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Simulation and modeling of natural processes
  • Level Foundation
  • Duration 23 hours
  • Course by University of Geneva
  • Offered by

About

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.

Modules

Introduction and general concepts

    • 1 Readings
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1 Readings

  • Course slides

Objectives and background

    • 1 Videos
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1 Videos

  • Objectives and background

Modeling and Simulation

    • 1 Videos
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1 Videos

  • Modeling and Simulation

Modeling Space and Time

    • 1 Videos
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1 Videos

  • Modeling Space and Time

Example of bio-medical Modeling

    • 1 Videos
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1 Videos

  • Example of bio-medical Modeling

Monte-Carlo methods

    • 3 Videos
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3 Videos

  • Monte Carlo methods I
  • Monte Carlo methods II
  • Monte Carlo methods III

Assignments

    • 1 Assignment
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1 Assignment

  • Introduction and general concepts

Introduction to programming with Python 3

    • 1 Readings
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1 Readings

  • Course slides

Introduction to high performance computing for modeling

    • 1 Videos
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1 Videos

  • Introduction to high performance computing for modeling

Concepts of code optimization

    • 1 Videos
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1 Videos

  • Concepts of code optimization

Parallelism

    • 2 Videos
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2 Videos

  • Concepts of parallelism
  • Palabos, a parallel lattice Boltzmann solver

An introduction to Python 3

    • 1 Videos
    • 1 Readings
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1 Videos

  • An introduction to Python 3

1 Readings

  • Dive into python 3

Running a Python program

    • 1 Videos
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1 Videos

  • Running a Python program

Variables and data types

    • 1 Videos
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1 Videos

  • Variables and data types

Operators

    • 1 Videos
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1 Videos

  • Operators

Control structures

    • 2 Videos
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2 Videos

  • Conditional Statements
  • Loops

Functions

    • 1 Videos
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1 Videos

  • Functions

NumPy

    • 1 Videos
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1 Videos

  • NumPy

Assignments

    • 3 Assignment
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3 Assignment

  • Introduction to programming with Python 3
  • Project - Piles
  • Project - Class:Integration

Dynamical systems and numerical integration

    • 2 Readings
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2 Readings

  • Course slides
  • References for numerical analysis

General introduction to dynamical systems

    • 1 Videos
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1 Videos

  • General introduction to dynamical systems

Two examples of dynamical systems

    • 2 Videos
    • 1 Readings
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2 Videos

  • The random walk
  • Growth of a population

1 Readings

  • A reference for the random walk

Balance equations

    • 2 Videos
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2 Videos

  • Balance equations I
  • Balance equations II

Ordinary differential equations

    • 3 Videos
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3 Videos

  • Integration of ordinary differential equations
  • Error of the approximation
  • The implicit Euler scheme

Numerical integration of partial differential equations

    • 1 Videos
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1 Videos

  • Numerical integration of partial differential equations

Assignments

    • 3 Assignment
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3 Assignment

  • Dynamical systems and numerical integration
  • The implicit Euler scheme
  • Project - Lotka-Volterra

Cellular Automata

    • 1 Readings
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1 Readings

  • Course slides

Definition and basic concepts

    • 1 Videos
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1 Videos

  • Definition and basic concepts

Historical background

    • 1 Videos
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1 Videos

  • Historical background

A mathematical abstraction of reality

    • 1 Videos
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1 Videos

  • A mathematical abstraction of reality

Cellular Automata Models for Traffic

    • 1 Videos
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1 Videos

  • Cellular Automata Models for Traffic

Complex systems

    • 1 Videos
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1 Videos

  • Complex systems

Lattice-gas Automata

    • 2 Videos
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2 Videos

  • Lattice-gas models
  • Microdynamics of LGA

Assignments

    • 1 Readings
    • 2 Assignment
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2 Assignment

  • Cellular Automata
  • Project - The Parity Rule

1 Readings

  • Notes on the Parity Rule

Lattice Boltzmann modeling of fluid flow

    • 1 Readings
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1 Readings

  • Course slides

Introduction

    • 3 Videos
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3 Videos

  • Computational Fluid Dynamics: Overview
  • Equations and challenges
  • From Lattice Gas to Lattice Boltzmann

The Lattice Boltzmann Algorithm

    • 3 Videos
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3 Videos

  • Macroscopic Variables
  • Collision step: the BGK model
  • Streaming Step

Application

    • 2 Videos
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2 Videos

  • Boundary Conditions
  • Flow around an obstacle

Assignments

    • 4 Assignment
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4 Assignment

  • Optional - Equations and challenges
  • Lattice Boltzmann modeling of fluid flow
  • Project - Flow around a cylinder
  • Collision Invariant

Particles and point-like objects

    • 1 Readings
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1 Readings

  • Course slides

Numerical modeling of point-like objects

    • 3 Videos
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3 Videos

  • Particles and point-like objects: Overview
  • Newton’s laws of motion, potentials and forces
  • Time-integration of equations of motion

Short-range interactions

    • 1 Videos
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1 Videos

  • The Lennard-Jones potential: Introducing a cut-off distance

Long-range interactions

    • 2 Videos
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2 Videos

  • The n-body problem: Evaluation of gravitational forces
  • Barnes-Hut algorithm: using the quadtree

Assignments

    • 2 Assignment
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2 Assignment

  • Particles and point-like objects
  • Project - Barnes-Hut Galaxy Simulator

Introduction to Discrete Events Simulation

    • 1 Readings
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1 Readings

  • Course slides

Introduction to Discrete Events

    • 1 Videos
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1 Videos

  • Introduction to Discrete Events

Definition of Discrete Events Simulations

    • 1 Videos
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1 Videos

  • Definition of Discrete Events Simulations

Optimisation problems

    • 1 Videos
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1 Videos

  • Optimisation problems

Implementation matters

    • 1 Videos
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1 Videos

  • Implementation matters

Two examples

    • 2 Videos
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2 Videos

  • Traffic intersection
  • Volcano ballistics

Assignments

    • 2 Assignment
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2 Assignment

  • Introduction to Discrete Event Simulation
  • Project - Simple modelling of traffic lights

Agent based models

    • 1 Readings
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1 Readings

  • Course slides

Motivation

    • 1 Videos
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1 Videos

  • Motivation

Agents

    • 1 Videos
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1 Videos

  • Agents

Multi-Agent systems

    • 1 Videos
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1 Videos

  • Multi-Agent systems

Implementation of Agent Based Models

    • 1 Videos
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1 Videos

  • Implementation of Agent Based Models

Two examples

    • 2 Videos
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2 Videos

  • Ants Corpse clustering
  • Bacteria chemotaxy

Assignments

    • 2 Assignment
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2 Assignment

  • Agent based models
  • Project - Multi-agents model

Auto Summary

Explore the fundamentals of modeling methods and simulation tools for natural phenomena in this foundational course. Covering topics from fluid motion to population evolution, it provides a broad overview without delving deeply into numerical methods. Designed for practical learning, you'll create short programs to solve simple problems, making it accessible without advanced programming experience. Offered by Coursera, the course spans 1380 minutes with Starter and Professional subscription options, ideal for science and engineering enthusiasts.

Bastien Chopard
Instructors

Bastien Chopard

Jean-Luc Falcone
Instructors

Jean-Luc Falcone

Jonas Latt
Instructors

Jonas Latt

Orestis Malaspinas
Instructors

Orestis Malaspinas