About this course: 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.
Created by: University of Geneva
Taught by: Bastien Chopard, Full Professor
Computer Science
Taught by: Jean-Luc Falcone, Research Associate
Computer Science
Taught by: Jonas Latt, Senior Lecturer
Computer Science
Taught by: Orestis Malaspinas, Research Associate
Computer Science Department
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
Syllabus
WEEK 1
Introduction 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 simu...
7 videos, 1 reading
Graded: Introduction and general concepts
WEEK 2
Introduction 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 videos, 2 readings
Graded: Introduction to programming with Python 3
Graded: Project - Piles
Graded: Project - Class:Integration
WEEK 3
Dynamical 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 resolu...
9 videos, 1 reading
Graded: Dynamical systems and numerical integration
Graded: The implicit Euler scheme
Graded: Project - Lotka-Volterra
WEEK 4
Cellular 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 flow...
7 videos, 2 readings
Graded: Cellular Automata
Graded: Project - The Parity Rule
WEEK 5
Lattice Boltzmann modeling of fluid flow
This module provides an introduction to the lattice Boltzmann method, a powerful tool in computational fluid dynamics. The lesson is practice oriented and show, step by step, how to write a program for the lattice Boltzmann method. The program is used to showc...
8 videos, 1 reading, 1 practice quiz
Graded: Lattice Boltzmann modeling of fluid flow
Graded: Project - Flow around a cylinder
Graded: Collision Invariant
WEEK 6
Particles and point-like objects
A short review of classical mechanics, and of numerical methods used to integrate the equations of motions for many interacting particles is presented. The student will learn that the computational expense of resolving all interaction between particles poses a...
6 videos, 1 reading
Graded: Particles and point-like objects
Graded: Project - Barnes-Hut Galaxy Simulator
WEEK 7
Introduction to Discrete Events Simulation
In this module, we will see an alternative approach to model systems which display a trivial behaviour most of the time, but which may change significantly under a sequence of discrete events. Initially developed to simulate queue theory systems (such as consu...
6 videos, 1 reading
Graded: Introduction to Discrete Event Simulation
Graded: Project - Simple modelling of traffic lights
WEEK 8
Agent based models
Agent Based Models (ABM) are used to model a complex system by decomposing it in small entities (agents) and by focusing on the relations between agents and with the environment. This approach is derived from artificial intelligence research and is currently u...
6 videos, 1 reading
Graded: Agent based models
Graded: Project - Multi-agents model
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