Departments' graduate courses

Course start and periodicity may vary. Please see details for each course for up-to-date information. The courses are managed and administered by the respective departments. For more information about the courses, how to sign up, and other practical issues, please contact the examiner or course contact to be found in the course information.

Probabilistic Risk Analysis (PRA)

  • Course code: FBOM095
  • Course higher education credits: 5.0
  • Graduate school: Civil and Environmental Engineering
  • Course is normally given: Concact Lars Rosén,
  • Language: The course will be given in English

Course description
Risk assessment has become an increasingly important part of civil and environmental engineering. It has a wide range of applications, e.g. in transportation, remediation of contaminated land, protection of drinking water resources, ground stability, and tunneling. Risk assessment not only includes the estimation of risk levels, but also provides a basis for decisions regarding what are the most relevant actions to be taken to reduce and control risks. In some cases, risk assessment is also part of the regulatory framework and required as a basis for design, construction and performance of technical systems.

Risk assessment is an inherently complex and multi-dimensional concept, since it involves the combination of probability and consequence of unwanted events as well as the evaluation of risk with respect to risk tolerability and alternative actions to reduce and control risks. Probabilistic risk assessment (PRA) is a quantitative concept and thus involves quantification of probabilities and consequences. A major issue in PRA is the understanding of uncertainty and how it can be modeled mathematically using probability.

In this doctoral course we will:

  • Present the basic concepts of PRA and uncertainty modeling.
  • Present Bayesian and classical statistical inference methods.
  • Apply probabilistic methods for modeling uncertainty.
  • Apply logic tree models (fault trees, event trees, decision trees).
  • Apply Monte Carlo simulation.
  • Present methods for expert judgments.
  • Work on project assignments.
  • Present our findings at a seminar.
The course is a mixture of lectures by Tommy Norberg and Lars Rosén, seminars, and a project assignment. The students are encouraged to work on their own projects.


Bedford, T., Cooke, R. 2001. Probabilistic Risk Analysis. Cambridge University Press.

Lecture notes.

Senior Lecturer Tommy Norberg, former on the department of Mathematical Science, Senior Lecturer Jenny Norrman, division of GeoEngineering, Professor Lars Rosén, division of GeoEngineering,
More information
Contact Lars Rosén,

Published: Tue 22 Aug 2017.