manner a sophisticated mathematical model;
  • Perform a critical scientific literature search;
  • Write a scientific report of quality and substance;
  • Deliver an efficient and clear oral presentation of a complex technical topic.
 

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”.
Content
Topics covered include:  (i) dimensional analysis (Buckingham "Pi" Theorem, similarity solutions, scaling), (ii) perturbation methods (regular and singular perturbations, boundary layers, matched asymptotic expansions, multi-scale analysis), (iii) generic topic of diffusion processes (random walk and Brownian motion, diffusion equation, Fick's constitutive equation, Einstein and Langevin approaches), (iv) stochastic calculus and Fokker-Planck equation for Markov processes (Wiener process, Itô calculus, equivalence between stochastic differential equation and Fokker-Planck equation, numerical methods), (v) illustration of recent developments:  micro-macro modeling of polymer dynamics (kinetic theory of polymer solutions, associated Fokker-Planck equation, closure approximations and derivation of constitutive equations, numerical solution of Fokker-Planck equation in configuration spaces of high dimension).
Teaching methods
Lectures and a project carried out in the course of the second semester (individually of by groups of two students). Students choose their project's topic, they identify and analyse the relevant scientific references (journal papers or books), present a summary of their project to fellow students, and write a report that will be discussed with the professor at the oral exam.
Evaluation methods
Evaluation:  oral exam (open book; 50% of final mark), project (written report + 20 minute presentation to fellow students; 50% of final mark)
Other information
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Online resources
Various optional documents (slides, bibliographical and web references) are gathered at  http://moodleucl.uclouvain.be/course/view.php?id=874
Bibliography
  • M. H. Holmes (2009) Introduction to the Foundations of Applied Mathematics
  • E.J. Hinch (1991) Perturbation Methods
  • H.C. Öttinger (1996) Stochastic Processes in Polymeric Fluids
Faculty or entity
MAP


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Mathematical Engineering