Curricular Unit: | Code: | ||

Modeling and Computing Applied to Engineering Problems | 831MCAP | ||

Year: | Level: | Course: | Credits: |

3 | Undergraduate | Computer Systems Engineering | 4 ects |

Learning Period: | Language of Instruction: | Total Hours: | |

Spring Semester | Portuguese/English | 52 | |

Learning Outcomes of the Curricular Unit: | |||

Mathematical models construction and its computational implementation for the understanding and simulation of diverse scenarios in real world situations and for predicting results in engineering problems in several areas, namely, electric and electromagnetic fields, heat transfer and fluid mechanics. | |||

Syllabus: | |||

1. Python programming 2. Applications of differential equations and partial differential equations in mathematical modelling 2.1. Heat transfer 2.2. Electric Fields 2.3. Fluids flow 3. Finite Differences 3.1. Basic Concepts 3.2. Applications and computer solving 4. Finite Elements 4.1. Basic Concepts 4.2. Applications and computer solving | |||

Demonstration of the Syllabus Coherence with the Curricular Unit's Objectives: | |||

The first chapter introduce subjects related with syntax and Python programing paradigms in order to construct programs for numeric integration by the methods presented in chapters 3 and 4. The second chapter presents the theoretical questions associated with the development of some equations that can be solved by those methods. Chapters 3 and 4 develops the concepts and some applications in the domain of the finite differences and finite elements for the solution of some of the problems presented in 2, recurring to the programing language introduced in 1. | |||

Teaching Methodologies (Including Evaluation): | |||

The methodology of teaching and learning is expository, interrogative and demonstrative. Drawing on problem solving geared to allow understanding and application of fundamental concepts and methods. The assessment includes: • One single written test evaluation • One group work (2 students groups at maximum) • Student performance, including attendance, resolution of proposed problems and active participation in classes. | |||

Demonstration of the Coherence between the Teaching Methodologies and the Learning Outcomes: | |||

The proposed methodologies are consistent with the learning objectives of the unit, in a way that they establish a close and continuous coordination between theoretical concepts, practical examples and problem solving. This approach enables the interpretation and practical application concepts and methods | |||

Reading: | |||

[1] Banasiak, J. (2017) Modelação matemática em dimensão um: uma introdução via equações diferenciais e às diferenças. trad. Fernando Pestana da Costa, Filipe Oliveira. IST Press. [2] Chapra, S. C.& Canale, R. P. (2015) Numerical Methods for Engineers. McGraw-Hill. 2015 [3] The Python Tutorial. https://www.learnpython.org [4] Villate, J. E. (2011) Equações Diferenciais e Equações de Diferenças. Faculdade de Engenharia da Universidade do Porto. http://villate.org/doc/eqdiferenciais/ |