Model Output Uncertainty in Risk Assessment
Volume 9, Number 5, September 2013 - Paper 02 - pp. 475-486
TERJE AVEN1 and ENRICO ZIO21 University of Stavanger, NORWAY
2 Chair on Systems Science and the Energetic Challenge, European Foundation for New Energy - Electricité de France, at École Centrale Paris - Supelec, France and Politecnico di Milano, ITALY
(Received on June 01, 2012 , revised on May 28, 2013)
In the context of risk assessment, we focus on the prediction of an unknown quantity Z whose value is realised in the future, and for which experimental data are not available. We deal with the issue of the uncertainty associated to the difference between the output of the model used for the prediction of Z and the true unknown value of Z itself. Accepted principles and methods for handling this uncertainty in the specific conditions of risk assessment are still lacking. Through the paper we seek to contribute by:
We argue that in risk assessment, quantification of model output uncertainty serves for the qualification and acceptance of the models used, whose outputs feed the following risk-informed decision making process.
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