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The course aims at teaching the basic discretization methods for the solution of partial differential equations (PDE). During the lectures, we will cover fundamental aspects concerning the three main categories: elliptic PDE, parabolic PDE and hyperbolic PDE. 

Program: 

  • Classification and examples of partial differential equations (elliptic, parabolic, hyperbolic) and some some analytical solutions;
  • Finite difference methods;
  • Elliptic equations (Laplace and Poisson Equations): Gauss-Seidel, Jacobi and SOR methods;
  • Parabolic equations (heat eq.): explicit methods, Crank-Nicholson and ADI methods;
  • Hyperbolic PDE: characteristic curves, advection equation, Burger's equation (shocks and rarefactions), linear systems and nonlinear equations (with application to Euler eqns.). Godunov's method.


Prerequisites:  

Knowledge of Linux-like environments (Mac / Ubuntu / Windows Subsystem for Linux) and acquaintance with at least one programming language (C / C++ / Fortran). 


Timetable: 

Lectures will be held mostly in Aula Fubini (5th floor) and Aula Verde (1st floor) on the following dates:

  1. Wednesday  April 3,     14:00-16:00 [Aula Fubini]
  2. Monday        April 8,     14:00-16:00 [Aula Fubini]
  3. Wednesday  April 10,   14:00-16:00 [Aula Fubini]
  4. Monday        April 15,   14:00-16:00 [Aula Verde]
  5. Wednesday  April 24,   09:00-11:00 [Aula Verde]
  6. Monday        April 29,   14:00-16:00 [Aula Fubini]
  7. Tuesday        April 30,   14:00-16:00 [Aula Fubini]
  8. Wednesday  May 15,    14:00-16:00 [webex*]

Bring your laptop with you.

*https://unito.webex.com/meet/andrea.mignone


Lecture material:

- Lecture 1 (PDE: theroy &  classification)

Lecture 2 (Analytical Solutions)

Lecture 3 (Introduction to Finite Difference Methods )

Lecture 4 (Numerical solution of Parabolic PDEs). Check also the notes for tridiagonal matrix inversion and the soource code tridiag.cpp.

Lecture 5 (Numerical solution of Elliptic PDEs). 

Lecture 6+7 (Finite difference / finite volume methods for Hyperbolic PDEs). 

© Andrea Mignone 2023