35433 - Numerical Methods

Course Unit Page

Academic Year 2020/2021

Learning outcomes

A successful learner from this course will be able to: a) deal with numerical analysis topics such as: accuracy, truncation and round-off errors, condition numbers, convergence, stability, curve-fitting, interpolation, numerical differentiation and integration, numerical linear algebra; b) deal with numerical methods for solving ordinary and partial differential equations, with finite difference and finite element methods for parabolic and elliptic partial differential equations, applications of computer programs to case studies derived from civil engineering practice.

Course contents

The course will cover fundamental topics in numerical computation, including in particular:

  • Basic concepts: accuracy, precision, truncation and round-off errors, condition numbers, operation counts, convergence and stability.
  • Matlab programming environment.
  • Numerical Solution of nonlinear equations.
  • Numerical solution of linear and non linear systems.
  • Least squares approximation.
  • Numerical solution of Differential Equations.

Throughout the course, lectures will be supported by computer laboratory activities, during which the Matlab software will be used for solving practical problems.

Readings/Bibliography

  • Uri M. Ascher, Chen Greif, A first Course in Numerical Methods, SIAM 2011
  • S. C. Chapra, R. P. Canale Numerical Methods for Engineers, Sixth Edition, Mc Graw Hill.

Teaching methods

The course involves theoretical lectures and practical Matlab exercises carried out during the laboratory classes.

Assessment methods

Assessment is based on a practical exam in the laboratory. The test includes 30% theoretical questions and 70% programming exercises based on the templates explained during the lectures.

Teaching tools

Lectures, lecture slides, exercises, laboratory activities with Matlab and preparatory quizzes on the learning platform IoL

Office hours

See the website of Fabiana Zama