Numerical Analysis
Module Notes
Module Details
Ability for deep understanding of the fundamental numerical methods.
Ability to recognize the advantages and disadvantages of each method in order to decide the most convenient in use on application basis
Ability to use specific software in order to develop the necessary applications
Ability to analyze and interpret data
There are no prerequisite modules. It is, however, recommended that students should have a good knowledge of Mathematics (Calculus, Linear Algebra, Differential Equations) as well as fundamental skills on Scientific Programming)
Introduction (discretization, error analysis), Numerical Differentiation (forward, backward and central differences), Numerical Integration (trapezoid rule, Simpson rule, Newton-Cotes formulae), Interpolation/Extrapolation (Taylor, Lagrange polynomials), Numerical solution of algebraic equations (trial & error, bisection, Newton-Raphson), Numerical solution of linear systems (Gauss, Jacobi, Gauss-Seidel), Numerical Integration of Ordinary Differential Equations (Euler, Runge-Kutta), Finite Differences, Special Topics, Non-linear systems.
Teaching Organization
LECTURES: 3 h/w
RECITATION: 1 h/w
LAB/PRACTICE: 3 h/w
PROJECT/HOMEWORK: 6/semester
Total Module Workload (ECTS Standards):
Assessment
- (70%): Final Written Examination, which includes problem-solving and theory questions.
- (30%): Evaluation of Six (6) Laboratory Exercises / Programming Projects and Six (6) Preparatory (Ticket) Exercises, submitted throughout the semester at the Computer Center of the Department of Chemical Engineering.
Only students who have attended all laboratory exercises are eligible to participate in the written exam. This prerequisite is verified by the attendance records maintained by the Laboratory and Course coordinators.
Gilat Amos, Subramaniam Vish, Αριθμητικές Μέθοδοι για Μηχανικούς και Επιστήμονες, Broken Hill (2021)
ISBN: 9789925576357