NUMERICAL METHODS IN ENGINEERING SCIENCES
Stampa
Anno immatricolazione
2021/2022
Anno offerta
2021/2022
Normativa
DM270
SSD
MAT/08 (ANALISI NUMERICA)
Dipartimento
DIPARTIMENTO DI INGEGNERIA INDUSTRIALE E DELL'INFORMAZIONE
Corso di studio
INDUSTRIAL AUTOMATION ENGINEERING - INGEGNERIA DELL'AUTOMAZIONE INDUSTRIALE
Curriculum
PERCORSO COMUNE
Anno di corso
Periodo didattico
Primo Semestre (27/09/2021 - 21/01/2022)
Crediti
6
Ore
46 ore di attività frontale
Lingua insegnamento
English
Tipo esame
SCRITTO E ORALE CONGIUNTI
Docente
SANGALLI GIANCARLO (titolare) - 6 CFU
Prerequisiti
Differential and integral calculus for real functions; complex numbers; linear algebra; computer programming experience.
Obiettivi formativi
The aim of the course is to enable students to classify real-life problems and choose the best suited algorithms for solving them, in terms of costs/benefits and convergence properties. At the same time, the course is meant to make students well acquainted with the use of Matlab software and with the practical implementation of some algorithms.
Programma e contenuti
* Numerical solution of ordinary differential equations.

*Solution of linear systems of equations: direct and iterative methods.

*Nonlinear equations: bisection and Newton's methods. Convergence, order of convergence, stopping criteria.

*Lagrange interpolation: interpolation error, piecewise Lagrange interpolation, order of approximation.

*Least squares method for data fitting: linear regression and various examples.

*Interpolatory quadrature formulas in 1D: midpoint, trapezoidal, Simpson and error analysis. Gaussian formulae.
Metodi didattici
Lessons and computer lab practice
Testi di riferimento
Teacher' slides. For more material see: A. Quarteroni, R. Sacco, F. Saleri . Numerical Mathematics-2nd edition. Springer Series: Texts in Applied Mathematics, Vol. 37 (2007).
Modalità verifica apprendimento
The exam will be written. Each student will be offered a couple of questions on subjects developed in the classes and has one hour to answer.
Altre informazioni
Additional information can be found on the web page:
http://www-dimat.unipv.it/sangalli
Obiettivi Agenda 2030 per lo sviluppo sostenibile