NUMERICAL METHODS FOR DIFFERENTIAL AND INTEGRAL EQUATIONS
cod. 1010331

Anno accademico 2021/22
1° anno di corso - Secondo semestre
Docente
Heiko GIMPERLEIN
Settore scientifico disciplinare
Analisi numerica (MAT/08)
Ambito
Attività formative affini o integrative
Tipologia attività formativa
Affine/Integrativa
48 ore
di attività frontali
6 crediti
sede:
insegnamento
in INGLESE

Obiettivi formativi

-- Knowledge and understanding of elementary concepts for the numerical modeling of elliptic and parabolic partial di_erential equations, in particular, based on finite difference, finite element, spectral and boundary element methods. - Ability to program the discussed numerical methods in Matlab for classical elliptic and parabolic linear equations, as well as the evaluation of algorithmic aspects, accuracy, stability and efficiency. - Autonomy of judgment in evaluating the approximation algorithms and the obtained results also through discussion with one's peers in possible team work. - Ability to clearly communicate the acquired concepts and to discuss the obtained results. - Ability to learn the drawbacks and the advantages of models and methods of resolution and to apply them in di_erent working and scientific contexts.

Prerequisiti

- Basic methods and algorithms of numerical analysis.
- Knowledge of a programming language

Contenuti dell'insegnamento

Relevant background in analysis: Sobolev spaces, variational formulations of elliptic PDEs, relevant functional analysis - Finite dfference methods for elliptic problems: introduction, implementation, basic analysis. - Galerkin methods for elliptic problems: stability, error analysis, implementation of standard finite element methods. - Spectral methods for elliptic problems: spectral Galerkin and collocation methods. - Methods for parabolic problems: time discretization, implicit and explicit Euler method.

- Advanced topics, including boundary element methods and adaptive methods.

Programma esteso

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Bibliografia

- "Finite Elements", D. Braess, Cambridge University Press, 2010. - "Numerical Approximation of Partial Di_erential Equations", A. Quarteroni, A. Valli, ed. Springer, 1994. - "Spectral Methods: Algorithms, Analysis and Applications", J. Shen, T. Tang, L.-L. Wang, Springer, 2011. -" Afinite element primer", D. J. Silvester, https://personalpages.manchester.ac.uk/sta_/david.silvester/primer.pdf - Sppectral Methods in Matlab", L. N. Trefethen, SIAM.

Metodi didattici

During the lectures the contents of the course will be analyzed, highlighting the difficulties related to the introduced numerical techniques. Moreover, the course will consist of a part of autonomous re-elaboration, supervised by the professor, consisting in the application of the numerical techniques through laboratory programming. This activity will allow students to acquire the ability to deal with "numerical" difficulties and to evaluate the reliability and consistency of the obtained results

Modalità verifica apprendimento

The exam includes: - the assignment of a work for the application of numerical techniques introduced to solve a specific problem. The analysis of the results obtained by the student will allow to evaluate the acquisition of the above listed skills. In particular the threshold of sufficiency is fixed to the ability to achieve reliable numerical results. - an assessment of the knowledge through a discussion of topics of the course. The threshold of sufficiency consists in the knowledge of the discriminating characteristics of the various methods presented in the course.

Altre informazioni

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Obiettivi agenda 2030 per lo sviluppo sostenibile

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Referenti e contatti

Numero verde

800 904 084

Segreteria studenti

E. segreteria.scienze@unipr.it
 

Servizio per la qualità della didattica

Manager della didattica:
Dott.ssa Giulia Bonamartini
T. +39 0521 904157
E. servizio smfi.didattica@unipr.it
E. del manager giulia.bonamartini@unipr.it

Presidente del corso di studio

Prof. Luca Lorenzi
E. luca.lorenzi@unipr.it

Delegato orientamento in ingresso

Prof. Luca Lorenzi
E.  luca.lorenzi@unipr.it

Delegato orientamento in uscita

Prof.ssa Chiara Guardasoni
E. chiara.guardasoni@unipr.it

Docenti tutor

Prof.ssa Alessandra Aimi
E. alessandra.aimi@unipr.it

Prof. Luca Lorenzi
E. luca.lorenzi@unipr.it

Prof. Adriano Tomassini
E. adriano.tomassini@unipr.it

Delegati Erasmus

Prof. Leonardo Biliotti
E. leonardo.biliotti@unipr.it

Referente assicurazione qualità

Prof.ssa Alessandra Aimi
E. alessandra.aimi@unipr.it

Tirocini formativi

Prof. Costantino Medori
E. costantino.medori@unipr.it

Referente per le fasce deboli

Prof.ssa Fiorenza Morini
E. fiorenza.morini@unipr.it

Studentessa tutor

Dott. Jacopo Borsotti
E. jacopo.borsotti@studenti.unipr.it