Uncertainty in risk engineering: concepts


Overview

Fog on a refinery

This submodule covers the following topics:

  • aleatory, epistemic and value-related categories of uncertainty

  • the objectives of uncertainty modelling

  • different levels of integration of uncertainty modelling in risk assessment

  • the propagation of uncertainty through risk models to characterize output uncertainty

This submodule is a part of the risk management module.

Learning objectives

Upon completion of this submodule, you should be able to:

  • Understand probabilistic modelling and uncertainty propagation

  • Know when probabilistic and possibilistic uncertainty representations should be used

  • Know how to combine probabilistic and possibilistic representations in a single model and propagate uncertainties

  • Understand use of results for decision-making

Course material

Uncertainty in risk engineering: concepts

Lecture slides (PDF)
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Python notebook on uncertainty propagation

View Python notebook online
Download Python notebook
Launch interactive notebook mybinder

Other resources

We recommend the following sources of further information on this topic:

Photo credits: Louis Vest, CC BY-SA