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B014739 - ADVANCED NUMERICAL ANALYSIS
Main information
Teaching Language
Course Content
Suggested readings
Learning Objectives
Prerequisites
Teaching Methods
Type of Assessment
Course program
Academic Year 2018-19
Coorte 2018 - Second Cycle Degree in Mechanical Engineering
Course year
First year - Second Semester
Belonging Department
Industrial Engineering (DIEF)
Course Type
Single education field course
Scientific Area
MAT/08 - NUMERICAL ANALYSIS
Credits
6
Teaching Hours
48
Teaching Term
25/02/2019 ⇒ 07/06/2019
Attendance required
No
Type of Evaluation
Final Grade
Course Content
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Course program
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Lectureship
Mutuality
Course teached as:
B014739 - ANALISI NUMERICA
3-years First Cycle Degree (DM 270/04) in MECHANICAL ENGINEERING
Curriculum SCIENTIFICO-MECCANICO
B014739 - ANALISI NUMERICA
3-years First Cycle Degree (DM 270/04) in MECHANICAL ENGINEERING
Curriculum SCIENTIFICO-MECCANICO
Teaching Language
Italian
Course Content
The Matlab environment and programming language. Direct methods for sparse linear systems. Iterative methods for nonlinear systems of equations. Newton-Cotes, composite and adaptive quadrature rules. Numerical methods for the Cauchy problem. Numerical methods for partial differential equations.
Suggested readings (Search our library's catalogue)
A. Quarteroni, R. Sacco, F. Saleri, Matematica numerica, Springer–Verlag.
J. Epperson, Introduzione all'analisi numerica,Teoria, metodi, algoritmi, Mc-Graw Hill.
J. Epperson, Introduzione all'analisi numerica,Teoria, metodi, algoritmi, Mc-Graw Hill.
Learning Objectives
Knowledge of standard and advanced numerical methods for solving linear and nonlinear equation, ordinary and partial diferential equations, and integrals.
Ability to solve problems modelling engineering applications, Matlab programming.
Ability to solve problems modelling engineering applications, Matlab programming.
Prerequisites
Numerical Calculus
Teaching Methods
Lectures and Matlab laboratory.
Type of Assessment
Oral exam on the numerical methods presented, their theoretical properties and implementation.
Course program
Matlab: environment and programming language. Direct factorization for sparse linear systems. Newton method and its variants, linesearch strategies. Newton-Cotes and composite quadrature rules.
One-step merical methods for the Cauchy problem: Runge-Kutta and Runge-Kutta-Fehlberg methods, some implicit schemes. Finite differences methods for partial differential equations, an introduction to finite elements methods.
One-step merical methods for the Cauchy problem: Runge-Kutta and Runge-Kutta-Fehlberg methods, some implicit schemes. Finite differences methods for partial differential equations, an introduction to finite elements methods.