DTE-3601 Simulations - 5 stp

Diverse concepts and methods of applied mathematics, numerical analysis and approximation theory, including aspects of optimal control, game theory, Monte Carlo methods, computational fluid dynamics (CFD), finite and boundary element methods (FEM/BEM), etc.

Argument-based selection of a best approach for modelling and simulation in a given context among several alternatives.

A relevant undergraduate Bachelor Engineering program with minimum 25 credits mathematics, 5 credits statistics, 7,5 credits physics

Application code: 9371

Recommended:

- Master-level course in Numerical Methods

- Master-level course in Linear Algebra 2

- Master-level course in Partial Differential Equations and the Finite Element Method

- Master-level course in Geometric Modelling

After passing the course, students will have the following learning outcomes:

Knowledge and understanding:

• Well systematized knowledge of fundamental terminology, definitions, concepts, ideas, methods and results needed to formulate mathematical models, to develop symbolic implementations and/or numerical approximations of these models that can be simulated numerically, with respective verification and, if necessary, tuning and upgrading.
• Getting acquainted with a rich diversity of concrete case of modelling and simulating mechanisms and processed from various fields of natural and engineering sciences, on macro and micro (including nano-) level.
• Main emphasis is on modelling with boundary-value problems for linear and non-linear partial differential equations of elliptic, parabolic, hyperbolic and mixed type, and their numerical solutions, together with analysis of the performance of these models in simulation (stability, order of accuracy, compexity, etc.)

Skills:

• Ability to use the acquired knowledge to perform mathematical modelling and computer simulation of mechanisms and processes.
• Ability to assess the performance and verify the fidelity of the results of computer simulations.

Competence:

• A holistic understanding of the iterative nature and main components of the entire process of mathematical modelling and numerical simulation, with verification and scientific visualization of the results, and incorporating these results within larger cooperation projects.
• Versatility in cooperation in joint projects of research and development teams.
• Versatility in communication of concepts, ideas and methods of mathematical modelling and numerical simulations.
• Some of the best students in this course, who later choose a topic in computer simulations for their master diploma thesis project, will be expected to communicate their results at international conferences.

• Classroom lectures
• Classroom exercises