04524 - Numerical Analysis

Academic Year 2024/2025

  • Docente: Lucia Romani
  • Credits: 6
  • SSD: MAT/08
  • Language: Italian
  • Teaching Mode: Traditional lectures
  • Campus: Forli
  • Corso: First cycle degree programme (L) in Aerospace Engineering (cod. 9234)

    Also valid for First cycle degree programme (L) in Mechanical Engineering (cod. 0949)

Learning outcomes

At the end of the course the student knows the numerical-mathematical aspects and the main algorithmic methodologies that allow him to solve problems of interest in engineering. In particular: the methods of numerical linear algebra to solve linear and non-linear systems, least squares linear problems, differential models. The student carries out exercises and projects together with the teacher during the hours of computer laboratory with the help of the MATLAB software.

Course contents

1. Finite numbers - Floating point representation of real numbers. Machine or floating point numbers. Representation errors. Floating point arithmetic. Error analysis in elementary arithmetic operations. Error propagation: conditioning of a problem and stability of an algorithm.

2. Linear Algebra recalls on vectors, matrices and vector spaces. Vector norms and matrix norms.

3. Zeros of Functions - Problem formulation. Resolution techniques. Iterative methods, convergence and order of convergence of methods. Global convergence and local convergence methods. Bisection method, Newton's method and the secant method. Fixed-point iteration methods. Convergence theorems.

4. Numerical solution of Linear Systems - Condition number of a matrix and conditioning of the problem. The Gauss elimination algorithm. LU factorization of a matrix. Stability of LU factorization. Pivoting. Cholesky factorization of symmetric and positive definite matrices. Householder method and QR factorization of non-square matrices. Properties of the illustrated methods.

5. Least Squares approximation - Normal equations and QRLS method (least squares solution using QR factorization). Properties of the two methods.

6. Interpolation - Polynomial interpolation. Existence and uniqueness of the interpolating polynomial. Lagrange's form and Newton's form of the interpolating polynomial. Error expression in polynomial interpolation. Convergence problems. Conditioning of the polynomial interpolation problem.

7. Numerical Integration - Newton-Cotes quadrature formulas (Trapezoidal and Simpson's formula). Simple and composite quadrature formulas. Error of simple and composite formulas. Adaptive quadrature formulas.

Readings/Bibliography

It will be fundamental to use the notes taken during the lectures and the computer material made available at https://virtuale.unibo.it/ 

 

+ For further study we recommend:

[1] A. Quarteroni, R. Sacco, F. Saleri, P. Gervasio: Matematica Numerica (4a edizione), Springer, 2014.

[2] A. Quarteroni: Matematica Numerica - Esercizi, Laboratori e Progetti (2a edizione), Springer, 2013.

[3] A. Quarteroni, F. Saleri, P. Gervasio: Calcolo Scientifico - Esercizi e problemi risolti con MATLAB e Octave (6a edizione), Springer 2017.

 

+ Older books, only for the most enthusiasts:

[4] R. Bevilacqua, D. Bini, M. Capovani, O. Menchi: Metodi Numerici, Zanichelli, Bologna, 1992.

[5] D. Bini, M. Capovani, O. Menchi: Metodi numerici per l'algebra lineare, Zanichelli, Bologna, 1996.

 

+ Alternatively, for those who want a text in English we recommend:

[6] E. E. Mikhailov: Programming with MATLAB for Scientists: A Beginner’s Introduction, CRC Press, Inc., 2017.

[7] A. Quarteroni, F. Saleri, P. Gervasio: Scientific Computing with MATLAB and Octave (4th edition), Springer, 2014.

[8] U. M. Ascher, C. Greif: A first Course in Numerical Methods, SIAM, 2011.

[9] C. Moler: Numerical Computing with MATLAB, SIAM, 2004.

Teaching methods

The course is structured in lectures and exercises in the computer laboratory. More precisely, the lectures on the basic numerical methods to solve classical mathematical problems through the use of a computer are followed by laboratory exercises aimed at implementing these methods in MATLAB and developing an adequate sensitivity and awareness of their use.

In consideration of the type of activity and of the adopted teaching methods, the attendance of this training activity requires the prior participation of all students in Modules 1 and 2 of Health and Safety training courses [https://elearning-sicurezza.unibo.it/?lang=en] in e-learning mode.

Assessment methods

The end-of-course exam aims to verify the achievement of the following educational objectives:

- knowledge of the fundamental elements of numerical calculus, illustrated during the lectures;

- ability to exploit basic numerical methods to solve mathematical problems of usual interest in engineering by using a computer.

The end-of-course exam (the evaluation of which is in thirtieths) will take place in the computer laboratory. The student has 90 minutes to solve two exercises that include both the development of MATLAB codes for solving numerical problems and the written answer to theoretical questions on the topics covered in the lessons.

During the exam the use of support material such as textbooks, notes and computer supports is not allowed.

To participate in the exam students must register in the lists available on the AlmaEsami web platform. On the day of the exam students will be able to access the laboratory and take the test only after showing an identification document.

The dates of the exams can be consulted on the AlmaEsami web platform of the University of Bologna and are visible several months in advance.

Teaching tools

The course includes a laboratory activity in which the MATLAB software is used. The corresponding teaching material will be made available to the student in electronic format, and will be downlodable at https://virtuale.unibo.it/

Students will also benefit from the support of a tutor who will help them to solve the exercises assigned by the teacher during the course.

Office hours

See the website of Lucia Romani

SDGs

Quality education

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.