Course content

To face the increasing complexity of technical systems, the different engineering disciplines have virtualized their content to a large extent: each industrial system comes now with hundreds if not thousands of models. These models are used not only in the design phase of systems, but also for their operation and even for their decommissioning. This course is about models, with a special focus on risk assessment models. It is organised as a series of seminars on various subjects related to model-based system engineering and model-based safety assessment: mathematical frameworks, algorithms and heuristics, modeling languages and paradigms, modeling methodologies and best practices, safety standards... Examples of topics: perspective on system architecture; mathematical models of degradation; finite state automata, high level modeling languages; advanced data-structures and algorithms for probabilistic risk analysis; optimization methods, safety integrity levels...

Learning outcome

The course gives a vision of some active research topics and a state of the art on model-based system engineering and model based safety assessment.

Learning methods and activities

The course is organized as a series of seminars. Aside attending seminars, students will be assigned an individual homework. This homework will typically consist in studying a (reasonable size) use case, designing a model for that use case, performing some experiments on that model and reporting the results of these experiments. The use case will be preferably related to their PhD subject. If there are less than 3 registered students, the course coordinator will decide whether the course will take place.

Recommended previous knowledge

A basic knowledge of methods for risk analysis is recommended. Some knowledge of programming is also useful.

Required previous knowledge

All students taking this course must be enrolled in a PhD program at NTNU or a different university.

Course materials

The course relies for the most part on the following book, but it may be completed by slides, articles and books.

Antoine Rauzy. Model-Based Reliability Engineering - An Introduction from First Principles. AltaRica Association 2022. ISBN 978-82-692273-2-1 (pdf available on the author's webpage).