This course gives you an introduction to modeling methods and simulation tools for a wide range of natural phenomena. The different methodologies that will be presented here can be applied to very wide range of topics such as fluid motion, stellar dynamics, population evolution, ... This course does not intend to go deeply into any numerical method or process and does not provide any recipe for the resolution of a particular problem. It is rather a basic guideline towards different methodologies that can be applied to solve any kind of problem and help you pick the one best suited for you.
The assignments of this course will be made as practical as possible in order to allow you to actually create from scratch short programs that will solve simple problems. Although programming will be used extensively in this course we do not require any advanced programming experience in order to complete it.
Simulation and modeling of natural processes
proposé par
University of Geneva
Programme du cours : ce que vous apprendrez dans ce cours
Semaine
1Introduction and general concepts
This module gives an overview of the course and presents the general ideas about modeling and simulation. An emphasis is given on ways to represent space and time from a conceptual point of view. An insight of modeling of complex systems is given with the simulation of the grothw and thrombosis of giant aneurysms. Finally, a first class of modeling approaches is presented: the Monte-Carlo methods.
7 vidéos (Total 85 min), 1 lecture, 1 quiz
7 vidéos
Modeling and Simulation13 min
Modeling Space and Time15 min
Example of bio-medical Modeling9 min
Monte Carlo methods I9 min
Monte Carlo methods II15 min
Monte Carlo methods III10 min
1 lectures
Course slides10 min
1 exercices pour s'entraîner
Introduction and general concepts8 min
Semaine
2Introduction to programming with Python 3
This module intends to provide the most basic concepts of high performance computing used for modeling purposes. It also aims at teaching the basics of Python 3 which will be the programming language used for the quizzes in this course.
12 vidéos (Total 94 min), 2 lectures, 3 quiz
12 vidéos
Concepts of code optimization6 min
Concepts of parallelism4 min
Palabos, a parallel lattice Boltzmann solver5 min
An introduction to Python 36 min
Running a Python program6 min
Variables and data types11 min
Operators8 min
Conditional Statements7 min
Loops7 min
Functions15 min
NumPy11 min
2 lectures
Course slides10 min
Dive into python 310 min
3 exercices pour s'entraîner
Introduction to programming with Python 310 min
Project - Piles2 min
Project - Class:Integration2 min
Semaine
3Dynamical systems and numerical integration
Dynamical systems modeling is the principal method developed to study time-space dependent problems. It aims at translating a natural phenomenon into a mathematical set of equations. Once this basic step is performed the principal obstacle is the actual resolution of the obtained mathematical problem. Usually these equations do not possess an analytical solution and advanced numerical methods must be applied to solve them. In this module you will learn the basics of how to write mathematical equations representing natural phenomena and then how to numerically solve them.
9 vidéos (Total 92 min), 3 lectures, 3 quiz
9 vidéos
The random walk14 min
Growth of a population8 min
Balance equations I8 min
Balance equations II13 min
Integration of ordinary differential equations7 min
Error of the approximation8 min
The implicit Euler scheme11 min
Numerical integration of partial differential equations13 min
3 lectures
Course slides10 min
References for numerical analysis10 min
A reference for the random walk10 min
3 exercices pour s'entraîner
Dynamical systems and numerical integration8 min
The implicit Euler scheme18 min
Project - Lotka-Volterra8 min
Semaine
4Cellular Automata
This module defines the concept of cellular automata by outlining the basic building blocks of this method. Then an insight of how to apply this technique to natural phenomena is given. Finally the lattice gas automata, a subclass of models used for fluid flows, is presented.
7 vidéos (Total 108 min), 2 lectures, 2 quiz
7 vidéos
Historical background9 min
A mathematical abstraction of reality20 min
Cellular Automata Models for Traffic13 min
Complex systems20 min
Lattice-gas models9 min
Microdynamics of LGA17 min
2 lectures
Course slides10 min
Notes on the Parity Rule10 min
2 exercices pour s'entraîner
Cellular Automata8 min
Project - The Parity Rule6 min
4.2
17 avisMeilleurs avis
par EM•Nov 18th 2017
This course was a perfect match with my expectations! I think it is a perfect introduction to Computer modeling of natural processes. I enjoyed lectures and tasks. Thank you very much!
par AR•Apr 18th 2018
Excellent course for people who love math, physics and simulations ! I choose it to get an insight on Lattice Boltzmann Method, I was happy to apply it and extend it to other cases.
Enseignants
Bastien Chopard
Full ProfessorComputer Science
Jean-Luc Falcone
Research AssociateComputer Science
Jonas Latt
Senior LecturerComputer Science
Orestis Malaspinas
Research AssociateComputer Science Department
À propos de University of Geneva
Founded in 1559, the University of Geneva (UNIGE) is one of Europe's leading universities. Devoted to research, education and dialogue, the UNIGE shares the international calling of its host city, Geneva, a centre of international and multicultural activities with a venerable cosmopolitan tradition.
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