Scientific Computing

A.Y. 2020/2021
6
Max ECTS
60
Overall hours
SSD
MAT/08
Language
Italian
Learning objectives
The course aims to offer an enlarged vision on the various aspects - both from the theoretical and implementation viewpoints - that characterize the modern use of Scientific Computing, along with its application to problems arising in physics, biology and engineering.
Expected learning outcomes
Upon completing the course, the students will be able to apply adequate discretization techniques to handle partial differential equation problems of elliptic, parabolic and hyperbolic type. They will also be able to quantify the accuracy of the chosen method and to produce an adequate implementation in Matlab.
Course syllabus and organization

Single session

Responsible
Lesson period
Second semester
Distance learning (async and sync modes)
Course syllabus
Propedeuticità consigliate
Corso di base di Calcolo Numerico, Programmazione Matlab, Analisi Matematica

Materiale di riferimento
Appunti del corso, materiale fornito dalla docente
Introduction to partial differential equation problems and their importance in the applications. Non-dimensionalization and scaling procedures. Discretization of ordinary derivative equations: multistep and Runge Kutta methods. Analysis and Matlab implementation. Partial derivative equations: theoretical properties and finite difference discretization in 1D and nD for elliptic and parabolic equations. Convection-diffusion-reaction problems with transport / dominant reaction. Introduction to inverse problems. Introduction to
Prerequisites for admission
Fundamentals of Numerical Analysis, Matlab Programming, Calculus
Teaching methods
lectures and lab sessions
Teaching Resources
notes of the course, study material provided during the course
Assessment methods and Criteria
The exam is composed of 4 projects to be delivered during the term. The projects aim to verify the competences and include theoretical and coding questions
MAT/08 - NUMERICAL ANALYSIS - University credits: 6
Laboratories: 24 hours
Lessons: 36 hours
Professor: Causin Paola
Professor(s)