Public University of Navarre



Castellano | Academic year: 2016/2017
Bachelor's degree in Industrial Engineering at the Universidad Pública de Navarra
Course code: 242602 Subject title: NUMERICAL METHODS
Credits: 3 Type of subject: Mandatory Year: 3 Period: 2º S
Department: Mathematics and Computer Engineering
Lecturers:
ARRARAS VENTURA, ANDRÉS   [Mentoring ]

Partes de este texto:

 

Module/Subject matter

Module: Scientific-technological transversal module.

Subject matter: Further studies in Mathematics and Physics.

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Descriptors


Numerical Analysis.

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General proficiencies

  • CG3: Knowledge of basic and technological subjects qualifying to learn new methods and theories, and providing versatility to adapt to new situations.
  • CG4: Problem solving proficiency with personal initiative, decision making, creativity and critical reasoning. Ability to elaborate and communicate knowledge and skills in the field of Industrial Engineering.

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Specific proficiencies

  • CFB1: Ability to solve mathematical problems in engineering. Ability to apply theoretical knowledge of linear algebra, geometry, differential geometry, differential and integral calculus, ordinary and partial differential equations, numerical methods, algorithmics, statistics and optimization. 
  • CFB3: Proficiency to use and program computers, operating systems, databases and software with application in engineering.

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Learning outcomes


At the end of the course, the student is able to:

  • O1: Understand the basic principles and aims of Numerical Analysis.
  • O2: Describe and use direct and iterative methods to solve linear systems and boundary value problems.
  • O3: Describe and use fixed-point iteration methods to solve nonlinear equations and systems.
  • O4: Describe and use Runge-Kutta methods and linear multistep methods to solve initial value problems and initial-boundary value problems.
  • O5: Understand the applicability conditions for each method, and analyze and interpret its results.
  • O6: Understand, run and modify simple programs written in MATLAB/Octave which implement the numerical methods under consideration.

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Methodology

Methodology - Activity
On-site hours
Off-site hours
A-1 Lectures
21.5
 
A-2 Practical sessions
6
 
A-3 Self-study
 
44
A-4 Exams and assessment
2.5
 
A-5 Tutoring
1
 
Total
31
44

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Relationship between formative activities and proficiencies/learning outcomes

Formative activity
Proficiency
A1
CFB1, CFB3
A2 
CG3, CG4, CFB1, CFB3
A3
CFB1, CFB3
A4 
CG3, CG4, CFB1, CFB3
A5
CG3, CG4, CFB1, CFB3

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Languages


English.

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Evaluation


Continuous assessment is considered along the semester based on the following activities:

Learning outcome

Assessment activity

Weight (%)

Resit assessment

O1, O2, O5, O6

Midterm exam A
on lessons 1 and 2

40

Yes
(final exam)

O3, O5, O6

Midterm exam B
on lesson 3

25

Yes
(final exam) 

O4, O5, O6

Midterm exam C
on lesson 4

35
Minimum to be considered
in the final mark: 2/10

 Yes
(final exam)


In order to pass the subject, one of the following conditions must be fulfilled:

  • the mark of the midterm exam C is not less than 2 and the weighted average of the marks of all three midterm exams is not less than 5;
  • the mark of the final exam covering the whole course (to be scheduled during the resit assessment period) is not less than 5.

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Contents

  • Numerical methods for linear systems: direct and iterative methods.
  • Numerical methods for nonlinear equations and systems.
  • Numerical methods for ordinary differential equations.
  • Numerical methods for partial differential equations.

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Agenda

 

  1. Introduction to Numerical Analysis.
    Preliminaries. Numerical differentiation.

  2. Numerical solution of linear systems.
    Matrix norms and conditioning. Direct and iterative methods. Application to the solution of boundary value problems.

  3. Numerical solution of nonlinear equations and systems.
    Fixed-point iteration methods. Newton's method. Quasi-Newton methods.

  4. Numerical solution of initial value problems.
    Runge-Kutta methods. Linear multistep methods. Stiff problems. Application to the solution of initial-boundary value problems.


Practical sessions:

  • Session 1: Numerical solution of linear systems.
  • Session 2: Numerical solution of nonlinear equations and systems.
  • Session 3: Numerical solution of initial value problems.

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Bibliography

Access the bibliography that your professor has requested from the Library.



Basic bibliography:

  1. R.L. Burden, J.D. Faires. Numerical analysis. Brooks-Cole.
  2. J.D. Faires, R.L. Burden. Numerical methods. Brooks-Cole.
  3. D. Kincaid, W. Cheney. Numerical analysis. Mathematics of scientific computing. American Mathematical Society.

Additional bibliography:

  1. C. Conde, G. Winter. Métodos y algoritmos básicos del álgebra numérica. Editorial Reverté.
  2. C. Moler. Numerical computing with MATLAB. SIAM. Electronic edition: http://www.mathworks.es/moler/chapters.html.
  3. L.F. Shampine, I. Gladwell, S. Thompson. Solving ODEs with MATLAB. Cambridge University Press.

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Location

Lecture room building (Arrosadía Campus). The practical sessions will take place at the computer laboratory.

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