Risk analysis 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 underground construction. Risk analysis 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 analysis is also part of the regulatory framework and required as a basis for design, construction and performance of technical systems.
Risk analysis is an inherently complex and multi-dimensional concept, since it involves the combination of probability and consequences of unwanted events and is closely connected to the evaluation of risk with respect to risk tolerability and alternative actions to reduce and control risks. Probabilistic risk analysis (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.
Introduce the concept of Bayesian Value of Information Analysis (VOIA)
Present methods for expert judgments.
Work on project assignments.
Present our findings at a seminar.
The course will be a mix of lectures from the course leaders, presentations of assigned sections of the course literature by the participants, and seminars on project assignments. Each participant will also identify a task related to his/her current research and individually perform a probabilistic risk analysis on this task. The project assignment will be presented orally and in written paper-manuscript form with a maximum of 6000 words.
At the seminars, the participants will show how their projects are progressing. The seminars also provide an opportunity for participants to ask questions and for the teachers to give feedback. Each participant will perform a peer-review of the written paper manuscript by another participant and provide this review to both the participant and the teacher team. The manuscript then will be revised before presentation at the final full-day seminar.
After successfully performing seminars and individual assignments the course will give 7.5 HEC (higher education credits).
The purpose is that after completing the course the participants should be able to:
Perform a probabilistic risk analysis of an engineering problem
To critically review probabilistic risk analyses
To perform uncertainty and sensitivity analysis of risk models
Lars Rosén, examinator, avdelningen för Geologi och geoteknik
Jenny Norrman, avdelningen för Geologi och geoteknik
Ezra Haaf, avdelningen för Geologi och geoteknik
Tommy Norberg, tidigare på institutionen för Matematiska vetenskaper