Computational Modelling and Simulation in Engineering Physics

General characterization

Prerequisites

Programming proficiency. Access to a computer. Undergraduate course in Physical Engineering or equivalent. 

Bibliography

"Introduction to Statistical Physics" J. Casquilho, P. Teixeira (2015) QC174.8.CAS

"An Introduction to Computer Simulation Methods: applications to physical systems" H. Gould, J. Tobochnik, W. Christian (2006) QC52.GOU

Teaching method

In each block of the program syllabus an introduction to the topic, and or methods, is presented by the teacher. The students implement a minimal base program, obtain results and analyze them. The program is changed by the students, with teacher supervision, other assumptions or methods of simulation are explored and the new results are analyzed and  compared with previous ones.  The students present the program to the teacher in the classroom and at a predefined date, the students deliver the final program.

Evaluation method

In accordance with the KNOWLEDGE ASSESSMENT RULES OF THE FACULTY OF SCIENCES AND TECHNOLOGY OF THE UNIVERSITY NOVA DE LISBOA (approved on January 16, 2018), this is a curricular unit with "Laboratory or Project Assessment". Carried out based on carrying out practical laboratory work, design or problem solving, and their reports and/or respective tests, carried out individually or in groups, and their discussion, if any;

1) Assessment by 2 computational works among those proposed by the teacher and carried out in a group with a grade of up to 9 points.

2) Summative assessment of performance and participation in classes and discussion on the various topics throughout the semester

Frequência at the UC by attending at least 2/3 of the classes.

Subject matter

1 - Review of Python language and introduction to numerical and graphic libraries.

2. First aplications of numerical and graphic libraries: forest fire simulation application.

3. Monte Carlo simulations of simple, non-reversible, increasing and increasing random walks that are self-avoiding.

4. Ferromagnetism: Introduction, Heisenberg Model, Weiss Model, Landau Theory, Monte Carlo Simulations with the Ising model;

5. Differential equations - numerical methods

6. Python code optimization

Programs

Programs where the course is taught: