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Scheda Riassuntiva
Anno Accademico 2018/2019
Scuola Scuola di Ingegneria Industriale e dell'Informazione
Insegnamento 096233 - MATHEMATICAL AND NUMERICAL METHODS IN ENGINEERING [I.C.]
  • 096231 - MATHEMATICAL AND NUMERICAL METHODS IN ENGINEERING [2]
Docente Vergara Christian
Cfu 7.00 Tipo insegnamento Modulo Di Corso Strutturato

Corso di Studi Codice Piano di Studio preventivamente approvato Da (compreso) A (escluso) Insegnamento
Ing Ind - Inf (Mag.)(ord. 270) - BV (478) NUCLEAR ENGINEERING - INGEGNERIA NUCLEARE*AM096296 - NUMERICAL METHODS IN ENGINEERING
Ing Ind - Inf (Mag.)(ord. 270) - MI (471) BIOMEDICAL ENGINEERING - INGEGNERIA BIOMEDICA*AM096233 - MATHEMATICAL AND NUMERICAL METHODS IN ENGINEERING [I.C.]
Ing Ind - Inf (Mag.)(ord. 270) - MI (491) MATERIALS ENGINEERING AND NANOTECHNOLOGY - INGEGNERIA DEI MATERIALI E DELLE NANOTECNOLOGIE*AM096296 - NUMERICAL METHODS IN ENGINEERING

Obiettivi dell'insegnamento

The goal of the course is to provide students with notions and tools about the understanding, the development and the analysis of numerical methods for the approximation of partial differential equations. In particular, the course will treat two families of discretization methods for steady and time dependent problems: finite differences and finite elements. Particular attention will be devoted to simple (initial and boundary value) problems deriving from continuum mechanics, which are prarticularly important for engineers. The learning process will involve lectures on the theory and computer laboratories about the application of simple examples of numerical methods.


Risultati di apprendimento attesi

The lectures and the laboratories will provide students with:

i) knowledge and understanding of

* finite difference approximation of time and space operators (of first and second order);

* finite element approximation in space (of first and seond order operators);

* the fundamental concepts of: consistency, stability and convergence;

ii) the ability to apply the previous knowledge to simple examples on the calculator. In particular the student is required to

* be able to run and suitably modify a computer script provided by the instructor;

* critically discuss the resuls of the numerical experiments above in prespective of the theory;

The instructor expects a broad comprehension of the subjects which sould not be limited to the statement of theoretical results.

Instead, the acquired knowledge should enable students to express critical judgment and make informed choices on numerical methods for partial differential equations.

The students are expected to express their answers in a mathematically rigorous and clear way.


Argomenti trattati

First Part – Differential modeling and finite difference approximation

  1. Review

Finite difference formulae to approximate derivatives. Numerical approximation of ordinary differential equations, convergence, absolute stability.

  1. First-order conservation laws

Approximation with finite differences. Convergence, consistency, zero-stability and absolute stability. Forward Euler-centered scheme. Upwind, Lax-Friedrichs and Lax-Wendroff schemes. Analysis of the schemes, CFL condition and its meaning. Backward Euler-centered scheme. A quick description of systems and of non-linear problems.

  1. Diffusion

Discretization of the heat equation with finite differences. Implicit and explicit time marching schemes, the theta-method, stability analysis.

  1. Laplace-Poisson equation

Discretization with finite differences of a one-dimensional elliptic problem. Imposition of the Dirichlet and Neumann boundary conditions. Algebraic formulation and matrix properties. Diffusion-convection and diffusion-reaction problems.

  1. Wave equation

Discretization of the wave equation with finite difference explicit and implicit schemes. Leapfrog and Newmark schemes. Stability properties.

 

Second Part – Variational formulations and discretizations via finite element method.

  1. Weak formulation and Finite Elements approximation of stationary problems

Bilinear form, abstract variational problems and Lax-Milgram lemma. Variational formulation of elliptic problems and applications to transport-reaction-diffusion equations. Introduction to the Galerkin method for a one-dimensional elliptic problem. Consistency, stability and convergence. Cea' Lemma. The finite elements method. Linear and quadratic finite elements. Definition of Lagrangian basis functions, of composite interpolation and error estimates. Extension to the 2D case. Approximation of the diffusion-convection-reaction problem: comparison with the finite difference case and stability analysis. Stabilization with the upwind strategy and the mass lumping technique.

       6. Evolution problems

Approximation with the Galerkin method, the semi-discrete problem. Explicit and implicit time marching schemes, the theta-method. Stability properties. A quick description of finite elements for hyperbolic problems.


Prerequisiti

We recommend that students who attend this course have knowledge of linear algebra and numerical analysis, in particular:

* numerical solution of linear systems (by direct and iterative methods);

* polynomial interpolation;

* basic numerical methods for the approximation of ordinary differential equations;


Modalità di valutazione

There are five examination dates (two in January-February, two in June-July, one in September). The course consists in two moduli, one in Mathematical Methods (ref. G. Arioli and F. Cipriani) and one in Numerical Methods (ref. C. Vergara and P. Zunino).
The exam in Mathematical Methods is written and consists in both questions on the theory and exercises. The exam in Numerical Methods consists in a written part and an optional oral part. The written part of both moduli takes place in the same day. Students can take the oral exam for the Numerical Methods modulus only when the corresponding written grade is at least 15 out of 30.

The final grade is the (rounded up) arithmetic mean of the grades obtained in the two moduli. To get the grade “30 cum laude” one should obtain such grade in both the subparts. If this is not the case, a single "30 cum laude" in one of the parts will be considered as 30 in performing the arithmetic mean.

It is possible to take the exam in one modulus (Mathematical or Numerical Methods) in one of the five examination dates and in the other modulus in another examination date, provided such dates are in the same academic year. It is mandatory to take the written and the oral part of the Numerical Methods modulus within the same examination date, i.e. it is not possible to give the written part in one examination date and the oral part in another one.

The participation to the written exam of one of the two moduli, automatically discards any previous grade obtained for that modulus, even if the student chooses to withdraw.

NOTES

1)  Mathematical Methods in Engineering and Numerical Methods in Engineering are also single courses which can be taken independently.

2)  Browsing texts, notes, and electronic devices are not allowed during the tests. It is mandatory to bring an ID (e.g. identity card, driver’s licence,…) in order to be identified.

3)  Registration to the exam is mandatory. Unregistered students will not be admitted.

 

The exam is designed to test the student on the following skills:

i) the knowledge and understanding of

* finite difference approximation;

* finite element approximation in space;

* the ability to solve simple exercises based on all the metods that have been introduced in the course;

* the concepts of consistency, stability and convergence applied to all the metods that have been introduced in the course;

ii) the ability to apply the previous knowledge to simple examples on the calculator. In particular the student is required to

* be able to run and suitably modify a computer script provided by the instructor;

* critically discuss the resuls of the numerical experiments above in prespective of the theory;

The instructor expects a broad comprehension of the subjects which sould not be limited to the statement of theoretical results.

Instead, the acquired knowledge should enable students to express critical judgment and make informed choices on numerical methods for partial differential equations.

The students are expected to express their answers in a mathematically rigorous and clear way.


Bibliografia
Risorsa bibliografica obbligatoriaQuarteroni A., Modellistica Numerica per Problemi Differenziali, Editore: Springer, Anno edizione: 2012

Forme didattiche
Tipo Forma Didattica Ore di attività svolte in aula
(hh:mm)
Ore di studio autonome
(hh:mm)
Lezione
45:30
68:15
Esercitazione
24:30
36:45
Laboratorio Informatico
0:00
0:00
Laboratorio Sperimentale
0:00
0:00
Laboratorio Di Progetto
0:00
0:00
Totale 70:00 105:00

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese
Disponibilità di materiale didattico/slides in lingua inglese
Disponibilità di libri di testo/bibliografia in lingua inglese
Possibilità di sostenere l'esame in lingua inglese
Disponibilità di supporto didattico in lingua inglese
schedaincarico v. 1.6.5 / 1.6.5
Area Servizi ICT
20/09/2020