Numerical recipes for environmental sciences with MATLAB - Ph.D. Course in Models and Methods for Material and
Environmental Sciences - Università degli Studi di Modena e Reggio Emilia - A.A. 2021/22
Numerical simulations are computations we run on a computer with programs implementing a mathematical model for a chemical, physical or biological system. We need them to study the behavior of processes whose mathematical formulations are too complex to provide analytical solutions. The computational science area is itself a rapidly growing field. While the largest and most accurate simulations often use advanced computing capabilities, there is an ample layer of small and intermediate problems across many disciplines that we can face with easier-to-handle tools. This course will address one of such tools called MATLAB. We will use it to perform small-scale computer simulations. In the first place, we are going to introduce the programming language on its own and take some familiarity with it. Then, we will apply it to solve some problems in Earth, Life, and Chemical sciences.
Scheduling: Two lessons per week of two hours each from the 1st of March. Tuesday and Thursday from 9.00 to 11.00.
Modalities: The course will take place online in synchronous mode on Microsoft Teams.
Lecture notes: lecture notes and exercises are available
on-line.
A version
of the notes can be downloaded, it is just the direct
conversion of the web-pages, so it is not very visually pleasing.
Diary of the lessons
- 01/03/2022 - Introduction to the course and to the MATLAB environment.
- 03/03/2022 - Writing scripts, functions and control instructions.
- 08/03/2022 - Reading data from file, elaboration and plot.
- 11/03/2022 - Modeling evolutionary problems: solving ODEs.
- 15/03/2022 - Fitting data to models: least square based methods.
- 17/03/2022 - Fitting data to a differential model.
- 22/03/2022 - Graphs and Complex Networks.
- 24/03/2022 - Graphs and Complex Networks: clustering, eigenvalues and K-Means.
- 29/03/2022 - Graphs and Complex Networks: centrality measures.
- 31/03/2022 - Working with images.