APPLICATIONS OF PROBABILISTIC CONSEQUENCE ASSESSMENT UNCERTAINTY ANALYSIS FOR PLANT MANAGEMENT

摘要

Probabilistic Consequence Assessment (PCA) models describe the dispersion of released radioactivke materals and predict the resulting interaction with and influece on the environment and man. Increasing use is being made of PAC tools as an inptu to the evaluation and improvement of safety for nuclear installations. The nature and extent of the assessment performed varies consdierably according to its intended purpose. Nevertheless with the increasing use of such techniques, greater attention has been given to the reliabiltiy of the mehods used and the inherent uncertainty associated with their predictions. Uncertainty analyses can provide the decision-maker with information to quantify how uncertian the answer is and what drives that ucnertainty. The often force a review of the baseline assumptions for any PCA methodology and provide a benchmark agains which the impact of further changes in models and recommendations can be compared. This process provdie valuable management informationto help priorities further actions or research.