Computational Modelling and Simulation in Engineering Physics


Knowledge at graduate level in computational and simulation methods.

General characterization





Responsible teacher

Yuri Fonseca da Silva Nunes


Weekly - 3

Total - 42

Teaching language



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


"Complex and Adaptive Dynamical Systems" C. Gros (2015)

"A Guide to Simulation" P. Bratley, B. Fox, L. Schrag (1987) CIUL-1023

"An Introduction to Computer Simulation in Applied Science" F. Abraham, W. Tiller (1972)

"Introduction to Computational Science: Modeling and Simulation for the Sciences", A. B. Shiflet, G. W. Shiflet (2014)

"Basic Concepts in Computational Physics" B. A. Stickler, E. Schachinger (2016)

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


Subject matter

• Numerical integrations methods
• Random variables. Discrete distributions
• Monte Carlo for numerical integration
• Variance reduction methods (option)
• Finite difference method
• Diffusion equation
• Introduction to Linear Regressions
• ARIMA Model(option)
• Introduction to PCA

• Use of R and/or Python to data analysis, modelling and data visualization.
• Compiling DLLs in C++ and/or C#, for high performance computing with R and/or Python and/or VBA integration.
• Use these languages with SQL database integration (option)
• Uses of VBA to integrate other languages and methods functions in Excel


Programs where the course is taught: