IDENTIFYING DATA 2015_16
Subject (*) NUMERICAL METHODS IN ENGINEERING Code 17665105
Study programme
Computer Engineering: Computer Security and Intelligent Systems (2013)
 Cycle 2nd
Descriptors Credits Type Year Period
6 Compulsory First 1Q
Language
Anglès
Department Enginyeria Informàtica i Matemàtiques
Coordinator
GARCÍA GÓMEZ, CARLOS
 E-mail carlos.garciag@urv.cat
Lecturers
GARCÍA GÓMEZ, CARLOS
Web http://moodle.urv.cat
General description and relevant information Introduction to numerical methods used in engineering.

Competences
Type A Code Competences Specific
 A3 Perform mathematical modelling, calculation and simulation in company technology and engineering centres, particularly in tasks of research, development and innovation in all areas related to computer engineering.
 T7 Understand and apply advanced knowledge of high performance computing and numerical or computational methods to engineering problems.
 T9 Apply computational, mathematical, statistical and artificial intelligence methods in order to model, design and develop applications, services, smart systems and knowledge-based systems.
Type B Code Competences Transversal
 B1 Learning to learn
 B3 Treballar de forma autònoma amb responsabilitat i iniciativa.
Type C Code Competences Nuclear
 C2 Be advanced users of the information and communication technologies
 C3 Be able to manage information and knowledge

Learning outcomes
Type A Code Learning outcomes
 A3 Apply the basic numerical techniques appearing in scientific and engineering problems.
Select the most suitable algorithm in each case.
 T7 Describe the error, stability and convergence concepts of an algorithm.
Identify and know how to program the basic algorithms to solve problems simulating evolutionary systems.
 T9 Correctly interpret the results obtained with a numerical algorithm.
Type B Code Learning outcomes
 B1 Adapt the learning objectives put forward by the teaching staff.
 B3 Decide how to manage and organize work and time.
Type C Code Learning outcomes
 C2 Use software for on-line communication: interactive tools (web, moodle, blogs, etc.), e-mail, forums, chat rooms, video conferences, collaborative work tools, etc.
 C3 Locate and access information effectively and efficiently.

Contents
Topic Sub-topic
Concepts of error and the error propagation, algorithm stability and convergence.
Roots of nonlinear functions
Function approximation
Simulation of dynamical systems

Planning
Methodologies  ::  Tests
  Competences (*) Class hours
 Hours outside the classroom
 (**) Total hours
Introductory activities
1 0 1
Lecture
T7
 15 30 45
Problem solving, classroom exercises
A3
B1
 10 30 40
Practicals using information and communication technologies (ICTs) in computer rooms
T9
B3
C2
 15 30 45
Personal tuition
15 0 15
 
Objective short-answer tests
T7
C3
 1 0 1
Mixed tests
A3
T9
B1
 3 0 3
 
(*) On e-learning, hours of virtual attendance of the teacher.
(**) The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies
  Description
Introductory activities Description of the development of classes and the evaluation of the subject.
Lecture Transfer of basic theoretical knowledge
Problem solving, classroom exercises Resolution of problems in class with active student participation
Practicals using information and communication technologies (ICTs) in computer rooms Formulation, analysis and resolution of problems related to the topic of the course.
Personal tuition Answering questions on individualized way

Personalized attention
Description
Answering questions on individualized way in the teacher's office

Assessment
Methodologies Competences Description Weight        
Practicals using information and communication technologies (ICTs) in computer rooms
T9
B3
C2
 Formulaton, analysis and resolution of problems related to the contents of the course. 40%
Objective short-answer tests
T7
C3
 Short questions 20%
Mixed tests
A3
T9
B1
 Global practice
40%
Others  
 
Other comments and second exam session

The second call will consist of a test which will count 20%. In principle, the practical grade will remain, but if the student wants, he can improve it.

Sources of information

Basic Ronald W. Shonkwiler, Franklin Mendivil, Explorations in Monte Carlo Methods, última disponible, Springer
Forman S. Acton, Numerical Methods that Work, última disponible, Mathematical Association of America
Robert, Ch.P., Casella, G, Introducing Monte Carlo Methods With R , última disponible, Springer

Complementary James E. Gentle, Random Number Generation and Monte Carlo Methods, última disponible, Springer
Suess, E.A., Trumbo, B.E., Introduction to Probability Simulation and Gibbs Sampling with R , última disponible, Springer

Recommendations
(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.